Recent advancement in biomedical applications on the surface of two-dimensional materials: from biosensing to tissue engineering

Emily P. Nguyen a, Cecilia de Carvalho Castro Silva ab and Arben Merkoçi *ac
aNanobioelectronics & Biosensors Group, Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain. E-mail: arben.merkoçi@icn2.cat
bMackGraphe – Graphene and Nanomaterials Research Center, Mackenzie Presbyterian University, 01302-907, São Paulo, Brazil
cICREA Institució Catalana de Recerca i Estudis Avançats, Barcelona 08010, Spain

Received 15th July 2020 , Accepted 20th August 2020

First published on 22nd September 2020


Abstract

As biosensors and biomedical devices have become increasingly important to everyday diagnostics and monitoring, there are tremendous, and constant efforts towards developing and improving the reliability and versatility of such technology. As they offer high surface area-to-volume ratios and a diverse range of properties, from electronic to optical, two dimensional (2D) materials have proven to be very promising candidates for biological applications and technologies. Due to the dimensionality, 2D materials facilitate many interfacial phenomena that have shown to significantly improve the performance of biosensors, while recent advances in synthesis techniques and surface engineering methods also enable the realization of future biomedical devices. This short review aims to highlight the influence of 2D material surfaces and the properties that arise due to their 2D structure. Using recent (within the last few years) examples of biosensors and biomedical applications, we emphasize the important role of 2D materials in advancing developments and research for biosensing and healthcare.


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Emily P. Nguyen

Dr Emily P. Nguyen received her PhD in 2017 from the Royal Melbourne Institute of Technology (RMIT) University, Australia. During that time, she also had a research stay at the University of California, Los Angeles (UCLA). Since 2018, she has held a post-doctoral position in the Nanobioelectronics and Biosensors Group at the Catalan Institute of Nanoscience and Nanotechnology (ICN2), Spain. Her research interests include chemistry and functionalization of 2D materials for optoelectronic and electrochemical biosensors, and printed bioelectronics.

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Cecilia de Carvalho Castro Silva

Dr Cecília de Carvalho Castro Silva obtained her PhD from the University of Campinas (Unicamp), Campinas, Brazil (2015). Since January 2016, she has been assistant professor at MackGraphe – Graphene and Nanomaterials Research Center, Mackenzie Presbyterian University, São Paulo, Brazil. Currently, she is a visiting professor in the Nanobioelectronics and Biosensors Group at the Catalan Institute of Nanoscience and Nanotechnology (ICN2), Barcelona, Spain. She was included by Forbes-Brazil in the list “30 Under 30”, of the 30 most talented youngsters under 30 years in 2016. Her research interests are dedicated to two-dimensional materials, biosensors and bioelectronics for health-care applications.

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Arben Merkoçi

Prof. Arben Merkoçi is an ICREA Research Professor and leader of the Nanobioelectronics and Biosensors Group in the Catalan Institute of Nanoscience and Nanotechnology (ICN2), Barcelona, Spain. Prof. Merkoçi is the co-founder of two spin-off companies: GraphenicaLab, devoted to graphene patterning, and PaperDrop, devoted to clinical diagnostics. His research is focused on the integration of biological molecules and other species with micro- and nanostructures of interest in the design of novel (bio)sensors. He is also Co-Editor in Chief of Biosensors and Bioelectronics, and a member of the editorial board of Electroanalysis, Microchimica Acta and other journals.


1. Introduction

Since the isolation of graphene in 2004,1 2D materials have revolutionized many aspects of scientific and technological research. From that time, the family of 2D materials has immensely grown to include all different types of lattice configurations (from honeycomb to octahedral) with different atomic compositions and ratios, and they exhibit different types of electronic structures (conducting to insulating).2,3 The advantages of using 2D materials lie predominantly in their 2D structure that, in comparison to their bulk counterparts, exhibits many fascinating and unique properties.4–6

One area of research that has benefited greatly from 2D materials is the field of bio-applications. In particular, for biosensing and biomedical devices, tremendous progress and technological advancements have been made.7–9 In the biomedical applications of 2D materials, the biological species, such as biomolecules, bioreceptors, cells, tissues, pathogens etc., will be in direct contact with the surface of these materials. In this way, the successful development of biomedical devices based on 2D materials lies in understanding the surface properties of these materials and how to harness these properties for many different applications, such as in biosensors, implants, tissue engineering, antimicrobial and antifouling, among others. An example of that is the integration of 2D materials in biosensors. As most of the atoms of 2D materials are on the surface, their physical and electronic properties can be more effectively modified with the interaction of bioreceptors and/or biomolecules, making these materials excellent platforms for the development of highly sensitive biosensors.10–12

Based on that, in this short review, we aim to explore the surface effects in the current and a few emerging 2D materials and how the surface properties of these materials influence their applications as biosensors and biomedical devices (Fig. 1). Whilst the applications of 2D materials in biotechnology are extensively reviewed, the goal of this review is to highlight and discuss the importance of dimensionality and its impact on the properties that are exhibited. Using recent biosensing and biomedical examples, we discuss, from a materials science perspective, and demonstrate how 2D materials have improved and enhanced research in this field. A summary of recent applications in biosensors and selected biomedical applications, including antibacterial, antifouling, tissue engineering and drug delivery, are presented in Tables 1 and 2, respectively. With regard to bio-applications, we briefly discuss the main characteristics of 2D materials and their surface effects that are important in the biosensor and biomedical fields – namely surface area, electrochemical properties, and functionalization – and have facilitated their research and development.


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Fig. 1 Summary of the surface properties of two-dimensional materials (2D) and their main biomedical applications.
Table 1 Surface property effects of 2D materials on recent biosensing applications. Common properties such as high surface area, biocompatibility, excellent mechanical strength, flexibility etc. are omitted to negate repetition
2D material Surface properties Application on biosensorsa Target LOD/LR Ref.
a EC: electrochemical; ECL: electrochemiluminescence; FET: field effect transistors; PEC: photoelectrochemical; SPR: surface plasmon resonance.
Graphene and its derivatives Zero gap semiconductor, excellent conductor, high electron transfer capabilities, ease of functionalization and doping, fluorescence quenching FET (rGO) Brain natriuretic peptide (BNP) in whole blood 100 fM 13
Optical (graphdiyne) DNA 25 fM 14
Optical GO Glutathione 4 nm/0.02–20 μM 15
PEC (GO) PSA 0.3 pg mL−1/1 pg mL−1–100 ng mL−1 16
EC (rGO) Acetylcholine 4 nm/4 nm–800 μM 17
EC (rGO) Glucose nonenzymatic 0.3 μM/0.0025–0.1525 mM 18
 
2H MoS2 Semiconducting, tunable band gap (∼1.8 eV monolayer), high on/off ratios, photoluminescence, ease of functionalisation via thiol and amide chemistry, fluorescence quenching capabilities, catalytic abilities (can act as a nanozyme) Optical Intracellular caspase-3 activity 0.33 ng mL−1/2–360 ng mL−1 19
SPR BSA 14.5 nM 20
PEC Acetamiprid 16.7 fM/0.05 pM–1 nM 21
SPR E Coli 94 CFU mL−1 22
SPR miRNA-141 0.5 fM 23
FET Prostate cancer biomarkers 100 fg mL−1 24
EC miRNA-21 0.78 fm (DPV) 0.45 fM (EIS)/10 fM–nM 25
EC miRNA-21 0.26 pM/1 pM–10 nM 26
EC Cancer cells 50 cells per mL/50–106 cells per mL 27
 
2H WS2 Semiconducting, tunable band gap (∼2.05 eV monolayer), photoluminescence, ease of functionalization, fluorescence quenching capabilities SERS Cardiac marker myoglobin 0.5 aM/0.5 aM–5 pM 28
PEC DNA 2.29 fM/5 fM–50 pM 29
PEC Human epididymis protein 4 0.03 pg mL−1/0.1 pg mL−1–10 ng mL−1 30
EC Trichloroacetic acid (TCA) and NaNO2 0.4 mmol L−1 (TCA) 0.2 mmol L−1 (NaNO2) 31
EC Carbohydrate antigen 72e4 (CA72-4) 0.6 U L−1/2–50 U L−1 32
 
BP Semiconducting, direct and tunable band gap (∼1.88 eV monolayer) high carrier mobility, moderate on/off ratios, broad absorption range EC TCA, NaNO2 and H2O2 1.0 mmol L−1 (TCA), 0.033 mmol L−1 (NaNO2) and 0.67 mmol L−1 (H2O2) 33
FETs IgG 0.065–3.25 nM 34
 
MnO2 Semiconducting, exhibits nanozyme activities, broad spectrum quencher Colorimetric assays nanozyme Glutathione 300 nM 35
 
g-C3N4 Semiconducting, a large band tunable band gap (∼2.75eV monolayer) photosensitivity and activity, capability to convert light into electricity, emits strong fluorescence (λ = ∼440 nm) ECL DNA 3.6 × 10−14 M/10 μM–0.1 fM 36
 
Ti3C2 MXenes Metallic, excellent conductivity, ease of functionalization, hydrophilic surface EC Cancer biomarkers (carcinoembryonic antigen (CE)) 0.000018 ng mL−2/0.0001–2000 ng mL−1 37
Heterostructures
FTO/PDDA/g-C3N4/MoS2/CdS QDs Co-sensitization due to coupling of 2D materials, accelerate electron transfer, broaden the wavelength range of absorbed light, enhanced photoelectricity PEC DNA 0.32 pm/1 pM–2 mM 38
 
MoS2/graphene aerogel Framework increases the surface area, improved charge transfer and conductivity EC Glucose 0.29 mM/2–20 mM 39
 
ZnO nanosheets grown on 2D thin-layered MoS2 Surface electrostatic forces enabled growth of ZnO on MoS2, low surface roughness, enhanced surface affinity for negatively charged DNA, increased electron transfer EC DNA 6.6 × 10−16 M 40
 
Gold nanoparticles (AuNPs) with hybrid 2D materials consisting of boron nitride (BN) and tungsten disulphide (WS2) Improved charge transfer at the interface, introduction of new electronic states leading to enhanced performances EC H2O2 3.0 mM/0.15–15.0 mM 41
 
Molybdenum trioxide (MoO3) anchored onto reduced graphene oxide (RGO) Improved electron shuttling leading to faster transfer rates and efficient heterogeneous electron activity FET Breast cancer biomarker human epidermal growth factor receptor-2 (HER-2) 0.001 ng ml−1/0.001–500 ng mL−1 42


Table 2 Surface property effects of 2D materials in antibacterial, antifouling, tissue engineering and drug delivery applications. Common properties, such as high surface area and biocompatibility, are omitted to negate repetition
2D material Surface properties Effect Efficiency Ref.
2H MoS2 The high negative surface charge; semiconducting; low friction; low surface roughness Antifouling Antifouling layer against natural organic matter and E. coli 43
1T MoS2 The high negative surface charge; metallic; “nanoknives” Antibacterial Antibacterial properties against Gram-negative bacteria Escherichia coli 44
1T MoSe2
1T WS2
2H WS2 The high negative surface charge; high surface area; semiconducting; “nanoknives” Antibacterial Antibacterial properties against S. aureus and E. coli with antibacterial rates of 91.3% and 89.7%, respectively. 45
BP The high negative surface charge; high surface area; semiconducting; photocatalytic; “nanoknives” Antibacterial Antibacterial properties against E. coli and B. subtilis with 91.65% and 99.69% of efficiency respectively 46
Antibacterial properties against E. coli and S. aureus under irradiation (808 nm laser, 1 W cm−2) 47
GO The high negative surface charge; smooth surface; semiconducting; “nanoknives” Antibacterial Inhibition of S. aureus and E. coli. 48
GO and nano GO Irregular surface (wrinkles); “nanoknives”; photothermic Antibacterial Antibacterial properties against Gram-positive S. aureus and Gram-negative E. coli bacteria under irradiation of ultra-low doses (65 mW cm−2) of 630 nm light 49
GO/ZnO nanocomposite The high negative surface charge; oxygen functional groups; “nanoknives” Antibacterial and biofilm inhibition Inhibition of biofilm formation around 90% Escherichia coli, Salmonella typhi, Pseudomonas aeruginosa and Shigella flexneri 50
Graphene/chitosan nanocomposites Irregular surface (wrinkles); “nanoknives” Antibiofilm Inhibition of biofilm formation Pseudomonas aeruginosa and Klebsiella pneumoniae in 94 and 92%, respectively 51
GO/alginate nanocomposite bioinks High surface roughness; oxygen functional groups; negative charge Tissue engineering Enhanced osteogenic differentiation by the 3D scaffolds printed with the bioink based on mesenchymal stem cells (MSCs) and the alginate/GO 52
GO/silk fibroin (SF)/nano-hydroxyapatite (nHAp) nanocomposite CO/SF/nHAp scaffold with high capability for stimulating bone marrow mesenchymal stem cells (BMSCs) adhesion and proliferation. 53
GO/BP/poly(propylene fumarate nanocomposite High surface roughness; oxygen functional groups; phosphate groups Tissue engineering 3D printed BP/GO/poly(propylene fumarate) scaffolds enhance cell proliferation, osteogenesis and the mineralization process 54
MXenes-Ti3C2Tz – poly(lactic acid) (PLA) nanocomposite High surface roughness; high hydrophilicity; high binding energy between their surfaces and bridging Ca2+ ions Tissue engineering Enhanced the in vitro adhesion, proliferation, and osteogenic differentiation of MC3T3-E1 mouse preosteoblasts 55
hBN-gelatin nancomposite Lewis “acid behaviour” due to the vacant “p” orbital of the B atom on h-BN Tissue engineering The hBN–gelatin nancomposite fibers with high bioactivity to form bonelike hydroxyapatite; high biocompatibility in human bone cells (HOS osteosarcoma cell line) 56
hBN – poly(propylene fumarate) (PPF) nanocomposite High surface roughness; thermal conductivity Enhanced mechanical strength and adsorption of collagen I protein, improved the extracellular matrix (ECM) deposition, cell attachment and spreading for bone grafts 57
rGO Hydrophobic surface; π–π stacking interactions at the surface Drug delivery/chemotherapy Delivery of doxorubicin (DOX) with a maximal loading rate of 98% at pH 9 58
Hyaluronic acid-decorated GO nanosheet Coexistence of hydrophobic and hydrophilic surface properties; π–π stacking interactions and hydrogen bonding at the surface; good water dispersion; strong near infrared (NIR) absorption Drug delivery/photothermal therapy (PTT)/chemotherapy DOX delivery release rate of 45% in 16 h. Antitumor efficiency due to photothermally controlled and redox-triggered cytoplasmic rapid delivery of DOX molecules, with the combined chemo- and photothermal therapy 59
GO-based molecularly imprinted polymer (MIP) Drug delivery Specific recognition to carcino-embryonic (CEA) tumor markers, biocompatibility, and pH sensitivity for DOX delivery. 60
hBN-assembled with adenine π–π stacking interactions; porosity; thermal conductivity Drug delivery/chemotherapy High DOX loading capacity (up to 36.2%) by tuning the pH and temperature 61
MoS2 modified with hyaluronic acid Thermal conductivity; high near-infrared absorption Drug delivery/chemotherapy/PTT Delivery of melanin and DOX; a photothermal conversion efficiency of 55.3% 62
MXenes-Ti3C2 Thermal conductivity, free electrons, negative surface charge Drug delivery photothermal/photodynamic/chemotherapy Delivery of DOX with a high loading capacity of 84.2% and stimuli responsive DOX releasing performance mediated by pH and a NIR laser. 63
BP Thermal conductivity, high near-infrared absorption Drug delivery photothermal//chemotherapy Delivery of fluoxetine by irradiation of NIR light (808 nm); the fluoxetine loading capacity onto BP of 700%; the released capacity of 90% of fluoxetine with NIR for 30 min 64
BP-mesoporous silica nanoparticles (MSNs) Thrombolytic drug release under (NIR) laser irradiation (808 nm, 0.2 W cm−2). A loading efficiency of 92.78%. 65


