Etching strategies induced multihierarchical structures of MOFs and their derivatives for gas sensing applications: a review

Zhuo Liu a, He Lv b and Yan Xu *ac
aDepartment of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning 110819, China. E-mail: xuyan@mail.neu.edu.cn; Fax: +86-024-83684533; Tel: +86-024-83684533
bQingdao Engineering Research Center for New Metallic Functional Materials, Qingdao Binhai University, Qingdao 266555, Shandong, P. R. China
cFoshan Graduate School of Innovation, Northeastern University, Foshan, Guangdong 528311, China

Received 27th November 2024 , Accepted 17th January 2025

First published on 17th January 2025


Abstract

A growing need for accurate monitoring of both outdoor and indoor pollution sources demands enhanced gas sensors with improved sensitivity, selectivity, stability, fast response and low detection limits. Metal–organic frameworks (MOFs), a class of porous materials, stand out as superior candidates for high performance gas detection due to their exceptional structure characteristics, including tunable porosity, limitless structural motifs, and customizable chemical components. Tailoring the structure and functionalization of MOFs through etching has opened up new opportunities to adjust the gas-sensing capabilities of MOFs. In this review article, we provide a concise overview of the most recent advancements in three distinct aspects of etching MOFs: pore engineering, chemical modification, and transformation of MOFs into targeted derivatives. Despite extensive progress, research on etching strategies to elucidate the intricate relationship between the innovative structure and the sensing properties remains in its infancy. Focusing on MOFs and their derivative-based gas sensors with distinct critical structural features, the schemes to enhance sensor performance are introduced. We also outline the current barriers and future prospects in the field of gas sensing. This review seeks to offer guidance on modulating MOF-based gas sensors by strategically applying efficient etching methods, navigating contemporary challenges and future prospects in the gas sensing field.


image file: d4tc05012f-p1.tif

Zhuo Liu

Zhuo Liu is currently a doctoral candidate in the Department of Chemistry at Northeastern University, China. Her research interests focus on the synthesis chemistry and technology of semiconductor nanomaterials, toxic and harmful gas sensitive materials and devices.

image file: d4tc05012f-p2.tif

He Lv

Dr. He Lv received her PhD degree from the School of Chemistry and Materials Science, Heilongjiang University, in 2021. She is an associate professor of the School of Mechanical and Electrical Engineering, Qingdao Binhai University. Her research interests are mainly directed towards the development of nanomaterials and inorganic hybrid materials and their application as gas sensors and cathodes in metal-ion batteries.

image file: d4tc05012f-p3.tif

Yan Xu

Yan Xu received her PhD degree from Jilin University in 2013. Currently, she is a university distinguished professor at Northeastern University. Her research interests focus on the design and synthesis of inorganic functional materials, as well as the study of their luminescent, gas-sensing, and electrochemical sensing properties.


1. Introduction

Hazardous gas sensing has emerged as a critical technology across various fields, including environmental monitoring and chemical process control, and applications in agriculture and medicine. Particularly, harmful gases like NO2, H2S, NH3, CO, and volatile organic chemicals (VOCs), emitted by industries, pose significant risk to human health and the environment. Extensive research has explored various materials, including semiconducting metal oxides (SMOx), carbon-based materials, polymers, and transition metal dichalcogenides (TMDs) for gas sensing applications.1 Nevertheless, developing novel gas sensors with ultrasensitive detection performance remains of great significance. Crystalline metal–organic frameworks (MOFs) are a class of materials with ordered and periodic structures formed by self-assembly of metal-based nodes, like metal ions or clusters, and various organic ligands through coordination bonds.2–4 Their high surface area, adjustable pore sizes, and customizable functionalities make MOFs ideal for a wide range of applications,5,6 particularly in selective gas sensing, for the following reasons: (1) their distinctive porous structures, varying in shape and size, facilitate easy gas access and transport within the skeleton; (2) gas molecules can be adsorbed onto the open metal active sites of MOFs through chemical coordination, or via intermolecular interactions, including van der Waals bonding, hydrogen bonding and π–π stacking with the functional groups of organic ligands; and (3) the tunable pore sizes and shapes enable a molecular sieving effect, and the multi-dimensional architecture of MOFs supports both reversible physisorption and robust chemisorption processes.7–10 Nevertheless, several drawbacks of MOFs, including narrow micropores, poor electrical conductivity, instability at high temperatures, and reduced adsorption capacity in high-humidity environments still inhibit their practical applications. Thus, functional MOF structures are gaining increasing prominence in the field of gas sensing, driven by the advancement of targeted, versatile, and convenient chemical modification techniques.