2. Surfaces and reduction of dimensionality

Every 3D material is made up of a bulk that contains the majority of the atoms, and a surface, where its atoms come into contact and interact with the external and surrounding environments. By its very definition, 2D materials are all surface, as all their atoms are the surface itself, and there is no bulk. While on a macroscale this may be a drawback and can seem weak (similar to comparing a piece of paper to a thick plank of wood), interestingly on the nanoscale, the reduction of dimensionality reveals several unique properties that broaden their use and applications.8,10 With regard to biosensing and biomedical applications, here we discuss some of the unique properties that arise from reducing the dimensionality and how they can be applied or is beneficial for biosensing and biomedical applications such as antibacterial activity, antifouling, tissue engineering and improvement of the biocompatibility. Although the methods for obtaining these 2D materials and fabrication of the devices have a very important role in the overall properties, we will only briefly discuss these topics and processes in this short review as there are several recent reviews dedicated to these topics.66–69

2.1 Surface area and removal of van der Waals interactions

The first, and most obvious advantage of decreasing the dimensionality, is the increase of surface area and, by extension, the increase in the surface area-to-volume ratio.70,71 This is a very important characteristic as the higher the amount of exposed surface area, the better (and more) the reactant can have accessible contact with the material. Moreover, by having a planar structure, 2D materials have unprecedented levels of sensitivity to the surrounding environment and changes to their properties due to chemical or biological interactions are not lost in the bulk response. Besides that, the high surface area of 2D materials permits the higher density immobilization of bioreceptors, such as enzymes, antibodies, DNAs and/or aptamers, onto the surface of 2D materials, improving the sensitivity of biosensors based on these materials. Electrical biosensors based on 2D materials, such as chemiresistors and field effect transistors (FETs, discussed later), take advantage of this property.2,72 For example, Bazylewski et al.73 recently described a solid state chemiresistor based on cysteine modified MoS2 for the rapid (within a second) sensing of cadmium ions in drinking water in the sub-ppb range (1–10 ppb, Fig. 2(a)). The sensor also exhibited excellent selectivity towards cadmium as there was negligible interference from the other heavy metals.
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Fig. 2 (a) Bar graphs demonstrating the sensitivity of (i) MoS2-Cys sensors to different metal ions depending on the pH and metal ion used and (ii) MoS2-COOH compared to MoS2-Cys using a 10 ppb solution at varying pH, and (ii) charge transfer at the nanostructured surface of MoS2-Cys films (adapted with permission from ref. 73. Copyright (2020) American Chemical Society, further permission related to the material excerpted should be directed to the ACS). (b) Schematic illustration of real-sample analysis (adapted with permission from ref. 106. Copyright (2019) American Chemical Society). (c) (i) Synthetic route to EGODP (path a) and to MIX (path b), (ii) CVs recorded at EGO (red line), EGODP (blue line) and MIX (green line) modified-SPEs in 0.1 M PBS (pH 7.0) and 0.1 M KCl after 20 potential cycles, and (iii) voltammetric traces recorded at the same modified electrodes after addition of 0.5 mM NADH; only the forward scan after subtraction of the relevant signal obtained in the absence of NADH is reported (adapted with permission from ref. 113, Copyright 2018 © IOP Publishing. Reproduced with permission. All rights reserved.). (d) (i) Attachment of active proteins to MoS2 with the optical and AFM images of the pristine and modified material with mCherry after functionalization and (ii) bright field, confocal fluorescence microscopy images in GFP (green) and mCherry (red) channels, and fluorescence images overlaid onto BF images, after the protein attachment process (adapted with permission from ref. 114. Copyright 2018 American Chemical Society). (e) (i) Schematic of the defective graphene (DGr) based sensor with the response to 100 ppm NO2 for varying (ii) irradiation influence and (iii) H2 etching time at room temperature and (iv) comparison of the responses of the DGr-based gas sensor to different gases at room temperature (adapted with permission from ref. 121, licensed under a Creative Commons Attribution (CC BY) license, Copyright 2019 AIP Publishing).

Within a monolayer of 2D materials, the bonds that hold the atoms together are very strong. The nearby in-plane atoms are covalently bonded with low defect density and thus give rise to superior mechanical properties.74 For example, graphene, which is reported be the stiffest 2D material with the highest Young's modulus of ∼1 TPa,75–77 has a tensile strength that is 1000 times stronger than its bulk counterpart, graphite, and is 100 times stronger than steel. Yet even with their high mechanical resistance, due to the atomic thickness of the 2D crystal, 2D materials show exceptional flexibility and are ideal candidates for next generation flexible electronics, which could be used in wearable health-monitoring devices, biocompatible electronic skins and implantable biomedical devices, such as biosensors and prosthesis (discussed later).78,79

While mono and few layer 2D materials offer numerous advantages as aforementioned, the stacking and combination of different 2D materials together also has its own merits and broadens the use and potential applications of 2D materials. Within the class of 2D materials, there are many types of materials with unique electronic structures ranging from conducting to insulating. As such, there are many possibilities for creating layer-by-layer solids, known as 2D or van der Waals heterostructures, that can have unique and synergistic properties.80–82

The stability and stacking of the layers is achieved through weak van der Waals interactions at the interface of each 2D monolayer. However, as these interactions are relatively weak, the intrinsic properties of the individual layers are still maintained or present with other intriguing properties that are not observed in the single 2D material nor it's bulk.83,84 Although the use of the heterostructure format is primarily for energy harvesting and storage, within recent years, there has been growing interest in its implementation for biosensing, in particular for photoelectrochemical biosensing (see the Electrochemical section).85,86

2.2 Confinement of electrons

As aforementioned, another fascinating and important aspect of 2D materials, upon reduction of their dimensionality, is the rise of unique electronic and optical properties that are not typically observed in the bulk. The manifestation of these properties can be attributed to the confinement of electrons into a 2D plane.87 Several popular 2D materials and their properties are summarized in Tables 1 and 2. This is a highly interesting aspect to 2D materials, and there are many recent reviews that describe the emergence of these properties and discuss them in detail.88,89

Briefly, in materials, the electronic and optical properties are dictated by their electronic band structure, which describes the electron movement through the material. Upon reducing the dimensionality, the periodicity in the direction perpendicular to the 2D plane is removed and results in large changes to the band structure and the electronic and optical properties that are expressed.90 These modified band structures are responsible for the many unique properties found in 2D materials, such as the high conductivity in graphene and the photoluminescence of monolayer MoS2. Moreover, as the band structures dictate the properties, modifying and tuning of the band structures also allow for tailoring the properties for specific applications and outcomes. In particular for biosensing, applications such as FETs and electrochemical based sensors can benefit greatly as on/off current ratios can be modulated and improve or facilitate faster electron transfer, thus leading to more sensitive biosensors.91 Tuning of the band structure can be achieved by various approaches, including electrical, mechanical and chemical means.92,93

2.3 Defects and functionalization

In its bulk 3D form, the material layers are weakly held together by van der Waals interactions that can be easily broken by applying an external force, such as mechanical or shear stress.8,94,95 This approach is known as the top-down approach, as it starts with a bulk piece as the source of 2D materials, and includes exfoliation methods such as sonication assisted exfoliation, lithium intercalation exfoliation and, the now famous, scotch-tape method. The other approach, known as the bottom-up approach, is to start with a substrate where the 2D material will be assembled from chemical precursors under specific conditions, typically high temperatures and pressures. While each approach has its merits, there are various limitations that arise and must be addressed depending on the desired application or outcomes.

While there are many reports on the influences of various factors and reaction parameters during the synthetic process,96–98 a key issue that presents itself in both approaches is the pristiness of the resulting 2D material, in particular for applications that require monolayers. In top-down approaches, exfoliation is unpredictable and can result in a 2D material of various layers (i.e. monolayers, bi-layers, bulk etc.), structures (i.e. nanosheets, nanoflowers, quantum dots etc.) and surface defects and vacancies. Similarly, the bottom-up approach can also produce 2D materials with surface/atomic vacancies and replacement of atoms in the crystal lattice (doping). Fortunately, whilst these defects can severely affect the properties, these defects can also be used to fine tune the properties or to give the 2D material additional functionalities.99

Perfection is not always everything, and this can be particularly true for 2D materials. Whilst pristine crystalline materials are necessary for electronics, the presence of defects has been shown to change or enhance the physical and electrochemical properties, and great efforts have gone into investigating and harnessing these effects for better and faster applications.99–101

Surface vacancies, where an atom is missing from the crystal lattice, are often the result of the violent nature of exfoliation methods, such as ion intercalation, or intentionally created by various means, such as irradiation. For example, point defects in graphene, such as the absence of carbon atoms (either/both sp2 or sp3), can lead to changes in the electronic sp2 structure and affect the chemical reactivity on the surface.102 Chen et al.103 recently reported a systematic evaluation of the electronic structure of MoS2 with lattice defects. Here, by purposefully creating sulphur vacancies on CVD grown MoS2, the authors found that the ‘defective’ samples had faster hydrogen evolution kinetics in comparison to pristine samples. This increase in activity can be attributed to the formation of new catalytic/active sites in the basal plane.104,105 Moreover, the authors also examined the effects of various substrates, such as gold, graphene and h-BN, and found that the electronic energy levels were influenced by the charge transfer at the interface.

Doping is an effective approach to increase the catalytic or electronic properties of 2D materials. In particular, doping with other metals can introduce strains and defects to the basal plane and, ultimately, increase the density of active sites, and thus the electrocatalytic activity and the rate of charge transfer.92 Harnessing the effects of both metal atom doping and defective sites, Ramaraj et al.106 developed a new electrocatalyst for biosensing using manganese (Mn) doped MoSe2via a hydrothermal synthetic process (Fig. 2(b)). By introducing Mn into the crystal structure, the authors observed the creation of Se vacancies107 that led to increased catalytic and electronic activities. Moreover, the vacancies were also used as active sites for the effective immobilization of enzymes, which in their case was myoglobin. The modified 2D material was then evaluated by EIS for hydrogen peroxide sensing with a reported ultralow detection limit of 0.004 μM and a sensitivity of 222.78 μA μM−1 cm−2. This work not only demonstrates the advantages of doping, but also the additional benefit of surface vacancies.

With regard to biosensors, and other applications that may require selectivity, selectivity is a primary concern that should be considered. As the selectivity is highly influenced by the nature of 2D materials and the target analyte, approaches to integrating and modifying the surface of the sensing material are the most effective ways to fine tune the sensor itself. In particular, the interactions of 2D materials and the target molecule follow two distinctive mechanisms: chemisorption and physisorption.2,108

Chemisorption is when there are covalent interactions between the surface of the 2D material and other molecules, such as the target analyte or ion. This is a common approach to tailor the properties of 2D materials, as the electronic band structure can be modulated.95 In the scope of bio-applications, defect sites can be used as anchoring points for chemical functionalization of molecules to enhance the selectivity.109,110 This approach is typically adopted for biosensing, where receptor molecules are employed for their specific recognition capabilities to target analytes. Moreover, by functionalizing and increasing the amount of analyte-surface binding sites, the electronic properties of the material can be modulated or tailored to improve the sensitivity and lower the limit of detection.3,111,112 A recent example was demonstrated by Vulcano et al.113 who compared the sensing capabilities of electrochemically exfoliated GO with and without surface functionalisation. The surface of GO was covalently functionalized with dopamine, using NHS/EDAC as a linker, to target NADH (Fig. 2(c)). Due to the presence of dopamine, which introduced 1,2-dihydroxyphenyl moieties to the surface, the sensitivity of the modified GO showed enhanced sensitivities towards NADH by 180% and improved the limit of detection. Furthermore, they concluded that the performance improvement could also be attributed to the increased chemical stability of the electrode and measurements.

Chu et al.114 reported the covalent functionalization of MoS2 with a diazonium salt that preserved the semiconducting properties (Fig. 2(d)). However, interestingly, the author's DFT studies suggested that only a single surface vacancy was required to make the entire MoS2 surface functionalizable. The authors describe this effect as similar to the ‘cooperative effect’, as seen with bioploymers such as proteins and nucleic acids, where the covalent interactions between molecules or surfaces are strengthened upon binding events with other molecules. The authors then extend their technique to covalently tether active green fluorescent protein and mCherry to the MoS2 surface, demonstrating the use of this approach for bioimaging and biosensing. By examining the fluorescence images, it was revealed that the dyes had attached only to the areas where the MoS2 was functionalized, and that the fluorescence was increased when both dyes were used together.

Physisorption occurs when other molecules and ions interact with the surface of the 2D material without any covalent bonding. These interactions typically occur due to the reactivity, and compatibility, of the functional groups on the molecule to the surface of the 2D material, such as hydrogen bonding, electrostatic forces, pi–pi interactions, cation–pi, etc. For example, molecules are able to physisorb onto the basal planes of MoS2 due to the interactions between the molecule and the surface through van der Waals forces.115 Moreover, the electronic characteristics of pi–pi systems, such as aromatic molecules, have been shown to have influences that are able to modify the electronic and optical properties of 2D materials.116,117

For applications that follow the physisorption mechanism, the sensors typically have rapid response times and fast recoveries, as there is no chemical reaction required to attach and detach the analyte to the electrode/surface of the 2D material. Some studies have achieved higher adsorption of molecules onto the sensor surface by inducing the defect sites on the surface of the 2D material.118–120 Recently, Ma et al.121 compared the use of defective and pristine graphene as a gas sensor for NO2 at room temperature (Fig. 2(e)). The response of the defective graphene based sensor towards 100 ppm NO2 was 13 times higher than that of the pristine graphene sensor, and it also showed excellent selectivity, reproducibility and stability. The authors found that by tuning the defect density and size, via ion irradiation and H2 etching, more adsorption sites were created and, thus, improved the performance of the sensor.

3. Recent biosensing and biomedical applications

As discussed, 2D materials are very well-suited for biosensing and biomedical applications and offer many advantages. In this section, we highlight a few of the more recent studies of 2D material based bio-applications, and we discuss how these applications have harnessed the 2D planar structure and the unique properties for more reliable or enhanced operation. In particular, we focus on the common uses of 2D materials for biosensing, which include electrochemical, field effect transistors (FETs) and optical methods, and the more recent biomedical technologies, such as antibacterial and antifouling applications, drug delivery and tissue engineering. For clarity, we organize this section on the basis of the applications and discuss the properties and types of 2D materials which are typically used in the field.

3.1 Biosensing

The unique and versatile properties of 2D materials offer great advantages for biosensing applications. In many of these cases, the 2D material is used as the sensing element (working electrode) to enhance the detection signal upon interaction with the analyte or to facilitate charge transfer. Moreover, in this regard, recent biosensing trends have also implemented 2D materials in many on/off biosensing platforms, due to their conducting or semiconducting properties, and also as fluorescence quenchers in optical systems.
3.1.1 Electrochemical. On a commercial level, electrochemical biosensors are currently the most widely available and have been developed to integrate and target various bioanalytes, such as enzymes/enzymatic reactions, nucleic acids, antibodies etc.122 and have been adopted in various formats, including field-effect transistors (FET),123 electrochemical impedance/amperometric sensors,124,125 and photoelectrochemical sensors.126 Typically, the sensing principle of electrochemical biosensors is to convert the interaction between the recognition element and analyte into an electric signal. These interaction events are electron charge transfer processes that occur at the electrode surface; thus the electrode material has great effects on the performance of the sensor.127,128

Nanostructures and nanomaterials, like 2D materials, have facilitated considerable progress in biosensor research and development. 2D materials are ideal substrates for the development of electrochemical biosensors, due to their large specific surface area, outstanding electrical properties, and excellent biocompatibility.90,129,130 These characteristics create a favorable microenvironment for the immobilization of bioreceptors on the surface of these 2D materials, conferring selectivity to these electrochemical sensors. Moreover, by integrating 2D materials and harnessing their unique properties, performance parameters, such as the sensitivity and selectivity, can be greatly enhanced.131 In this regard, for electrochemical sensing, 2D materials with high conductivities, such as graphene and reduced graphene oxide, are typically employed to increase the charge transfer and conductivity of the electrode surface, and consequently increase its sensitivity. In fact, the use of graphene and its derivatives is widely examined and numerous studies have demonstrated that by coupling functional graphene and electrochemical methods, the overpotential was effectively decreased, while the current response was greatly enhanced.132 On the other hand, 2D materials with semiconducting properties, such as several MXenes and transition metal dichalcogenides, have also been widely explored for electrochemical sensing due to their surface properties and tunable intrinsic band gaps. Wang and Zhu et al.133 took advantage of the surface properties of the MXene-Ti3C2 to fabricate a mediator-free electrochemical biosensor to detect hydrogen peroxide (H2O2). Hemoglobin (Hb) was encapsulated onto the MXene-Ti3C2 layers by the use of Nafion and the biosensors exhibited good performance for the amperometric detection of H2O2 with a wide linear range of 0.1–260 μM, as well as an extremely low detection limit of 20 nM. The surface of the MXene-Ti3C2 provided a favorable microenvironment for Hb to undergo a facile electron-transfer reaction, in this way contributing to the excellent sensitivity of this biosensor to detect H2O2. In addition to the high surface area, Kim et al.134 also took advantage of the flexibility of 2D materials and developed a flexible electrochemical biosensor based on MoS2 for the detection of three endocrine hormones in real serum samples (Fig. 3(a)). By adopting a competitive assay and enzyme reaction mechanism, the novel biosensor displayed high sensitivity and reproducibility that were comparable to standard immunoassay equipment, thus further demonstrating the versatility of 2D materials for electrochemical biosensing.


image file: d0nr05287f-f3.tif
Fig. 3 (a) Process of competitive assay and enzymatic reaction mechanism for PTH, T3, and T4 antigens (immune complexes): (i) immobilization of standard antigens (Ag) and the competitive reaction between sample antigens and the antigen-conjugated surface of MoS2 on a flexible Au-PI electrode with the corresponding antibodies (Ab) and (ii) signal on/off by competitive reaction with the enzymatic reaction mechanism.(reprinted (adapted) with permission from ref. 134, Copyright 2020 American Chemical Society). (b) Comparison DPVs of 2.0 × 10−5 M myoglobin with (i) ZnO, (ii) MoS2 and (iii) ZnO/MoS2 modified electrodes with and without ssDNA and dsDNA (adapted with permission from ref. 137. Copyright 2018 Elsvier). (c) (i) Schematic illustration of the biosensor construction process and (ii) the photocurrent generation mechanism of the PEC biosensor (adapted with permission from ref. 140. Copyright 2019 Elsevier).

Recently, a typical trend that is seen with 2D materials is the pairing of the 2D material with other 2D materials. Since the first demonstration of 2D materials as biosensors, many have discovered that there are numerous factors that influence the performance of the sensor and that each material suffers from its own drawbacks. However, due to the surface nature of the 2D material, it is quite easy and facile to combine various materials together to synergistically enhance the material and the sensor.

For example, it is widely reported that MoS2 exemplifies great catalytic activities due to the exposed edges,70,135 but often suffers from low electrical conductivities and a tendency to stack or agglomerate, which decreases the accessible surface area136 and affects the electrochemical performance. In a synergistic approach, Yang et al.137 electrodeposited ZnO nanosheets onto an ultrasonicated exfoliated MoS2 scaffold for the electrochemical detection of DNA (Fig. 3(b)). The negatively charged MoS2 nucleated and supported the growth of ZnO through electrostatic interactions, while the presence of the positively charged ZnO improved the capacity of the nanocomposite for DNA immobilization and improved the electrochemical performance and an ultralow detection limit of 6.6 × 10−16 M was obtained. In another example, Jeong et al. demonstrated the synergistic effects of 2D MoS2 and graphene in an aerogel for glucose detection.136 In addition to harnessing the catalytic ability of MoS2, the 3D aerogel structure increased the surface area, which allowed for higher amounts and better immobilization of glucose oxidase, while the continuous graphene based framework exhibited superior conductive properties when compared to 2D MoS2/rGO. Using flow-injection amperometric analysis, their MoS2/graphene aerogel glucose sensor had a rapid response time of 4 s, a sensitivity of 3.36 lA mM−1, a LOD of 0.29 mM and a linear detection range between 2–20 mM.

Photoelectrochemical (PEC) biosensing and bioanalytics are becoming increasingly popular in recent years, and has even created its own subclass of innovative research. In comparison to conventional electrochemical and optical methods, the main attraction of this method of sensing can be attributed to the remarkable sensitivities and reduced background signals that can be achieved due to the total separation of the different energy forms of the excitation source (light) and the detection signal (electricity). Furthermore, the instrumentation of PEC is simpler, more cost effective and easier to miniaturize in comparison with optical techniques, which typically require additional apparatus that is often more complicated and expensive.138,139

As the PEC detection signal mainly stems from the photoelectric conversion capabilities of the photoactive material, the choice of electrode material is thus critical to the overall performance. Due to the optoelectronic properties and surface nature of 2D materials, 2D materials are ideal candidates for construction of PEC biosensors, in particular 2D heterostructures. Specially, the semiconducting 2D materials are ideal for PEC platforms due to their light absorbing capabilities, conduction and valence band positions, tunable band gaps, and flexibility as planar structures. In this regard, TMDs, such as MoS2 and WS2, and graphitic carbon nitride (g-C3N4) have been widely explored for PEC biosensing. Wang et al.140 proposed a novel PEC biosensor for ultrasensitive detection of miRNA-396a based on a MoS2/g-C3N4/TiO2 heterojunction decorated with antibody functionalized AuNPs for signal amplification (Fig. 3(c)). The developed biosensor had a low detection limit of 0.13 fM and a linear range of 0.5–5000 fM. The authors attributed the high sensitivity of the sensor to the staggered matching of the electronic band structures of the MoS2/g-C3N4/TiO2 heterojunction, which increased the charge carrier concentrations when irradiated.

3.1.2 Field-effect transistors (FETs). Biosensors based on field-effect transistors (FETs) are highly attractive as they promise real-time label-free electrical detection, scalability, inexpensive mass production, miniaturization, the use of alow volume of sample, and the possibility of on-chip integration of both sensor and measurement systems.141 2D semiconductor materials, such as graphene, TMDs and black phosphorus (BP), have attracted significant interest for the development of highly sensitive biosensors based on FET devices,22 replacing the traditional silicon technology.142 It is due to the outstanding properties of these materials such as the high charge carrier mobilities (μ) (μgraphene = 15[thin space (1/6-em)]000 cm2 V−1 s−1, BP ∼ 1000 cm2 V−1 s−1 and the acceptable μ2H MoS2 ∼ 60 cm2 V−1 s−1), high flexibility, biocompatibility, large specific surface area and facile chemical functionalization.22 In addition, a monolayer of graphene allows all carbon atoms to be exposed to the surroundings, in this way the carbon atoms can directly interact with the analyte, leading to increased sensitivity.

A typical FET biosensor based on 2D materials for evaluating liquid samples consists of a 2D material layer (the semiconductor channel), deposited on top of an insulator substrate, between two metal electrodes, called by the source (S) and drain (D). A third electrode, the gate electrode (usually a reference microelectrode, Pt wire or Ag/AgCl), is immersed in an electrolyte solution, where the 2D semiconductor material is exposed. The current between the S and D electrodes (Ids) could be modulated by an electric field generated by the gate voltage (Vgs), due to the change of the 2D material carrier densities.143,144 Upon interaction of an analyte on the 2D material surface, even at low concentrations, the values of the conductance, represented by the Ids current, change significantly.

FET biosensors based on 2D materials have drawn attention due to their impressive sensitivity. This feature is highlighted in the recent work of Seo et al.145 The authors developed a graphene FET (GraFET) biosensor for the label free detection of SARS-CoV-2 in clinical samples without any sample treatment step. For this, the authors immobilized a specific antibody against SARS-CoV-2 spike protein on the graphene surface through non-covalent functionalization with 1-pyrenebutanoic acid succinimidyl ester (PBASE), by the pi–pi interactions between the graphene surface and pyrene group of PBASE (Fig. 4a(i)). The GraFET biosensors were able to detect the SARS-CoV-2 spike protein at concentrations of 100 fg ml−1 in the clinical transport medium used in the nasopharyngeal swab (Fig. 4a(ii)). In addition, the GraFET biosensors successfully detected SARS-CoV-2 in clinical samples from patients with a LOD: 2.42 × 102 copies per ml (Fig. 4a(iii)).


image file: d0nr05287f-f4.tif
Fig. 4 (a) Graphene-based field effect transistor biosensors for COVID19 diagnosis. (i) Schematic diagram of the COVID-19 FET sensor operation procedure. Graphene as a sensing material is selected and the SARS-CoV-2 spike antibody is conjugated onto the graphene sheet via 1-pyrenebutyric acid n-hydroxysuccinimide ester, which is an interfacing molecule as a probe linker. (ii) Real-time response of the COVID-19 FET toward the SARS-CoV-2 antigen protein in UTM, insert the SARS-CoV-2 spike protein. (iii) Real time response of the COVID-19 FET toward SARS-CoV-2 virus from the clinical sample (reproduced with permission from ref. 145. Copyright 2020 American Chemical Society). (b) Scheme and characterization of the flat and crumpled graphene FET biosensor. (i) Cross-sectional scheme of the flat (left) and crumpled (right) graphene FET DNA sensor. Probe (black) and target (red) DNA strands are immobilized on the surface of graphene. The blue dot lines represent the Debye length in the ionic solution and the length is increased at the convex region of the crumpled graphene, thus more area DNA is inside the Debye length, which makes the crumpled graphene more electrically susceptible to the negative charge of DNA. The inset boxes represent the qualitative energy diagram in K-space. Graphene does not have an intrinsic bandgap. However, crumpled graphene may open the bandgap. (ii) SEM images of crumpled graphene. The scale bar is 500 nm (iii) ELD structures of flat (left) and crumpled graphene (right). Loosely structured EDL of crumpled graphene leads to a smaller capacitance value (ref). Nucleic acid absorption and hybridization test on the flat and crumpled FET. (iv) Dirac voltage shift of the FET sensor with miRNA detection of hybridization. Target RNA spiked in human serum was treated on the FET sensor (adapted with permission from ref. 148. Copyright 2020 Springer Nature).

The sensitivity of FET-based biosensors is not only related to the semiconductor material used as a channel, but also to the ionic concentration of the solution containing the analyte.146 One of the major hurdles to lower the detection limit of the FET-based biosensor is shielding of the molecule charge by the counter ions in solution (termed Debye shielding). Outside the Debye length (the length of the electrical double layer (EDL)), which is <1 nm in physiological solutions, the charges are electrically screened. An increase in the Debye length can result in a reduced screening effect and allow for a more sensitive electrical detection of charged biomolecules.147,148 Hwang et al.148 were pioneers in exploring the deformation of the graphene surface, by curving or bending it, to improve the sensitivity of the GraFET biosensors for detection of nucleic acids (DNA and/or RNA). The enhancement could be attributed to the modulation of the Debye length (or volume) and by the induced band-gap opening in the graphene channels due to strain. The probe DNA anchored via a linker molecule on the flat and crumpled graphene channels of the FET biosensors was affected in different ways by the Debye length. The flat graphene has a constant Debye length, whilst in the crumpled graphene, the Debye length oscillated at the peaks and the valleys of the crumpled surface (Fig. 4b(i)). The surface of crumpled graphene was disorganized with herringbone-like structures (Fig. 4b(ii)) and these structures contributed to the disorganization in the distribution of the counter-ions of the EDL over a longer distance away from the surface of the crumpled graphene. This accounted for decreases in the screening effect for the crumpled graphene in relation to the flat graphene (Fig. 4b(iii)). The theory proposed by the authors was fundamental from the results obtained by density functional theory (DFT) and molecular dynamics (MD) simulations, and from the expressive results of the determination of miRNA spiked in PBS buffer and undiluted human serum samples at a concentration of 600 zM and 20 aM, respectively, when compared to the negative control testes (Fig. 4b(iv)). In this way it is clear that the shape, deformation and roughness of the surface of the 2D materials also have an important role in the sensitivity of FET biosensors.

Other 2D materials such as 2H-MoS2 (semiconductor phase) and BP have been explored in the development of FET biosensors (Table 1). The FET biosensors based on 2H MoS2 exhibit an advantage over GraFETs that is the high current on/off ratio (Ion/off), that can exceed 1 × 108, which is much higher than that of GraFET biosensors.22,149 As monolayer 2H MoS2 is a semiconductor with a direct band gap of 1.8 eV, and in comparison with graphene which has a bandgap of 0 eV, offers a much higher gate-tunable conductance for 2H MoS2 based FETs. This can be attributed to low Ion/off values and, in some conditions, leakage currents which can impact the sensitivity of these devices.22,150

The few-layer BP demonstrated interesting characteristics for the development of FET devices, as a p-type semiconducting material with a mobility up to 984 cm2 V−1 s−1 (10 nm sample) and a direct band gap that is tunable from 0.3 eV for bulk BP to 2.0 eV for monolayer BP.151 However, the biggest challenge that needs to be overcome for using BPFETs as biosensors is the poor chemical stability of this material in the presence of oxygen and water. BP can degrade quickly to oxygenated phosphorus (POx), which makes biosensing processes on its surface unfeasible.22

For using BPFET as a biosensor, Chen et al.34 passivated the surface of the BP with a thin film of Al2O3, as a dielectric layer, to protect the BP from the oxidation process and to immobilize gold nanoparticles labelled antihuman IgG antibody onto Al2O3, for the label free detection of IgG antigens. The BPFET biosensor exhibited a low LOD of ∼10 ng mL−1 due to the electrical properties of the BP and the amplification signal of the gold nanoparticles. However, many efforts still need to be made in order to develop strategies for stabilizing the surface of BP in aqueous environments and allowing for exploration of the real potential of BPFETs as biosensors.

3.1.3 Optical. By exhibiting tunable optoelectronic properties, 2D materials are also ideal materials for optical sensors. Their unique optical and vibrational characteristics, such as photoluminescence, enhanced photoelectron interactions and plasmonic behaviors, have facilitated the construction of high performance biosensors with remarkable sensitivities and ultrafast response times that rival, and can potentially surpass or replace the use of current electrical biosensors.152–154 Typically, 2D based optical sensors will employ a 2D material as a substrate, due to the planar structure and high surface area and aforementioned properties, rather than an optical label. In particular, TMDs pose as ideal candidates for optical based sensing due to their tunable band gaps and abilities to absorb in the visible and NIR ranges upon doping.155 The most common 2D material based optical sensors include surface plasmon resonance (SPR), surface-enhanced Raman spectroscopy (SERS) and fluorescence based sensors.

Both SPR and SERS methods offer outstanding sensitivities and show the capability of single molecule and label free detection. Considered as a standard biophysical tool,156 surface plasmon resonance (SPR) sensors have found increasing bio-applications, ranging from environmental monitoring to healthcare diagnostics.157 There are many advantages of SPR sensors, including rapid analysis, high specificity and dynamic measurements, amongst many others. Using an emerging 2D material, atimonene, Xue et al.158 developed an SPR biosensor for ultrasensitive detection of miRNA (Fig. 5(a)). Despite possessing a similar lattice structure to graphene, the author's DFT studies revealed that antionmene exhibits strong spin–orbit coupling and has a greater interaction with ssDNA due to the higher delocalized 5s/5p orbitals. Motivated by this, the authors then obtained 2D atimonene nanosheets by liquid phase exfoliation and coated them onto a gold film for SPR sensing. To add selectivity to the antimonene, probe DNA conjugated gold nanorods were adsorbed onto the surface. Using miRNA-21 and miRNA-155, the ultralow detection limit of 10 aM was obtained, surpassing current sensing methods, and a concentration-dependent response up to 10−11 M.


image file: d0nr05287f-f5.tif
Fig. 5 (a) Fabrication of a miRNA sensor integrated with antimonene nanomaterials. The schematic illustration of the strategy employed to detect antimonene-miRNA hybridization events (reproduced with permission from ref. 158. Copyright 2019 Nature). (b) Schematic showing stepwise synthesis and fabrication of a Au-WS2 nanohybrid based SERS active platform (reproduced with permission from ref. 162. Copyright 2018 Springer). (c) Schematic illustration of the design rationale for lectin detection (reproduced with permission from ref. 167. Copyright 2018 Springer). (d) Scheme of the developed lateral flow (reproduced with permission from ref. 168. Copyright 2018 Elsvier).