Intrinsic and extrinsic methods are commonly used to enhance the gas sensitivity and selectivity of MOFs in gas detection by precisely modifying the shapes and sizes of pore structures. Generally, the inherent pore structure of MOFs arising from bottom-up synthetic approaches is mainly determined by the secondary building units and the underlying network topology, which often entail high costs and complicated synthesis processes. In contrast, top-down post-synthetic techniques stand out due to their advantages of simplicity, low-temperature processing, and cost-effectiveness, and they can introduce destructive effects in the targeted structural units of MOFs by breaking the coordination, hydrogen bonds, and van der Waals interactions between metal nodes and organic ligands, achieving the formation of enlarged and precisely controlled pore structures. Researchers have developed various destructive methods for MOFs through tailored cleavage of metal-linker bonds, including missing linkers and/or missing clusters. These result in the formation of uncoordinated metal ions and adjustable local electronic structures, which can help expose more accessible surface active sites and display unique properties for sensing applications.11,12 Among these methods, chemical etching has been proven to be an effective method to create defective MOFs while maintaining excellent crystallinity to some extent. Selective etching strategies allow for customization of specific pore sizes and shapes in MOF structures, creating size-selective gas channels and specialized binding sites to enhance gas sensing performance.13

In addition, the etching-induced self-templated transformation of MOFs following post-treatment processes such as calcination, phosphorization, or sulfurization, nitridation, and carbonization are widely recognized as highly effective strategies for preparing optimized sensing materials with diverse compositions and morphologies, as well as tunable porous structures.14,15 Most of the recent research studies have emphasized the critical role of pre-designed MOF derivatives with hollow, core–shell, or yolk–shell structures in enhancing the sensitivity, selectivity, and response/recovery times of gas sensors.16–20 These resultant hierarchical structures are typically difficult to prepare directly. And these structures exhibit exceptional gas sensing performance due to the formation of extensive heterojunctions and the exposure of more active sites, facilitated by shell permeability and internal voids.21–23 Meanwhile, a variety of intriguing MOF derivative architectures, featuring multi-component interfaces such as assemblies of metal oxides, metal phosphides, metal carbides, metal sulfides, or even the combinations of these materials, have been prepared through etching combined with post-treatment techniques.24,25 This review details various etching cases in MOFs and their derivatives, focusing on the construction of functionalized MOFs through strategies such as pore-opening, chemical regulation and phase conversion. It systematically summarizes how the structure, morphology, and phase composition of MOFs and MOF-derived materials influence their sensing capabilities, shedding light on the correlation between these unique structures and enhanced gas sensing properties, as illustrated in Scheme 1. It also highlights the importance of synergistic effects among pore structures, defects, composition, and morphology in enhancing gas sensing performance. Finally, we outline the remaining challenges and propose future research directions to advance the application of etched MOFs and their derivatives in gas sensing.


image file: d4tc05012f-s1.tif
Scheme 1 Schematic illustration of etching MOFs and derivatives for gas sensing applications.12,26,27

2. Etching engineering in MOFs

Most MOFs have microporous structures with pore sizes less than 2 nm, which pose a significant impediment to their application, preventing large gas molecules from accessing the internal pores.28 Hierarchically porous MOFs (HP-MOFs), incorporating micropores, mesopores, and even macropores, have garnered remarkable interest due to the fact that micropores contribute to a high surface area, while the mesopores and macropores effectively enhance the heat and mass diffusion efficiency. Moreover, HP-MOFs expose more accessible surface active sites and can serve as sieves for selective gas transfer and sensing.29,30 The pore engineering in HP-MOFs induced by etching can be precisely manipulated by optimizing and adjusting the etching conditions, resulting in their versatile pore structures and enabling essential expansions in gas sensing applications.31,32