SERS has also emerged as a powerful and reliable technique for bio and chemical sensing and analysis. The integration of 2D materials for SERS is typically focused to enhance the Raman signal by increasing the charge transfer rate between the (sensor) surface and the adsorbed analyte. In particular, TMDs exhibit excellent charge transfer properties159 and SERS activities when coupled to plasmonic gold or silver nanoparticles.160,161 Due to its compatible work function, WS2 has been shown to provide better SERS enhancement than MoS2, the most widely studied transition metal dichalcogenide.162 Motivated by this, Shorie et al.163 developed a SERS based aptasensor for the label free detection of myoglobin using a WS2-AuNP nanohybrid (Fig. 5(b)). The in situ coupling of WS2 and AuNP together greatly enhanced the SERS platform both chemically and electromagnetically, while the specific aptamers increased the selectivity. The sensor displayed enhanced sensitivity, as a low limit of detection of 0.5 aM was obtained, and great selectivity for myoglobin whilst in the presence of hemoglobin and bovine serum albumin.

Although SPR and SERS biosensors have achieved exceptional results, these platforms are not always user friendly as specific instruments and setups are required. Consequently, naked-eye detection methods are potential solutions as they are easy to use and, additionally, can be adapted for point of care (POC) devices. The most common use of 2D materials is in fluorescence based biosensors, where the exceptional intrinsic fluorescence-quenching abilities of 2D materials are harnessed. In particular, for microfluidic and on/off sensors,164 fluorescence based biosensors typically employ the Förster resonance energy transfer (FRET) approach that pairs a fluorophore (fluorescent donor) and a quencher (light absorbing acceptor) to obtain a signal.165,166 Yang et al.167 demonstrated the FRET approach for multiplexed sensing of lectins and bacteria with a fluorescence array that uses saccharide functionalized multi-colored QDs and 4-mercaptophenylboronic acid (PBA) functionalized MoS2 nanosheets (Fig. 5(c)). In their array, through the chemical interaction of the saccharides and PBA, the QDs are initially absorbed onto the MoS2 and the fluorescence is quenched. Then, depending on the lectins that are present/added, the QDs begin to detach from the MoS2 surface, thereby restoring the fluorescence. This effect was attributed to the diverse affinities of the lectins to the saccharides, which causes competitive binding of the lectins to the QDs, and leads to desorption from the MoS2 surface. In the presence of multiple lectins, a distinct fluorescence response pattern was observed and analyzed with linear discriminant analysis. The authors concluded that there was 100% accuracy in identification between multiple lectins and bacteria reaching detection limits as low as 3.7 nM and 66 cfu mL−1, respectively.

In another example, Zamora-Gálvez et al.168 used a similar approach for naked-eye detection of immunoglobulin G (IgG) in a paper-based lateral flow immunoassay (Fig. 5(d)). Here, the authors used CdSe QDs modified with anti-human IgG functionalized as the fluorescence probe, graphene oxide nanosheets as the quencher and SiO2 beads as a spacer. The SiO2 beads are functionalized with the detection antibodies that capture the analyte and flow towards the test and control lines via capillary action. Upon reaching the test line, the analyte forms an immunosandwich with the QDs and the (pre-attached) SiO2. The GO is then added to the paper strip as the ‘revealing’ agent. The presence of the SiO2 bead creates enough distance between the QD and the GO that hinders quenching of the fluorescence, whereas, without the analyte and the spacer bead, the fluorescence can be easily quenched as the GO comes in direct contact with the QDs.

3.2 Biomedical

2D materials are receiving increased interest in biomedical applications owing to their special physicochemical and surface properties. In this section, we will focus on the recent application of 2D materials for antibacterial, antifouling, tissue engineering and drug delivery. A widely studied approach is the use of 2D materials for optical biomedical applications, such as bioimaging, photothermal therapy and theranostics. While the surface area and the number of layers have a great influence on the optical properties of 2D materials, these optical biomedical applications will not be thoroughly discussed in this review, as their applications rely more on the intrinsic optical properties than on the surface of the 2D material. However, great progress has been made in this field of biomedical research and there are many recent reviews that brilliantly discuss these achievements.169–172
3.2.1 Antibacterial. 2D materials have attracted considerable attention in biomedical applications due to their antimicrobial activity.173–175 The antimicrobial activities of 2D materials, such as graphene materials (GMs, defined by graphene and its derivatives such as GO and rGO), MoS2, h-BN, BP and some MXenes, are related to the physicochemical and structural characteristics of these materials. So, in this way, the surface properties of these materials play an important role, as all the interactions between the 2D materials and these pathogens, mainly bacteria, occur at their surface.

The first materials that had their antimicrobial activities investigated were GMs in 2010.176 Since then, several mechanisms have been proposed to explain how these materials display antimicrobial activities. However, the main three most accepted mechanisms are: (i) nanoknives derived from the action of sharp edges; (ii) oxidative stress mediated with the production of reactive oxygen species (ROS), and (iii) wrapping or trapping of bacterial membranes derived from the flexible thin-film structure of GMs.177,178 Other recent mechanisms have been proposed as the extraction of lipid bilayers,179 the interference of protein–protein Interactions (PPIs)180 and the “self-killing” effect.181Fig. 6(a) summarizes the main mechanisms of the antimicrobial activities of GMs.


image file: d0nr05287f-f6.tif
Fig. 6 Antimicrobial properties of 2D materials. (a) Mechanisms of the antimicrobial activities of GMs (reproduced with permission from ref. 177. Copyright 2016 American Chemical Society). (b) Antibacterial membrane based on 2D Ti3C2Tx (MXene) nanosheets. (i) Ti3C2Tx (MXene) membrane on a PVDF support and (ii) its cross-sectional SEM image. (iii) Cell viability measurements of E. coli and B. subtilis grown on fresh and aged Ti3C2Tx (MXene) membranes for 24 h (adapted from ref. 189, Copyright 2017 Springer Nature). (c) The effect of the shape of the MoS2 nanosheets on their antibacterial properties. (i) The optical images of S. aureus, (ii) E. coli incubated 4 h with MoS2 nanomaterials of different concentrations (adapted with permission from ref. 191. Copyright 2020 Elsevier).

The nanoknife mechanism is related to the extremely sharp boundaries of the GM nanosheets. The blade like GM nanosheets can cause physical damage to the membranes of microbes and leakage of the intracellular matrix, thus leading to inactivation of the microorganisms.177,178 In this way, the control of the number of layers (exfoliation degree) in the GMs is a crucial factor for the antimicrobial activity by this mechanism, as the number of layers can increase the thickness of the GM nanosheets, thus decreasing the effectiveness of the nanoknife effect.

The oxidative stress mechanism can be attributed to the capacity of the GM nanosheets to induce oxidative stress in bacteria. Oxidative stress can interfere with bacterial metabolism and disrupt essential cellular functions, leading to cellular inactivation or even cell death.177,178 GM nanosheets are able to mediate the generation of ROS (such as hydrogen peroxide (H2O2), superoxide anions (O2˙), hydroxyl radicals (OH˙), or singlet molecular oxygen) by the adsorption of O2 on the defect sites and edges of the GM nanosheets.182 In this way, the density of functional oxygen groups and defects on the surface of the GM nanosheets contribute to the high generation of ROS and explain the excellent antimicrobial activity of GO.176,183–185

The last, and most acceptable, mechanism for the antimicrobial activity of GMs is related to wrapping or trapping effects in the bacterial membranes. GM nanosheets can entrap the bacteria or microorganisms and isolate them from their surroundings, making them incapable to proliferate due to gas exchange and access to nutrients, leading to bacterial growth inactivation or bacterial death.183,186

Other graphene-like nanomaterials also possess enormous potential in antibacterial applications, displaying antimicrobial mechanisms similar to that of GMs.47,174,187,188 The emerging class of 2D MXenes have also attracted attention for their intrinsic antibacterial properties. Rasool et al.189 reported the antibacterial properties of micrometer-thick titanium carbide (Ti3C2Tx) MXene membranes against Escherichia coli (E. coli) and Bacillus subtilis (B. ubtilis) bacteria. Ti3C2Tx MXene membranes were prepared by vacuum filtration of a colloidal solution of single- and few layers of Ti3C2Tx (Fig. 6b(i–ii)). The antibacterial rate of fresh Ti3C2Tx MXene membranes reached more than 73% against B. subtilis and 67% against E. coli as compared with that of the control PVDF, while the aged Ti3C2Tx membrane (after 30 days storage) showed over 99% growth inhibition of both bacteria under the same conditions (Fig. 6b(iii)). The authors attributed the antimicrobial effectiveness of the Ti3C2Tx MXene membranes to the sharp edges of the nanosheets, which caused physical damage and disruption of the bacteria cellular membranes, inducing oxidative stress that can be generated by the anatase TiO2 nanocrystals (produced from the natural oxidation of the Ti3C2Tx in air). Moreover, the negatively charged and hydrophilic surface of the Ti3C2Tx nanosheets may have also facilitated the inactivation of the bacteria by direct contact interaction with its surface.

MoS2 nanosheets have also been explored for antimicrobial applications based on the oxidative stress and the nanoknife mechanism.174,190,191 The conductivity of the MoS2 nanosheets also plays an important role in their antimicrobial properties. Due to the higher electrical conductivity of the metallic phase, 1T MoS2 has been shown to present with higher antimicrobial activity than that of the semiconducting 2H MoS2. The higher conductivities can provide lower electrical resistance for electron transfer from bacterial intracellular components to the external environment, promoting the oxidative stress of the bacteria.192 Another important factor for the antimicrobial activity of the MoS2 is the shape of the nanomaterial. Recently, Xu et al.191 evaluated this parameter by comparing MoS2 nanosheets and nanoflowers against S. aureus and E. coli (Fig. 6c(i–ii)). For this they obtained MoS2 nanosheets and nanoflowers from the galvanostatic electrolysis in a Mo electrode, by tuning the current in the system. The MoS2-nanoflowers showed relatively improved antibacterial performance in relation to the MoS2 nanosheets. The higher surface area of the MoS2-nanoflowers was attributed to cause more oxidation stress to bacteria upon contact than the nanosheets (Fig. 6c(i–ii)).

3.2.2 Antifouling. The formation of biofilms by microorganisms around implantable medical devices still represents a challenge for the biomedical community. Surfaces that are in direct contact with biological fluids, such as a catheter and urinary probe, are an ideal environment for bacteria to adhere and proliferate, leading to infection in the patients.193 Similarly, the surfaces of membranes for nanofiltration processes also suffer from the formation of biofilms, which reduces their performance and deactivates their surface. The best strategy to combat this is based on the use of biomaterials on the surface of these biomedical implantable devices and membranes that can repel the microbes or kill them in the surrounding areas.193,194 In this scenario the use of 2D materials as a coating, composites, or a membrane among others emerges as an interesting approach for antifouling application, due their unique surface properties.

In particular, 2D materials with high surface hydrophilicity and negative charge stand out. By controlling biofouling via an anti-adhesion mode, unfavorable conditions for natural organic matter (NOM) and some bacteria are created and hinder their growth onto the surface. In addition, the surface roughness of 2D materials also plays an important role in the antifouling properties, where several authors have shown that the surface roughness increases the adhesion forces resulting in larger bacterial attachment to rougher surfaces.195,196 In this case, MoS2 presents special features such as extremely low friction and low surface roughness and, along with GO, they have been explored for this purpose.43,80 Alam et al.43 performed a comparative study on the antifouling properties of MoS2 and GO. Both materials present a highly negative zeta potential in deionized water, −41.33 ± 0.5 mV and −40.34 ± 0.76 mV for GO and MoS2 respectively. However, the contact angle measurements of GO and MoS2 were 25 ± 5.4 and 42 ± 4.6, respectively, suggesting that GO was slightly more hydrophilic than MoS2. But, on the other hand, MoS2 exhibited slightly better antifouling properties than GO. In most cases, the deposition of NOM and E. coli (which are Gram-negative bacteria and are strongly negatively charged) was significantly lower on MoS2 than GO due to the presence of functional groups on GO, which bound more easily with the foulants, and the low roughness of the MoS2 surface.

Another interesting approach to further improve the antifouling properties of 2D materials is the preparation of nanocomposites and hybrid nanomaterials with metal and oxide nanoparticles and polymers, among others, that exhibit antibacterial properties.197,198 Graphene and GO have been explored in the development of nanocomposites with improved antifouling properties and the recent work of Muthuchamy et al.51 showed impressive anti-biofilm formation activities of a graphene/chitosan nanocomposite against biofilm producing P. aeruginosa and K. pneumoniae. The formation of biofilm by Pseudomonas aeruginosa and Klebsiella pneumoniae was inhibited at 94 and 92%, respectively, by the use of only 40 μg mL−1 of the graphene/chitosan (GR/CS) nanocomposite in PBS. The effectiveness of the GR/CS nanocomposite in hindering the biofilm formation was attributed to causing disruption in the biofilm aggregation via membrane damage and distorting the cellular morphology.

3.2.3 Tissue engineering. Bodily tissues can be easily damaged by physical trauma, infection, or tumors. Many efforts have been dedicated to treat and repair various tissues, mainly in bone and dental tissue regeneration. In this scenario, the integration of 2D materials in the tissue engineering approach appears as an advantageous alternative.199 Besides the outstanding physical and chemical properties of 2D materials, these materials possess also excellent biocompatibility, biodegradability, surface functionality, high mechanical resistance and plasticity, which make these materials suitable for applications in tissue engineering as coatings, nanocomposites, among many others.200 Specifically, the surface properties of 2D materials play an important role in tissue engineering, mainly due the interaction between the 2D material and the tissues, that is an interfacial phenomenon. The unique large surface area and surface chemical properties of 2D materials are strongly related to their biocompatibility, which is the key parameter to consider if a material is a biomaterial. The excellent mechanical strength and low cellular toxicity of 2D materials improve much more the biocompatibility of scaffolds and promote osteogenic differentiation, and are beneficial for bone tissue engineering.201 Besides that, the antimicrobial and antifouling properties of several 2D materials, as previously discussed, are very interesting for applications in wound repair202 and in medical implants, helping in the prevention of bacterial biofilm formation on the implantable medical devices.

The successful use of 2D materials as a coating for implantable biomedical devices is also related to the surface topography of these materials and plays a crucial role in the regulation of the cellular behavior.200 In this scenario, graphene and its derivatives like GO and rGO stand out as these materials have distinctive topographical characteristics, such as wrinkles, ripples etc., that can increase the surface roughness of the substrates.199,200,203 The rough surface of graphene and its derivatives provides anchorage sites for cells that allows the cells to easily adhere to the substrates. Moreover, the oxygen functional groups of GO (carboxyl, hydroxyl and epoxide groups) are able to adsorb serum protein in culture medium, by attaching to molecules or surfaces, and promote cellular differentiation and growth.204 This is evidenced in the use of a substrate recovered with GO film to promote the differentiation of dental pulp stem cells (DPSCs).205 Besides that, the negatively charged GO surface can promote electrostatic interactions with the positively charged calcium phosphate (due to the calcium moieties), enabling the development of nanocomposites based on GO and calcium phosphate and inducing the osteogenesis process in bone regeneration applications.206,207

One recent example of the development of a nanocomposite based on GO for bone regeneration is the work performed by Li and collaborators.208 The authors developed a bioactive three-dimensional GO foam (GF)/polydimethylsiloxane (PDMS)/zinc silicate (ZN) scaffold with enhanced osteoinductivity properties for bone regeneration. The nanocomposite was synthesized via dip coating and hydrothermal synthesis processes, resulting in an interconnected macroporous structure (Fig. 7(a)). The authors combined the properties of all the materials, such as (i) the 3D structures of the GO foam, to improve the proliferation of mouse bone marrow mesenchymal stem cells (mBMSCs) and play an active role in osteogenic differentiation in bone tissue engineering; (ii) the flexible stiffness and biocompatibility of the PDMS that can increase the mechanical properties of the GF scaffold without changing its good cell compatibility and (iii) the zinc silicate particles, to provide zinc and silicon ions to the GF scaffold to improve the ability of stem cells to survive and differentiate into bones and to achieve scaffolds exhibiting a porous characteristic with organic–inorganic components similar to natural bone tissue. The nanocomposite scaffold displayed excellent biocompatibility and the ability to induce mBMSC proliferation and preferential osteogenic differentiation. The in vivo analysis of critical bone defects in rabbits demonstrated superior bone formation in defect sites in the GF/PDMS/ZS scaffold group at 12 weeks of post implantation without any significant inflammatory response (Fig. 7a(i–xii)).


image file: d0nr05287f-f7.tif
Fig. 7 The application of 2D materials for bone tissue engineering. (a) Schematic illustration of the synthesis of a nanocomposite based on three-dimensional GO foam (GF)/polydimethylsiloxane (PDMS)/zinc silicate (ZN) scaffolds and their potential application in osteoblast differentiation. A 6 mm × 10 mm rabbit bone defect in vivo and the gross anatomy of the (i) blank group at 12 week post-surgery and (ii–iv) GF/PDMS/ZS composite scaffold group at 4, 8, and 12 weeks after surgery, respectively. A 3D CT reconstruction model diagram of the (x) blank group at 12 weeks after surgery and (vi–viii) GF/PDMS/ZS composite scaffold group at 4, 8, and 12 weeks after surgery, respectively. The sagittal plane anatomy of the (ix) blank group at 12 weeks after surgery and (x–xii) GF/PDMS/ZS composite scaffold group at 4, 8, and 12 weeks after surgery, respectively (adapted with permission from ref. 208. Copyright 2019 American Chemical Society). (b) Schematic illustration of the preparation of the black phosphorus nanosheet based 3D hydrogel platform via photopolymerization of gelatin methacrylamide (GelMA) and cationic arginine-based unsaturated poly(ester amide)s [U-Arg-PEAs], for effective bone regeneration (reproduced with permission from ref. 212). Copyright 2019 American Chemical Society).

Another 2D material that has been attracting attention in bone tissue engineering is BP.209,210 Besides having all the unique properties of 2D materials, BP has a special feature, which is related to its chemical composition – the phosphorus atoms. As previously mentioned in this review, BP has poor chemical stability in the environments with oxygen and water and rapidly degrades to oxygenated phosphorus (POx), releasing phosphate ions. However, the phosphate ions are a major constituent of bone minerals and play an important role in bone regeneration.211 Based on that, Huang et al.212 proposed to develop a 3D hydrogel based on BP nanosheets (BPNs) to consistently and mildly provide phosphorus ions to accelerate bone regeneration without introducing foreign calcium. The 3D hydrogel was fabricated by photo-crosslinking of gelatin methacrylamide, BPNs, and cationic arginine-based unsaturated poly(ester amide)s. The incorporation of BPNs in the 3D hydrogel scaffolds improved the mechanical performance of the hydrogels and promoted the capture of the calcium ions to accelerate the biomineralization process in defected bone (Fig. 7(b)).

Besides graphene, and BP many other 2D materials, and nanocomposites based on these materials have been explored in tissue engineering, where their surface properties confer these materials outstanding performance when incorporated into scaffolds, as can be seen in Table 2.

3.2.4 Drug delivery. Drug delivery systems represent one of the best strategies to perform target drug transportation and decrease side effects in patients. As the thinnest materials, 2D materials have the highest specific surface areas among all known materials, and can act as large reservoirs and anchoring sites to efficiently load and deliver therapeutic agents.129,213 Moreover, it is possible to take advantage of the outstanding physicochemical, optical, and electronic properties of 2D materials to combine drug delivery systems with cellular imaging, chemotherapy, photothermal (PPT) and photodynamic (PDT) therapies to develop smart drug delivery systems.214 In these applications, the surface properties of 2D materials play an important role in efficient drug loading. GMs – graphene, GO and rGO – were the first 2D materials explored as carriers in drug delivery systems215–217 by harnessing the surface properties. The surface of graphene is abundant in delocalized surface π electrons that can be used for effective drug loading of poorly soluble drugs (the most common drugs used in cancer therapies) via hydrophobic interactions and π–π stacking.216,218 Additionally, the large surface area of graphene allows the high density functionalization of its surface via both covalent and non-covalent approaches, improving the drug loading.219 However, GO is more widely used than graphene for drug delivery applications due to the presence of carboxylic, epoxy and hydroxide groups, which allow for a wide range of reactions and functionalization opportunities. Furthermore, the surface of GO displays a coexistence of hydrophobic and hydrophilic properties, due to the sp2 and sp3 hybridized carbon domains in its structure, which enables this material to possess good water dispersity and biocompatibility, but also a high affinity for some drug molecules that are immiscible in aqueous media. However, in contrast to GO, graphene has more sp2 hybridized carbon domains exhibiting a higher absorbance in the near-infrared region (NIR), which is favorable for the PPT and PDT applications.220

A particular function of drug delivery systems is to perform the release of a sequence of drugs with defined kinetics and molar ratios to enhance the therapeutic effects while minimizing the dose to patients.221 Recently, Schneible et al. achieved this concept by developing a nanocomposite based on GO nanosheets embedded in a Max8 peptide hydrogel, which provides controlled kinetics and molar ratios of release of doxorubicin (DOX) and gemcitabine (GEM).221 With this nanocomposite, the authors demonstrated a high DOX loading on GO and sustained release with pH (18.9% over 72 h and 31.4% over 4 weeks) and a Max8 hydrogel with a capability to release GEM with faster kinetics and with a 10-fold molar ratio to DOX. The nanocomposite based on the DOX/GO@GEM/Max8 hydrogel matrix was tested against a triple negative breast cancer cell line, MDA-MB-231, and achieved a combination index of 0.093 ± 0.001; indicating a much stronger synergistic effect compared to the DOX–GEM combination as free drugs co-administered in solution (CI = 0.396 ± 0.034). This combination index value obtained by the DOX/GO@GEM/Max8 hydrogel nanocomposite was the lowest reported in the literature for this and similar drugs.

As a member of the TMD family, MoS2 shows very interesting application in drug delivery systems combined with PPT and PDT. This is due to the fact that a monolayer of MoS2 has 7.8 times higher NIR absorbance than GO. In addition, the surface chemistry of MoS2 is rich for functionalization, since MoS2 has unsaturated d-orbitals, chemically active edge defects and sulfur vacancies, which act as sites for introducing functional groups and ligands.222 However MoS2 demonstrated low serum stability and inefficient intracellular delivery.223,224 A nice strategy to mitigate these issues, improve the biocompatibility and decrease even more the cytotoxicity is to perform the functionalization of the surface of Mos2 with biocompatible materials and/or biomolecules. This was clearly demonstrated recently by Xie M. et al.225 The authors showed the modification of the MoS2 surface with egg yolk phospholipids (MoS2-lipid) to enhance the stability of the MoS2 nanosheets under physiological conditions and to act as a nanocarrier system for the treatment of tumors via the combination of chemotherapy and photothermal therapy. The MoS2-lipid demonstrated a loading rate of DOX of 104.4%, and a release mediated by pH and NIR light. The non-covalent functionalization of the MoS2 surface with lipids by coating represents an easy strategy to improve the stability of MoS2 nanosheets, but also enhanced the biocompatibility and the accumulation of the nanocarrier in mouse tumors in vivo.

Another 2D material that has been drawing attention as an ideal candidate for drug delivery is h-BN, which possesses many beneficial properties including surface chemical inertness, hierarchical surface porosity, high specific surface area, low toxicity, and high thermal conductivity.129 Fu, Z. et al.,226 took advantage of the unique properties of h-BN to develop a multifunctional nanoplatform, co-carrying DOX and the heat shock protein inhibitor 17AAG, which can kill cancer cells and inhibit tumor growth at relatively low temperatures. The high surface area of h-BN allowed high density functionalization with the cRGD peptide to target the αvβ3 integrin, which is over-expressed in the cells of tumors. The h-BN nanoplatform exhibited a high loading capacity for DOX (603 mg g−1) with a drug release mediated by pH and NIR light. The presence of 17AAG and the high thermal conductivity of the h-BN nanosheets allowed for low temperature PTT to be combined with chemotherapy with DOX, resulting in highly effective anti-cancer activity of the multifunctional platform based on h-BN nanosheets.

Based on the combination of drug delivery and the PPT–PDT process, many other 2D materials have been exploited for this purpose, mainly that have strong light absorption in the NIR region, such as MXenes227 and BP172,228 as can be seen in Table 2.

3.3 Biocompatibility and biodegradability

The biocompatibility and biodegradability of 2D materials are essential for their integration and use in biomedical applications, such as implantable devices, tissue engineering, and drug delivery systems, among others. The biocompatibility of 2D materials is not only dependent on the surface properties of these materials, such as the functionalization degree and reactive surface, but also the concentration, purity, size, shape, thickness and form of 2D materials.229–231 For example, a study performed by Mateti et al.232 showed that micrometer-sized h-BN nanosheets possess in vitro biocompatibility against Osteoblast-like cells; however, nanosheets with a lateral size less than 1 μm and a thickness below 100 nm were less biocompatible. It was suggested that this observation may be due to the unsaturated B atoms located at the nanosheet edges or on the surface of the material (in the case of defects) are present in a radical state, triggering faster reactivity kinetics with other active atoms, such as oxygen, to generate ROS and leading to cell death. In this case, the larger lateral sized nanosheets of h-BN possess more exposed edges with unsaturated B atoms, and, thus, would decrease the biocompatibility of this 2D material.

In the case of GMs, graphene and its derivatives obtained by different methods, such as mechanical exfoliation, CVD or solution process (liquid and chemical exfoliation), can all exhibit different biocompatibility properties. Nanoflakes of chemically exfoliated graphene, micrometer sized flakes of GO, or substrate bound CVD graphene will have dramatically different interactions and effects (if any) on live cells and tissue that can result in contradicting conclusions.233 For example, a study performed by Park et al.234 showed that graphene obtained by CVD on copper foil was an ideal substrate to promote the cardiomyogenic differentiation process of mesenchymal stem cells. Moreover, it was also found that the grown graphene did not exhibit any sign of cytotoxicity for the stem cell cultures, indicating that this method for obtaining graphene could be an approach towards the development of implantable biosensors based on CVD graphene.

The functionalization of the surface of 2D materials is a great strategy to improve the biocompatibility of these materials.230,235 In this sense, GO poses as an ideal candidate due to its intrinsic oxygen functional groups at the surface. Jasim et al.236 demonstrated that the intravenous injection of large amounts of GO nanosheets into mice resulted in an extensive urinary excretion, indicating a rapid transit across the glomerular filtration barrier (GFB), without causing any kidney (or other tissue) damage. Similarly, it has been reported that the functionalization of the MoS2 surface with lipoic acid and poly(ethylene glycol) (PEG) improved significantly its biocompatibility and physiological stability.237

The mechanisms and material parameters that are responsible for the biocompatibility of 2D materials, and the potential of the materials to induce any type of damage in the tissues still warrant thorough investigation. This is the only way to ensure the safe use of 2D materials in biomedical applications. In this context, we can highlight government initiatives such as the GRAPHENE Flagship project,238 funded by the European Union that has a work package (Health and Environment) to study the safety and potential risks to the health of animals, humans and the environment of the graphene and other 2D materials. These initiatives help to improve and seek new knowledge regarding the nanosafety of 2D materials, contributing to the future commercial implementation of these materials in biomedical applications.

The biodegradability of 2D materials is another important parameter that needs to be very well investigated before its integration in biomedical applications. In particular, the biodegradaility has to be considered for some biomedical applications which may require long-term integration within the biological milieu,233 such as orthopedic or neuronal implants, catheters, wound healing agents, implantable biosensors and corneal devices. Moreover, for biomedical applications such as drug delivery systems, the ability of 2D materials to biodegrade is very important and can be influenced by many factors, inlcuding the type of material, the degree of chemical functionalization, the aqueous dispersity and the redox potentials of the different oxidative environments. Thus, it is of utmost importance to consider all of these parameters when examining the biodegradability of 2D materials, and to find stratergies to enable, or promote, this aspect for commercial biotechnologies.235 Recently, Bianco et al.235 performed an elegant roadmap study examining the main parameters into the biodegradation of 2D materials. The surface defects, functional groups and chemical functionalization all played an important role in the promotion of the biodegradability. Furthermore, the authors introduced the concept of “degradation-by-design” which represents a great approach to improve the biodegradability of 2D materials by the covalent modification of the material surface with appropriate molecules.

4. Future outlook and conclusions

From the early stages of discovery to recent advancements in synthesis and surface engineering, there is no denying that tremendous progress and achievements have been made in the field of 2D materials. With such a diverse range of properties, and endless possibilities to ‘mix and match’, 2D materials have benefited many areas of research and technology. In particular, 2D materials have great potential for bio-applications that can have great impacts on healthcare and society.

Owing to their outstanding properties that arise from their dimensionality and surface interactions, 2D materials have levitated many intrinsic limitations of biomolecular and chemical sensing, such as low signals, slow bio-reaction times or events, and instability, and have enabled the realization of many platforms and devices with high sensitivity and selectivity. Surface engineering and functionalization techniques to modify and tune the electronic and optical properties have become a common approach to expand the family of 2D materials and to compensate for various drawbacks. Moreover, due to the success of 2D materials, there are continuous efforts in finding newer and novel 2D materials with potentially superior properties or more facile synthetic routes.

With this in mind, there are still several challenges and limitations that need to be addressed. Whilst 2D materials have been a trending topic for the past two decades, the commercial availability of healthcare devices and technologies based on 2D materials is currently lacking. The key reason that hinders their market presence stems from large-scale production and standardization issues. As the properties of 2D materials are defined by their physical and atomic structures, it is essential that mass production of the materials have high uniformity (control on the number of layers, lateral size and defects of the nanosheets) such that there is no, or low, device-to-device variability. This is also particularly true for applications that require surface functionalization, where the amount/concentration of bioreceptors should be consistent in each sensor or device.

In addition, to have a competitive and economical edge, the synthesis methods should be low cost, yet with a high degree of controllability. The issue of low cost mass production is also another factor that hinders the commercial availability of 2D material-based biotechnologies. For platforms and devices that require pristine and uniform surfaces, like FETs, growth methods, such as chemical vapor deposition (CVD), are costly approaches to obtain high quality, yet low-yielding, 2D materials. To meet several growth parameters, such as high temperatures and pressures, expensive and specific instruments and facilities are typically required alongside the costs associated with hiring and training specialized personnel. On the other hand, solution based methods, such as ultrasonication assisted exfoliation, may be a cost effective and high-yielding approach. However, this represents only a reality for graphene and its derivatives, where some companies on the market are able to control the homogeneity of graphene and its derivatives from bath to batch. The mass production of 2D nanomaterials beyond graphene, such as TMDs and h-BN, still pose a challenge. Besides that, the implementation of 2D materials in biomedical applications, such as tissue engineering and drug delivery systems, requires a strict quality control of the 2D nanosheets obtained by solution based methods. The use of rigorous protocols that aim to purify and remove the remaining impurities from the liquid chemical exfoliation process, such as acids, bases, and metallic ions, among others, from the resulting 2D dispersion needs to be performed. The presence of chemical impurities, as well as the type of solvent and the pH value of the dispersion, can greatly affect the performance of 2D materials in biomedical applications and even more affect their cytotoxicity. Whilst these drawbacks may be overlooked in research settings, translation of these processes to commercial products and mass production must be addressed.

Another issue, mainly related to in vivo and biomedical uses, is the stability and compatibility in biological environments for extended periods of time. Factors such as device or material degradation, due to exposure to complex biological media, toxicity, and prolonged use and its effects should be systematically evaluated prior to their use in everyday life.

In conclusion, while there are still several challenges and limitations to be faced, it is evident that the field of 2D materials has made tremendous progress and has had great impacts for biosensors and biomedical devices. In this review we highlight the importance of the surface and dimensionality of 2D materials and how it has influenced the design and development of many biotechnologies. We showed that the understanding of surface properties (high surface area, surface roughness, chemical functionalities of the surface, surface charge, confinement of charge carriers, biocompatibility and among others), the dimensionality and shape of 2D materials’ nanosheets is the key point to better explore the potential of these materials in the successful development of biotechnologies such as in biosensors, implants, tissue engineering, membranes and surfaces with antimicrobial and antifouling properties, among others. Thanks to the unique surface properties of 2D materials it has been possible to develop biosensors with outstanding characteristics, never achieved before using materials at the bulk scale. Biosensors with impressive low limits of detection (fM, aM and even zM), miniaturized, integrated into the user's skin, stable and with different functionalities have been developed taking advantage of the 2D materials’ surface properties. The constant strive of many researchers, both inside and outside of academia, has made us better understand the properties and mechanisms of 2D materials that enable the creation of novel strategies and engineering methods to push for the realization of advanced and future biotechnologies.

Conflicts of interest

There are no conflicts of interest to declare.

Acknowledgements

We acknowledge the financial support from the EU Graphene Flagship Core 3 Project (No. 881603), from the Spanish MINECO under project MAT2017-87202-P. ICN2 is supported by the Severo Ochoa program from Spanish MINECO (grant no. SEV-2013-0295) and by the CERCA Programme/Generalitat de Catalunya. E. P. N. acknowledges funding through the EU's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 754510. C. C. C. S acknowledges funding through CAPES – PRINT (Programa Institucional de Internacionalização; grant # 88887.310281/2018-00 and 88887.467442/2019-00).

References

  1. K. S. Novoselov, Science, 2004, 306, 666–669 CrossRef CAS.
  2. C. W. Lee, J. M. Suh and H. W. Jang, Front. Chem., 2019, 7, 708 CrossRef CAS.
  3. A. Bolotsky, D. Butler, C. Dong, K. Gerace, N. R. Glavin, C. Muratore, J. A. Robinson and A. Ebrahimi, ACS Nano, 2019, 13, 9781–9810 CrossRef CAS.
  4. S. Balendhran, S. Walia, M. Alsaif, E. P. Nguyen, J. Z. Ou, S. Zhuiykov, S. Sriram, M. Bhaskaran and K. Kalantar-Zadeh, ACS Nano, 2013, 7, 9753–9760 CrossRef CAS.
  5. R. Kurapati, K. Kostarelos, M. Prato and A. Bianco, Adv. Mater., 2016, 28, 6052–6074 CrossRef CAS.
  6. M. Chhowalla, H. S. Shin, G. Eda, L. J. Li, K. P. Loh and H. Zhang, Nat. Chem., 2013, 5, 263–275 CrossRef.
  7. J. H. Kim and M. Benelmekki, in Frontiers of Nanoscience, 2019, vol. 14, pp. 103–120 Search PubMed.
  8. N. Ashraf, M. Isa khan, A. Majid, M. Rafique and M. B. Tahir, Chin. J. Phys., 2020, 66, 246–257 CrossRef CAS.
  9. S. Z. Butler, S. M. Hollen, L. Cao, Y. Cui, J. A. Gupta, H. R. Gutiérrez, T. F. Heinz, S. S. Hong, J. Huang, A. F. Ismach, E. Johnston-Halperin, M. Kuno, V. V. Plashnitsa, R. D. Robinson, R. S. Ruoff, S. Salahuddin, J. Shan, L. Shi, M. G. Spencer, M. Terrones, W. Windl and J. E. Goldberger, ACS Nano, 2013, 7, 2898–2926 CrossRef CAS.
  10. X. Gan, H. Zhao, R. Schirhagl and X. Quan, Microchim. Acta, 2018, 185, 478 CrossRef.
  11. R. Boroujerdi, A. Abdelkader and R. Paul, Nano-Micro Lett., 2020, 12, 33 CrossRef.
  12. Y. H. Wang, L. L. He, K. J. Huang, Y. X. Chen, S. Y. Wang, Z. H. Liu and D. Li, Analyst, 2019, 144, 2849–2866 RSC.
  13. Y. M. Lei, M. M. Xiao, Y. T. Li, L. Xu, H. Zhang, Z. Y. Zhang and G. J. Zhang, Biosens. Bioelectron., 2017, 91, 1–7 CrossRef CAS.
  14. N. Parvin, Q. Jin, Y. Wei, R. Yu, B. Zheng, L. Huang, Y. Zhang, L. Wang, H. Zhang, M. Gao, H. Zhao, W. Hu, Y. Li and D. Wang, Adv. Mater., 2017, 29, 1606755 CrossRef.
  15. H. H. Xu, H. H. Deng, X. Q. Lin, Y. Y. Wu, X. L. Lin, H. P. Peng, A. L. Liu, X. H. Xia and W. Chen, Microchim. Acta, 2017, 184, 3945–3951 CrossRef CAS.
  16. Q. Zhou, Y. Lin, J. Shu, K. Zhang, Z. Yu and D. Tang, Biosens. Bioelectron., 2017, 98, 15–21 CrossRef CAS.
  17. N. Chauhan, S. Chawla, C. S. Pundir and U. Jain, Biosens. Bioelectron., 2017, 89, 377–383 CrossRef CAS.
  18. M. Ma, T. Zhe, Y. Ma, Z. Wang, Q. Chen and J. Wang, Talanta, 2018, 180, 133–143 CrossRef CAS.
  19. X. Li, Y. Li, Q. Qiu, Q. Wen, Q. Zhang, W. Yang, L. Yuwen, L. Weng and L. Wang, J. Colloid Interface Sci., 2019, 543, 96–105 CrossRef CAS.
  20. N. F. Chiu and T. L. Lin, Talanta, 2018, 185, 174–181 CrossRef CAS.
  21. D. Jiang, X. Du, L. Zhou, H. Li and K. Wang, Anal. Chem., 2017, 89, 4525–4531 CrossRef CAS.
  22. S. Mao, J. Chang, H. Pu, G. Lu, Q. He, H. Zhang and J. Chen, Chem. Soc. Rev., 2017, 46, 6872–6904 RSC.
  23. W. Nie, Q. Wang, X. Yang, H. Zhang, Z. Li, L. Gao, Y. Zheng, X. Liu and K. Wang, Anal. Chim. Acta, 2017, 993, 55–62 CrossRef CAS.
  24. H. Park, G. Han, S. W. Lee, H. Lee, S. H. Jeong, M. Naqi, A. AlMutairi, Y. J. Kim, J. Lee, W. Kim, S. Kim, Y. Yoon and G. Yoo, ACS Appl. Mater. Interfaces, 2017, 9, 43490–43497 CrossRef CAS.
  25. S. Su, W. Cao, W. Liu, Z. Lu, D. Zhu, J. Chao, L. Weng, L. Wang, C. Fan and L. Wang, Biosens. Bioelectron., 2017, 94, 552–559 CrossRef CAS.
  26. D. Zhu, W. Liu, D. Zhao, Q. Hao, J. Li, J. Huang, J. Shi, J. Chao, S. Su and L. Wang, ACS Appl. Mater. Interfaces, 2017, 9, 35597–35603 CrossRef CAS.
  27. Y. Guo, Y. Shu, A. Li, B. Li, J. Pi, J. Cai, H. Cai and Q. Gao, J. Mater. Chem. B, 2017, 5, 5532–5538 RSC.
  28. M. Shorie, V. Kumar, H. Kaur, K. Singh, V. K. Tomer and P. Sabherwal, Microchim. Acta, 2018, 185, 158 CrossRef.
  29. Y. Ju, X. Hu, Y. Zang, R. Cao and H. Xue, Anal. Methods, 2019, 11, 2163–2169 RSC.
  30. Y. Tan, M. Li, X. Ye, Z. Wang, Y. Wang and C. Li, Sens. Actuators, B, 2018, 262, 982–990 CrossRef CAS.
  31. Y. Niu, R. Zou, H. A. Yones, X. Li, X. Li, X. Niu, Y. Chen, P. Li and W. Sun, J. Chin. Chem. Soc., 2018, 65, 1127–1135 CrossRef CAS.
  32. G. Hong, R. Chen, L. Xu, X. Lu, Z. Yang, G. Zhou, L. Li, W. Chen and H. Peng, Anal. Chim. Acta, 2020, 1099, 52–59 CrossRef CAS.
  33. X. Li, X. Niu, W. Zhao, W. Chen, C. Yin, Y. Men, G. Li and W. Sun, Electrochem. Commun., 2018, 86, 68–71 CrossRef CAS.
  34. Y. Chen, R. Ren, H. Pu, J. Chang, S. Mao and J. Chen, Biosens. Bioelectron., 2017, 89, 505–510 CrossRef CAS.
  35. J. Liu, L. Meng, Z. Fei, P. J. Dyson, X. Jing and X. Liu, Biosens. Bioelectron., 2017, 90, 69–74 CrossRef CAS.
  36. J. Ji, J. Wen, Y. Shen, Y. Lv, Y. Chen, S. Liu, H. Ma and Y. Zhang, J. Am. Chem. Soc., 2017, 139, 11698–11701 CrossRef CAS.
  37. S. Kumar, Y. Lei, N. H. Alshareef, M. A. Quevedo-Lopez and K. N. Salama, Biosens. Bioelectron., 2018, 121, 243–249 CrossRef CAS.
  38. P.-P. Li, X.-P. Liu, C.-J. Mao, B.-K. Jin and J.-J. Zhu, Anal. Chim. Acta, 2019, 1048, 42–49 CrossRef CAS.
  39. J.-M. Jeong, M. Yang, D. S. Kim, T. J. Lee, B. G. Choi and D. H. Kim, J. Colloid Interface Sci., 2017, 506, 379–385 CrossRef CAS.
  40. T. Yang, M. Chen, Q. Kong, X. Luo and K. Jiao, Biosens. Bioelectron., 2017, 89, 538–544 CrossRef CAS.
  41. R. Kumari, F. Opoku, A. O. Osikoya, W. W. Anku, S. K. Shukla and P. P. Govender, Mater. Chem. Phys., 2019, 226, 129–140 CrossRef CAS.
  42. S. Augustine, P. Kumar and B. D. Malhotra, ACS Appl. Bio Mater., 2019, 2, 5366–5378 CrossRef CAS.
  43. I. Alam, L. M. Guiney, M. C. Hersam and I. Chowdhury, Environ. Sci.: Nano, 2018, 5, 1628–1639 RSC.
  44. T. I. Kim, J. Kim, I.-J. Park, K.-O. Cho and S.-Y. Choi, 2D Mater., 2019, 6, 025025 CrossRef CAS.
  45. P. Cheng, Y. Chen, X. Yan, Y. Wang and W. Z. Lang, ChemSusChem, 2019, 12, 275–282 CrossRef CAS.
  46. Z. Xiong, X. Zhang, S. Zhang, L. Lei, W. Ma, D. Li, W. Wang, Q. Zhao and B. Xing, Ecotoxicol. Environ. Saf., 2018, 161, 507–514 CrossRef CAS.
  47. Z. Sun, Y. Zhang, H. Yu, C. Yan, Y. Liu, S. Hong, H. Tao, A. W. Robertson, Z. Wang and A. A. H. Pádua, Nanoscale, 2018, 10, 12543–12553 RSC.
  48. N. Yadav, A. Dubey, S. Shukla, C. P. Saini, G. Gupta, R. Priyadarshini and B. Lochab, ACS Omega, 2017, 2, 3070–3082 CrossRef CAS.
  49. M. P. Romero, V. S. Marangoni, C. G. de Faria, I. S. Leite, C. de C. C. e. Silva, C. M. Maroneze, M. A. Pereira-da-Silva, V. S. Bagnato and N. M. Inada, Front. Microbiol., 2020, 10, 2995 CrossRef.
  50. D. Prema, J. Prakash, S. Vignesh, P. Veluchamy, C. Ramachandran, D. B. Samal, D. H. Oh, S. Sahabudeen and G. Devanand Venkatasubbu, Appl. Nanosci., 2019, 10, 827–849 CrossRef.
  51. M. Muthuchamy, R. Govindan, K. Shine, V. Thangasamy, N. S. Alharbi, M. Thillaichidambaram, J. M. Khaled, J.-L. Wen and K. F. Alanzi, Carbohydr. Polym., 2020, 230, 115646 CrossRef CAS.
  52. G. Choe, S. Oh, J. M. Seok, S. A. Park and J. Y. Lee, Nanoscale, 2019, 11, 23275–23285 RSC.
  53. L. Wang, M. Fang, Y. Xia, J. Hou, X. Nan, B. Zhao and X. Wang, RSC Adv., 2020, 10, 10118–10128 RSC.
  54. X. Liu, A. L. Miller, S. Park, M. N. George, B. E. Waletzki, H. Xu, A. Terzic and L. Lu, ACS Appl. Mater. Interfaces, 2019, 11, 23558–23572 CrossRef CAS.
  55. K. Chen, Y. Chen, Q. Deng, S. H. Jeong, T. S. Jang, S. Du, H. E. Kim, Q. Huang and C. M. Han, Mater. Lett., 2018, 229, 114–117 CrossRef CAS.
  56. S. Nagarajan, H. Belaid, C. Pochat-Bohatier, C. Teyssier, I. Iatsunskyi, E. Coy, S. Balme, D. Cornu, P. Miele, N. S. Kalkura, V. Cavaillès and M. Bechelany, ACS Appl. Mater. Interfaces, 2017, 9, 33695–33706 CrossRef CAS.
  57. B. Farshid, G. Lalwani, M. Shir Mohammadi, J. Simonsen and B. Sitharaman, J. Biomed. Mater. Res., Part B, 2017, 105, 406–419 CrossRef CAS.
  58. L. He, S. Sarkar, A. Barras, R. Boukherroub, S. Szunerits and D. Mandler, Chem. Commun., 2017, 53, 4022–4025 RSC.
  59. T. Yin, J. Liu, Z. Zhao, Y. Zhao, L. Dong, M. Yang, J. Zhou and M. Huo, Adv. Funct. Mater., 2017, 27, 1–12 Search PubMed.
  60. S. Han, F. Teng, Y. Wang, L. Su, Q. Leng and H. Jiang, RSC Adv., 2020, 10, 10980–10988 RSC.
  61. C. C. Cheng, A. A. Muhabie, S. Y. Huang, C. Y. Wu, B. T. Gebeyehu, A. W. Lee, J. Y. Lai and D. J. Lee, Nanoscale, 2019, 11, 10393–10401 RSC.
  62. Y. Yang, J. Wu, D. H. Bremner, S. Niu, Y. Li, X. Zhang, X. Xie and L. M. Zhu, Colloids Surf., B, 2020, 185, 110585 CrossRef CAS.
  63. G. Liu, J. Zou, Q. Tang, X. Yang, Y. Zhang, Q. Zhang, W. Huang, P. Chen, J. Shao and X. Dong, ACS Appl. Mater. Interfaces, 2017, 9, 40077–40086 CrossRef CAS.
  64. L. Jin, P. Hu, Y. Wang, L. Wu, K. Qin, H. Cheng, S. Wang, B. Pan, H. Xin, W. Zhang and X. Wang, Adv. Mater., 2020, 32, 1906050 CrossRef CAS.
  65. X. Ding, C. Hong, G. Zhang, J. Liu, H. Ouyang, M. Wang, L. Dong, W. Zhang, H. Xin and X. Wang, Nanoscale Horiz., 2019, 4, 1277–1285 RSC.
  66. J. Wang, G. Li and L. Li, in Two-dimensional Materials - Synthesis, Characterization and Potential Applications, InTech, 2016 Search PubMed.
  67. A. Zavabeti, A. Jannat, L. Zhong, A. A. Haidry, Z. Yao and J. Z. Ou, Nano-Micro Lett., 2020, 12, 66 CrossRef CAS.
  68. F. Wang, Z. Wang, Q. Wang, F. Wang, L. Yin, K. Xu, Y. Huang and J. He, Nanotechnology, 2015, 26, 292001 CrossRef.
  69. R. Podila, A. Rao, P. Puneet, S. Bhattacharya, S. S. K. Mallineni, A. Srivastava, F. Liu, J. Taha-Tijerina, L. Peña-Parás, D. Maldonado-Cortes, G. Qin, M. Hu, Y. Alaskar, S. Arafin, K. Wang, Q. Chi, M. Xue, F. Li, R. Cheung and L. Guangshe, Two-dimensional Materials- Synthesis, Characterization and Potential Applications, INTECH, 2016 Search PubMed.
  70. Q. H. Wang, K. Kalantar-Zadeh, A. Kis, J. N. Coleman and M. S. Strano, Nat. Nanotechnol., 2012, 7, 699–712 CrossRef CAS.
  71. H. Zhang, ACS Nano, 2015, 9, 9451–9469 CrossRef CAS.
  72. C. Anichini, W. Czepa, D. Pakulski, A. Aliprandi, A. Ciesielski and P. Samorì, Chem. Soc. Rev., 2018, 47, 4860–4908 RSC.
  73. P. Bazylewski, S. Van Middelkoop, R. Divigalpitiya and G. Fanchini, ACS Omega, 2020, 5, 643–649 CrossRef CAS.
  74. D. Akinwande, C. J. Brennan, J. S. Bunch, P. Egberts, J. R. Felts, H. Gao, R. Huang, J. S. Kim, T. Li, Y. Li, K. M. Liechti, N. Lu, H. S. Park, E. J. Reed, P. Wang, B. I. Yakobson, T. Zhang, Y. W. Zhang, Y. Zhou and Y. Zhu, Extreme Mech. Lett., 2017, 13, 42–77 CrossRef.
  75. R. Zhang and R. Cheung, in Two-dimensional Materials - Synthesis, Characterization and Potential Applications, InTech, 2016 Search PubMed.
  76. C. Lee, X. Wei, J. W. Kysar and J. Hone, Science, 2008, 321, 385–388 CrossRef CAS.
  77. S. P. Koenig, N. G. Boddeti, M. L. Dunn and J. S. Bunch, Nat. Nanotechnol., 2011, 6, 543–546 CrossRef CAS.
  78. X. Cao, A. Halder, Y. Tang, C. Hou, H. Wang, J. O. Duus and Q. Chi, Mater. Chem. Front., 2018, 2, 1944–1986 RSC.
  79. H. Kim and J. H. Ahn, Carbon, 2017, 120, 244–257 CrossRef CAS.
  80. S. Begum, A. Pramanik, D. Davis, S. Patibandla, K. Gates, Y. Gao and P. C. Ray, ACS Omega, 2020, 5, 3116–3130 CrossRef CAS.
  81. M. Y. Li, C. H. Chen, Y. Shi and L. J. Li, Mater. Today, 2016, 19, 322–335 CrossRef CAS.
  82. Y. Gong, S. Lei, G. Ye, B. Li, Y. He, K. Keyshar, X. Zhang, Q. Wang, J. Lou, Z. Liu, R. Vajtai, W. Zhou and P. M. Ajayan, Nano Lett., 2015, 15, 6135–6141 CrossRef CAS.
  83. I. V. Sankar, J. Jeon, S. K. Jang, J. H. Cho, E. Hwang and S. Lee, Nano, 2019, 14 Search PubMed.
  84. A. K. Geim and I. V. Grigorieva, Nature, 2013, 499, 419–425 CrossRef CAS.
  85. M. Velicky and P. Toth, Appl. Mater. Today, 2017, 8, 68–103 CrossRef.
  86. P. P. Li, X. P. Liu, C. J. Mao, B. K. Jin and J. J. Zhu, Anal. Chim. Acta, 2019, 1048, 42–49 CrossRef CAS.
  87. R. Vargas-Bernal, Sensors, 2019, 19, 1295 CrossRef CAS.
  88. M. G. Stanford, P. D. Rack and D. Jariwala, npj 2D Mater. Appl., 2018, 2, 20 CrossRef.
  89. V. K. Sangwan and M. C. Hersam, Annu. Rev. Phys. Chem., 2018, 69, 299–325 CrossRef CAS.
  90. H. Huang, R. Jiang, Y. Feng, H. Ouyang, N. Zhou, X. Zhang and Y. Wei, Nanoscale, 2020, 12, 1325–1338 RSC.
  91. L. Syedmoradi, A. Ahmadi, M. L. Norton and K. Omidfar, Microchim. Acta, 2019, 186, 739 CrossRef CAS.
  92. Y. Chen, K. Yang, B. Jiang, J. Li, M. Zeng and L. Fu, J. Mater. Chem. A, 2017, 5, 8187–8208 RSC.
  93. J. Li, Z. Wei and J. Kang, Two–Dimensional Semicond, 2020, pp. 35–53 Search PubMed.
  94. M. Xiong, Q. Rong, H.-M. Meng and X.-B. Zhang, Biosens. Bioelectron., 2017, 89, 212–223 CrossRef CAS.
  95. L. Daukiya, J. Seibel and S. De Feyter, Adv. Phys.: X, 2019, 4, 1625723 CAS.
  96. S. Trivedi, K. Lobo and H. S. S. Ramakrishna Matte, in Woodhead Publishing Series in Electronic and Optical Materials, ed. M. Hywel, C. S. Rout and D. J. Late, Woodhead Publishing, 2019, pp. 25–90 Search PubMed.
  97. S. Trivedi, K. Lobo and H. S. S. Ramakrishna Matte, in Woodhead Publishing Series in Electronic and Optical Materials, ed. M. Hywel, C. S. Rout and D. J. Late, Woodhead Publishing, 2019, pp. 25–90 Search PubMed.
  98. T. Niu, J. Zhang and W. Chen, ChemNanoMat, 2019, 5, 6–23 CrossRef CAS.
  99. J. Hong, C. Jin, J. Yuan and Z. Zhang, Adv. Mater., 2017, 29, 1606434 CrossRef.
  100. Y. Qu, F. He, C. Yu, X. Liang, D. Liang, L. Ma and Q. Zhang, Mater. Sci. Eng., C, 2018, 90, 764–780 CrossRef CAS.
  101. S. Najmaei, J. Yuan, J. Zhang, P. Ajayan and J. Lou, Acc. Chem. Res., 2015, 48, 31–40 CrossRef CAS.
  102. M. Pumera, Mater. Today, 2011, 14, 308–315 CrossRef CAS.
  103. Y. Chen, S. Huang, X. Ji, K. Adepalli, K. Yin, X. Ling, X. Wang, J. Xue, M. Dresselhaus, J. Kong and B. Yildiz, ACS Nano, 2018, 12, 2569–2579 CrossRef CAS.
  104. L. Tao, X. Duan, C. Wang, X. Duan and S. Wang, Chem. Commun., 2015, 51, 7470–7473 RSC.
  105. H. Li, C. Tsai, A. L. Koh, L. Cai, A. W. Contryman, A. H. Fragapane, J. Zhao, H. S. Han, H. C. Manoharan, F. Abild-Pedersen, J. K. Nørskov and X. Zheng, Nat. Mater., 2016, 15, 48–53 CrossRef CAS.
  106. S. Ramaraj, M. Sakthivel, S. M. Chen, B. S. Lou and K. C. Ho, ACS Appl. Mater. Interfaces, 2019, 11, 7862–7871 CrossRef CAS.
  107. X. Zhao, X. Dai, C. Xia, T. Wang and Y. Peng, Solid State Commun., 2015, 215–216, 1–4 CAS.
  108. G. Maduraiveeran, M. Sasidharan and V. Ganesan, Biosens. Bioelectron., 2018, 103, 113–129 CrossRef CAS.
  109. K. Kalantar-Zadeh and J. Z. Ou, ACS Sens., 2016, 1, 5–16 CrossRef CAS.
  110. G. Guan and M. Han, Adv. Sci., 2019, 6, 1901837 CrossRef CAS.
  111. C. Zhu, D. Du and Y. Lin, Biosens. Bioelectron., 2017, 89, 43–55 CrossRef CAS.
  112. S. Varghese, S. Varghese, S. Swaminathan, K. Singh and V. Mittal, Electronics, 2015, 4, 651–687 CrossRef CAS.
  113. F. Vulcano, A. Kovtun, C. Bettini, Z. Xia, A. Liscio, F. Terzi, A. Heras, A. Colina, B. Zanfrognini, M. Melucci, V. Palermo and C. Zanardi, 2D Mater., 2020, 7 DOI:10.1088/2053-1583/ab734f.
  114. X. S. Chu, A. Yousaf, D. O. Li, A. A. Tang, A. Debnath, D. Ma, A. A. Green, E. J. G. Santos and Q. H. Wang, Chem. Mater., 2018, 30, 2112–2128 CrossRef CAS.
  115. P. G. Moses, J. J. Mortensen, B. I. Lundqvist and J. K. Nørskov, J. Chem. Phys., 2009, 130, 104709 CrossRef.
  116. E. P. Nguyen, B. J. Carey, C. J. Harrison, P. Atkin, K. J. Berean, E. Della Gaspera, J. Z. Ou, R. B. Kaner, K. Kalantar-Zadeh and T. Daeneke, Nanoscale, 2016, 8, 16276–16283 RSC.
  117. V. Georgakilas, M. Otyepka, A. B. Bourlinos, V. Chandra, N. Kim, K. C. Kemp, P. Hobza, R. Zboril and K. S. Kim, Chem. Rev., 2012, 112, 6156–6214 CrossRef CAS.
  118. S. Kumar, S. Kaushik, R. Pratap and S. Raghavan, ACS Appl. Mater. Interfaces, 2015, 7, 2189–2194 CrossRef CAS.
  119. A. Cagliani, D. M. A. Mackenzie, L. K. Tschammer, F. Pizzocchero, K. Almdal and P. Bøggild, Nano Res., 2014, 7, 743–754 CrossRef CAS.
  120. A. Salehi-Khojin, D. Estrada, K. Y. Lin, M.-H. Bae, F. Xiong, E. Pop and R. I. Masel, Adv. Mater., 2012, 24, 53–57 CrossRef CAS.
  121. J. Ma, M. Zhang, L. Dong, Y. Sun, Y. Su, Z. Xue and Z. Di, AIP Adv., 2019, 9, 075207 CrossRef.
  122. N. Bhalla, P. Jolly, N. Formisano and P. Estrela, Essays Biochem., 2016, 60, 1–8 CrossRef.
  123. S. Cheng, S. Hideshima, S. Kuroiwa, T. Nakanishi and T. Osaka, Sens. Actuators, B, 2015, 212, 329–334 CrossRef CAS.
  124. M. Huang, H. Li, H. He, X. Zhang and S. Wang, Anal. Methods, 2016, 8, 7413–7419 RSC.
  125. R. Seeber, L. Pigani, F. Terzi and C. Zanardi, Electrochim. Acta, 2015, 179, 350–363 CrossRef CAS.
  126. Y. Zang, J. Lei and H. Ju, Biosens. Bioelectron., 2017, 96, 8–16 CrossRef CAS.
  127. H. Y. Lin, W. H. Chen and C. H. Huang, Graphene in electrochemical biosensors, Elsevier Inc., 2019 Search PubMed.
  128. K. Shavanova, Y. Bakakina, I. Burkova, I. Shtepliuk, R. Viter, A. Ubelis, V. Beni, N. Starodub, R. Yakimova and V. Khranovskyy, Sensors, 2016, 16, 223 CrossRef.
  129. T. Hu, X. Mei, Y. Wang, X. Weng, R. Liang and M. Wei, Sci. Bull., 2019, 64, 1707–1727 CrossRef CAS.
  130. A. V. Pradeep, S. V. Satya Prasad, L. V. Suryam and P. Prasanna Kumari, Mater. Today: Proc., 2019, 19, 380–383 CAS.
  131. B. Liu and K. Zhou, Prog. Mater. Sci., 2019, 100, 99–169 CrossRef CAS.
  132. S. K. Vashist and J. H. T. Luong, Carbon, 2015, 84, 519–550 CrossRef CAS.
  133. F. Wang, C. Yang, C. Duan, D. Xiao, Y. Tang and J. Zhu, J. Electrochem. Soc., 2015, 162, B16–B21 CrossRef CAS.
  134. H. U. Kim, H. Y. Kim, H. Seok, V. Kanade, H. Yoo, K. Y. Park, J. H. Lee, M. H. Lee and T. Kim, Anal. Chem., 2020, 92, 6327–6333 CrossRef CAS.
  135. T. Wang, H. Zhu, J. Zhuo, Z. Zhu, P. Papakonstantinou, G. Lubarsky, J. Lin and M. Li, Anal. Chem., 2013, 85, 10289–10295 CrossRef CAS.
  136. J. M. Jeong, M. H. Yang, D. S. Kim, T. J. Lee, B. G. Choi and D. H. Kim, J. Colloid Interface Sci., 2017, 506, 379–385 CrossRef CAS.
  137. T. Yang, M. Chen, Q. Kong, X. Luo and K. Jiao, Biosens. Bioelectron., 2017, 89, 538–544 CrossRef CAS.
  138. Y.-N. Zheng, W.-B. Liang, C.-Y. Xiong, Y. Zhuo, Y.-Q. Chai and R. Yuan, Anal. Chem., 2017, 89, 9445–9451 CrossRef CAS.
  139. W. W. Zhao, J. J. Xu and H. Y. Chen, Chem. Soc. Rev., 2015, 44, 729–741 RSC.
  140. M. Wang, H. Yin, Y. Zhou, C. Sui, Y. Wang, X. Meng, G. I. N. Waterhouse and S. Ai, Biosens. Bioelectron., 2019, 128, 137–143 CrossRef CAS.
  141. Y.-C. Syu, W.-E. Hsu and C.-T. Lin, ECS J. Solid State Sci. Technol., 2018, 7(7), 3196–3207 CrossRef.
  142. C. S. Lee, S. Kyu Kim and M. Kim, Sensors, 2009, 9, 71111–77131 Search PubMed.
  143. M. Dankerl, M. V. Hauf, A. Lippert, L. H. Hess, S. Birner, I. D. Sharp, A. Mahmood, P. Mallet, J. Y. Veuillen, M. Stutzmann and J. A. Garrido, Adv. Funct. Mater., 2010, 20, 3117–3124 CrossRef CAS.
  144. L. H. Hess, M. Seifert and J. A. Garrido, Proc. IEEE, 2013, 101, 1780–1792 CAS.
  145. G. Seo, G. Lee, M. J. Kim, S. H. Baek, M. Choi, K. B. Ku, C. S. Lee, S. Jun, D. Park, H. G. Kim, S. J. Kim, J. O. Lee, B. T. Kim, E. C. Park and S. Il Kim, ACS Nano, 2020, 14, 5135–5142 CrossRef CAS.
  146. E. Stern, R. Wagner, F. J. Sigworth, R. Breaker, T. M. Fahmy and M. A. Reed, Nano Lett., 2007, 7, 3405–3409 CrossRef CAS.
  147. G. S. Kulkarni and Z. Zhong, Nano Lett., 2012, 12, 719–723 CrossRef CAS.
  148. M. T. Hwang, M. Heiranian, Y. Kim, S. You, J. Leem, A. Taqieddin, V. Faramarzi, Y. Jing, I. Park, A. M. van der Zande, S. Nam, N. R. Aluru and R. Bashir, Nat. Commun., 2020, 11, 1543 CrossRef CAS.
  149. B. Radisavljevic, A. Radenovic, J. Brivio, V. Giacometti and A. Kis, Nat. Nanotechnol., 2011, 6, 147–150 CrossRef CAS.
  150. M. Chhowalla, D. Jena and H. Zhang, Nat. Rev. Mater., 2016, 16052 CrossRef CAS.
  151. H. O. H. Churchill and P. Jarillo-Herrero, Nat. Nanotechnol., 2014, 9, 330–331 CrossRef CAS.
  152. B. N. Shivananju, H. Y. Hoh, W. Yu and Q. Bao, Optical biochemical sensors based on 2D materials, Elsevier Ltd, 2019 Search PubMed.
  153. B. N. Shivananju, W. Yu, Y. Liu, Y. Zhang, B. Lin, S. Li and Q. Bao, Adv. Funct. Mater., 2017, 27, 1603918 CrossRef.
  154. C. Zhu, D. Du and Y. Lin, 2D Mater., 2015, 2, 32004 CrossRef.
  155. B. N. Shivananju, H. Y. Hoh, W. Yu and Q. Bao, in Fundamentals and Sensing Applications of 2D Materials, Elsevier, 2019, pp. 379–406 Search PubMed.
  156. Z. Salamon, H. A. MacLeod and G. Tollin, Biochim. Biophys. Acta, Rev. Biomembr., 1997, 1331, 117–129 CrossRef CAS.
  157. G. Xia, C. Zhou, S. Jin, C. Huang, J. Xing and Z. Liu, Sensors, 2019, 19, 1198 CrossRef CAS.
  158. T. Xue, W. Liang, Y. Li, Y. Sun, Y. Xiang, Y. Zhang, Z. Dai, Y. Duo, L. Wu, K. Qi, B. N. Shivananju, L. Zhang, X. Cui, H. Zhang and Q. Bao, Nat. Commun., 2019, 10, 1–9 CrossRef.
  159. X. Chia, A. Y. S. Eng, A. Ambrosi, S. M. Tan and M. Pumera, Chem. Rev., 2015, 115, 11941–11966 CrossRef CAS.
  160. S. Su, C. Zhang, L. Yuwen, J. Chao, X. Zuo, X. Liu, C. Song, C. Fan and L. Wang, ACS Appl. Mater. Interfaces, 2014, 6, 18735–18741 CrossRef CAS.
  161. J. Zhao, Z. Zhang, S. Yang, H. Zheng and Y. Li, J. Alloys Compd., 2013, 559, 87–91 CrossRef CAS.
  162. J. Kim, S. Byun, A. J. Smith, J. Yu and J. Huang, J. Phys. Chem. Lett., 2013, 4, 1227–1232 CrossRef CAS.
  163. M. Shorie, V. Kumar, H. Kaur, K. Singh, V. K. Tomer and P. Sabherwal, Microchim. Acta, 2018, 185, 158 CrossRef.
  164. N. I. Khan and E. Song, Micromachines, 2020, 11, 220 CrossRef.
  165. P. M. Neema, A. M. Tomy and J. Cyriac, TrAC, Trends Anal. Chem., 2020, 124, 115797 CrossRef CAS.
  166. R.-M. Kong, L. Ding, Z. Wang, J. You and F. Qu, Anal. Bioanal. Chem., 2015, 407, 369–377 CrossRef CAS.
  167. H. Yang, X. Jie, L. Wang, Y. Zhang, M. Wang and W. Wei, Microchim. Acta, 2018, 185, 512 CrossRef.
  168. A. Zamora-Gálvez, E. Morales-Narváez, J. Romero and A. Merkoçi, Biosens. Bioelectron., 2018, 100, 208–213 CrossRef.
  169. X. Li, J. Shan, W. Zhang, S. Su, L. Yuwen and L. Wang, Small, 2017, 13, 1602660 CrossRef.
  170. S. Liu, X. Pan and H. Liu, Angew. Chem., 2020, 59, 5890–5900 CrossRef CAS.
  171. V. Yadav, S. Roy, P. Singh, Z. Khan and A. Jaiswal, Small, 2019, 15, 1–33 CrossRef.
  172. X. Qian, Z. Gu and Y. Chen, Mater. Horiz., 2017, 4, 800–816 RSC.
  173. S. Szunerits and R. Boukherroub, J. Mater. Chem. B, 2016, 4, 6892–6912 RSC.
  174. X. Yang, J. Li, T. Liang, C. Ma, Y. Zhang, H. Chen, N. Hanagata, H. Su and M. Xu, Nanoscale, 2014, 6, 10126–10133 RSC.
  175. K. Huang, Z. Li, J. Lin, G. Han and P. Huang, Chem. Soc. Rev., 2018, 47, 5109–5124 RSC.
  176. O. Akhavan and E. Ghaderi, ACS Nano, 2010, 4, 5731–5736 CrossRef CAS.
  177. X. Zou, L. Zhang, Z. Wang and Y. Luo, J. Am. Chem. Soc., 2016, 137, 2064–2077 CrossRef.
  178. K. Hossain, M. Rafatullah, S. Z. Abbas, A. Ahmad, N. Ismail and A. Y. Maruthi, in Micro and Nano Technologies, ed. M. Jawaid, A. Ahmad and D. Lokhat, Elsevier, 2019, pp. 293–314 Search PubMed.
  179. Y. Tu, M. Lv, P. Xiu, T. Huynh, M. Zhang, M. Castelli, Z. Liu, Q. Huang, C. Fan, H. Fang and R. Zhou, Nat. Nanotechnol., 2013, 8, 594–601 CrossRef CAS.
  180. B. Luan, T. Huynh, L. Zhao and R. Zhou, ACS Nano, 2015, 9, 663–669 CrossRef CAS.
  181. O. Akhavan and E. Ghaderi, Carbon, 2012, 50, 1853–1860 CrossRef CAS.
  182. J. D. West and L. J. Marnett, Chem. Res. Toxicol., 2006, 19, 173–194 Search PubMed.
  183. M. D. Rojas-Andrade, G. Chata, D. Rouholiman, J. Liu, C. Saltikov and S. Chen, Nanoscale, 2017, 9, 994–1006 RSC.
  184. A. Gusev, O. Zakharova, I. Vasyukova, D. S. Muratov, I. Rybkin, D. Bratashov, A. Lapanje, I. Il'inikh, E. Kolesnikov and D. Kuznetsov, Mater. Sci. Eng., C, 2019, 99, 275–281 CrossRef CAS.
  185. S. Liu, T. H. Zeng, M. Hofmann, E. Burcombe, J. Wei, R. Jiang, J. Kong and Y. Chen, ACS Nano, 2011, 5, 6971–6980 CrossRef CAS.
  186. I. E. Mejías Carpio, C. M. Santos, X. Wei and D. F. Rodrigues, Nanoscale, 2012, 4, 4746–4756 RSC.
  187. L. Mei, S. Zhu, W. Yin, C. Chen, G. Nie, Z. Gu and Y. Zhao, Theranostics, 2020, 10, 757–781 CrossRef CAS.
  188. M. Emanet, Ö. Sen, I. Ç. Taşkin and M. Çulha, Front. Bioeng. Biotechnol., 2019, 7 Search PubMed.
  189. K. Rasool, K. A. Mahmoud, D. J. Johnson, M. Helal, G. R. Berdiyorov and Y. Gogotsi, Sci. Rep., 2017, 7, 1–11 CrossRef CAS.
  190. R. Wu, X. Ou, R. Tian, J. Zhang, H. Jin, M. Dong, J. Li and L. Liu, Nanoscale, 2018, 10, 20162–20170 RSC.
  191. Q. Xu, P. Zhu, J. Zhang, Y. Liu, L. Cai, H. Jiang, M. Ji and J. Chen, Mater. Lett., 2020, 271, 127809 CrossRef CAS.
  192. T. I. Kim, J. Kim, I. J. Park, K. O. Cho and S. Y. Choi, 2D Mater., 2019, 6(2), 025025 CrossRef CAS.
  193. Z. Khatoon, C. D. McTiernan, E. J. Suuronen, T. F. Mah and E. I. Alarcon, Heliyon, 2018, 4, e01067 CrossRef.
  194. F. Ghilini, D. E. Pissinis, A. Miñán, P. L. Schilardi and C. Diaz, ACS Biomater. Sci. Eng., 2019, 5, 4920–4936 CrossRef CAS.
  195. M. Chhowalla and G. A. J. Amaratunga, Nature, 2000, 407, 164–167 CrossRef CAS.
  196. J. K. Yang, H. R. Lee, I. J. Hwang, H. I. Kim, D. B. Yim and J. H. Kim, Adv. Healthcare Mater., 2018, 7, 2–7 Search PubMed.
  197. J. Jang, Y. Choi, M. Tanaka and J. Choi, J. Ind. Eng. Chem., 2020, 83, 46–52 CrossRef CAS.
  198. J. Zheng, J. Li, L. Zhang, X. Chen, Y. Yu and H. Huang, J. Mater. Sci., 2020, 55, 7226–7246 CrossRef CAS.
  199. B. K. Gu, D. J. Choi, S. J. Park, Y. Kim and C. Kim, Cutting-Edge Enabling Technologies for Regenerative Medicine, 2018, vol. 1078 Search PubMed.
  200. J. Zhang, H. Chen, M. Zhao, G. Liu and J. Wu, Nano Res., 2020, 13, 2019–2034 CrossRef CAS.
  201. O. Erol, I. Uyan, M. Hatip, C. Yilmaz, A. B. Tekinay and M. O. Guler, Nanomedicine, 2018, 14, 2433–2454 CrossRef CAS.
  202. B. Lu, T. Li, H. Zhao, X. Li, C. Gao, S. Zhang and E. Xie, Nanoscale, 2012, 4, 2978–2982 RSC.
  203. V. Agarwal and K. Chatterjee, Nanoscale, 2018, 10, 16365–16397 RSC.
  204. H. Zanin, E. Saito, F. R. Marciano, H. J. Ceragioli, A. E. C. Granato, M. Porcionatto and A. O. Lobo, J. Mater. Chem. B, 2013, 1, 4947–4955 RSC.
  205. V. Rosa, H. Xie, N. Dubey, T. T. Madanagopal, S. S. Rajan, J. L. P. Morin, I. Islam and A. H. Castro Neto, Dent. Mater., 2016, 8, 1019–1025 CrossRef.
  206. J. J. Lee, Y. C. Shin, S. J. Song, J. M. Cha, S. W. Hong, Y. J. Lim, S. J. Jeong, D. W. Han and B. Kim, Coatings, 2018, 8, 13 CrossRef.
  207. J. Li, G. Wang, H. Geng, H. Zhu, M. Zhang, Z. Di, X. Liu, P. K. Chu and X. Wang, ACS Appl. Mater. Interfaces, 2015, 7, 19876–19881 CrossRef CAS.
  208. Y. Li, X. Zhang, C. Dai, Y. Yin, L. Gong, W. Pan, R. Huang, Y. Bu, X. Liao, K. Guo and F. Gao, ACS Biomater. Sci. Eng., 2020, 6, 3015–3025 CrossRef CAS.
  209. J. R. Choi, K. W. Yong, J. Y. Choi, A. Nilghaz, Y. Lin, J. Xu and X. Lu, Theranostics, 2018, 8, 1005–1026 CrossRef CAS.
  210. M. G. Raucci, I. Fasolino, M. Caporali, M. Serrano-Ruiz, A. Soriente, M. Peruzzini and L. Ambrosio, ACS Appl. Mater. Interfaces, 2019, 11, 9333–9342 CrossRef CAS.
  211. X. Liu, A. L. Miller, S. Park, M. N. George, B. E. Waletzki, H. Xu, A. Terzic and L. Lu, ACS Appl. Mater. Interfaces, 2019, 11, 23558–23572 CrossRef CAS.
  212. K. Huang, J. Wu and Z. Gu, ACS Appl. Mater. Interfaces, 2019, 11, 2908–2916 CrossRef CAS.
  213. L. Fusco, A. Gazzi, G. Peng, Y. Shin, S. Vranic, D. Bedognetti, F. Vitale, A. Yilmazer, X. Feng, B. Fadeel, C. Casiraghi and L. G. Delogu, Theranostics, 2020, 10, 5435–5488 CrossRef CAS.
  214. H. Zhang, T. Fan, W. Chen, Y. Li and B. Wang, Bioact. Mater., 2020, 5, 1071–1086 CrossRef.
  215. X. Sun, Z. Liu, K. Welsher, J. T. Robinson, A. Goodwin, S. Zaric and H. Dai, Nano Res., 2008, 1, 203–212 CrossRef CAS.
  216. S. Goenka, V. Sant and S. Sant, J. Controlled Release, 2014, 173, 75–88 CrossRef CAS.
  217. J. Liu, L. Cui and D. Losic, Acta Biomater., 2013, 9, 9243–9257 CrossRef CAS.
  218. L. Cheng, X. Wang, F. Gong, T. Liu and Z. Liu, Adv. Mater., 2020, 32, 1902333 CrossRef CAS.
  219. B. L. Li, R. Li, H. L. Zou, K. Ariga, N. B. Li and D. T. Leong, Mater. Horiz., 2020, 7, 455–469 RSC.
  220. G. Reina, J. M. González-Domínguez, A. Criado, E. Vázquez, A. Bianco and M. Prato, Chem. Soc. Rev., 2017, 46, 4400–4416 RSC.
  221. J. D. Schneible, K. Shi, A. T. Young, S. Ramesh, N. He, C. E. Dowdey, J. M. Dubnansky, R. L. Lilova, W. Gao, E. Santiso, M. Daniele and S. Menegatti, J. Mater. Chem. B, 2020, 8, 3852–3868 RSC.
  222. M.-H. Shin, E.-Y. Park, S. Han, H. S. Jung, D. H. Keum, G.-H. Lee, T. Kim, C. Kim, K. S. Kim, S. H. Yun and S. K. Hahn, Adv. Healthcare Mater., 2019, 8, 1801036 CrossRef.
  223. S. Wang, K. Li, Y. Chen, H. Chen, M. Ma, J. Feng, Q. Zhao and J. Shi, Biomaterials, 2015, 39, 206–217 CrossRef CAS.
  224. W. Yin, L. Yan, J. Yu, G. Tian, L. Zhou, X. Zheng, X. Zhang, Y. Yong, J. Li, Z. Gu and Y. Zhao, ACS Nano, 2014, 8, 6922–6933 CrossRef CAS.
  225. M. Xie, N. Yang, J. Cheng, M. Yang, T. Deng, Y. Li and C. Feng, Colloids Surf., B, 2020, 187, 110631 CrossRef CAS.
  226. Z. Fu, G. R. Williams, S. Niu, J. Wu, F. Gao, X. Zhang, Y. Yang, Y. Li and L.-M. Zhu, Nanoscale, 2020, 12, 14739–14750 RSC.
  227. A. Sundaram, J. S. Ponraj, J. S. Ponraj, C. Wang, W. K. Peng, R. K. Manavalan, S. C. Dhanabalan, H. Zhang and J. Gaspar, J. Mater. Chem. B, 2020, 8, 4990–5013 RSC.
  228. M. Qiu, D. Wang, W. Liang, L. Liu, Y. Zhang, X. Chen, D. K. Sang, C. Xing, Z. Li, B. Dong, F. Xing, D. Fan, S. Bao, H. Zhang and Y. Cao, Proc. Natl. Acad. Sci. U. S. A., 2018, 115, 501–506 CrossRef CAS.
  229. S. M. Sharker, Int. J. Nanomed., 2019, 14, 9983–9993 CrossRef.
  230. C. Martín, K. Kostarelos, M. Prato and A. Bianco, Chem. Commun., 2019, 55, 5540–5546 RSC.
  231. P. Wick, A. E. Louw-Gaume, M. Kucki, H. F. Krug, K. Kostarelos, B. Fadeel, K. A. Dawson, A. Salvati, E. Vázquez, L. Ballerini, M. Tretiach, F. Benfenati, E. Flahaut, L. Gauthier, M. Prato and A. Bianco, Angew. Chem., Int. Ed., 2014, 53, 7714–7718 CrossRef CAS.
  232. S. Mateti, C. S. Wong, Z. Liu, W. Yang, Y. Li, L. H. Li and Y. Chen, Nano Res., 2018, 11, 334–342 CrossRef CAS.
  233. K. Kostarelos and K. S. Novoselov, Science, 2014, 344, 261–263 CrossRef CAS.
  234. J. Park, S. Park, S. Ryu, S. H. Bhang, J. Kim, J.-K. Yoon, Y. H. Park, S.-P. Cho, S. Lee, B. H. Hong and B.-S. Kim, Adv. Healthcare Mater., 2014, 3, 176–181 CrossRef CAS.
  235. B. Ma, C. Martín, R. Kurapati and A. Bianco, Chem. Soc. Rev., 2020, 16–18 Search PubMed.
  236. D. A. Jasim, S. Murphy, L. Newman, A. Mironov, E. Prestat, J. McCaffrey, C. Ménard-Moyon, A. F. Rodrigues, A. Bianco, S. Haigh, R. Lennon and K. Kostarelos, ACS Nano, 2016, 10, 10753–10767 CrossRef CAS.
  237. T. Liu, C. Wang, X. Gu, H. Gong, L. Cheng, X. Shi, L. Feng, B. Sun and Z. Liu, Adv. Mater., 2014, 26, 3433–3440 CrossRef CAS.
  238. IT Crew, Graphene Flagship - Health and Environment.

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