2.1 Pore opening

2.1.1 Micro-mesoporous MOFs: small gas molecule etching. For HP-MOFs that integrate micro- and mesopores, a synergistic combination of high specific surface area and enhanced mass transfer is achieved, and they outperform traditional microporous MOFs for gas sensing applications.33,34 Two primary strategies are applied to produce micro- and mesoporous HP-MOFs: the liquid etching method and the vapor atmosphere etching method. The liquid etching process often involves a sophisticated screening of etching agents, leading to the creation of numerous MOF derivatives. The complexity of liquid etching also enriches the diversity of MOF etching products, which will be discussed in detail in Section 2.2. Currently, the etching method using gaseous small molecules is garnering increasing attention. This method is valued for its ability to preserve the structural integrity of MOFs while creating uniformly moderate pore sizes.35–37

Ammonia (NH3) is an appropriate etching agent for creating pores within carboxylate-based MOFs at specific temperatures due to the strong interaction of NH3 with open metal sites and its ability to form hydrogen bonds with oxoanion clusters. Mohamed K. Albolkany38 and colleagues proposed an ammonia-assisted gas etching strategy to create mesopores in a carboxylate-based HKUST-1 MOF without affecting the structure integrity. In the etching process, the NH3 molecules coordinate with the unsaturated coordination copper in the paddle wheel units. Meanwhile, the increase in thermally driven temperature not only affects the etching depth but also influences the adjustability of the mesopore volume (Fig. 1). Similarly, Zhai et al. have also confirmed the superiority of the vapor etching strategy in achieving uniform micro- and mesopores in UiO-66 MOF.39 A lower concentration of vapor can reduce the etching rate and intensity, while a longer etching time can enlarge the pore size. Other small molecules, such as ozone,40 water,41 phosphoric acid42 and even acetic acid43 can also be used to etch different types of microporous MOFs to obtain HP-MOFs that retain their original crystallinity and morphology.44


image file: d4tc05012f-f1.tif
Fig. 1 Schematic representation of ammonia loading inside the microporous HKUST-1 cavities followed by thermal treatment at different temperatures (80 to 200 °C). Reproduced with permission.38 Copyright 2021, Wiley-VCH.
2.1.2 Micro-macroporous MOFs: hard template assisted etching. As the increasing requirements of micro-macroporous MOFs expand into various emerging applications, significant advancements have been introduced to create macropores within microporous MOFs (Fig. 2). For example, Wang et al. proposed a popular “hard template” synthesis strategy to obtain one three-dimensionally ordered macro-microporous zeolite imidazolate framework-8 (3DOM ZIF-8) using polystyrene sphere (PS) monolith as a template (diameter >50 nm), which can be subsequently etched and removed using dimethylformamide and dichloromethane (Fig. 2(a)). The resultant hierarchically interconnected structure comprises two types of pores: micropores originating from ZIF-8 itself and macropores formed by the direct removal of PS templates (Fig. 2(b)). Although macroporous MOFs have a lower specific surface area compared to traditional microporous or mesoporous MOFs (as shown in Fig. 2(c)), their larger pore volume and higher permeability can provide sufficient space to hold the gas molecules, enabling rapid mass transfer and efficient utilization of active sites. Beyond the commonly used PS spheres, the template intervention method also utilizes porous alumina, silicon, organic polymers, molecular sieves, and carbon nanotubes as templates.45–49 Such a template-assisted etching method primarily exploits the spatial confinement effects imposed by these templates to achieve precise control over the morphology and internal structure of MOFs.
image file: d4tc05012f-f2.tif
Fig. 2 (a) Illustration of the preparation of H-3DOM-Co/ONC. (b) and (c) N2 adsorption–desorption isotherms, and pore size distributions calculated from the non-local density functional theory model. Reproduced with permission.50 Copyright 2023, Wiley-VCH.
2.1.3 Meso-macroporous MOFs: localized agglomeration and applications of templates. It is well-established that random and diverse pores may be obtained in etched MOF structures, if we do not selectively use templates in the etching process. Thus, this section primarily discusses the controllable formation of macropores within mesoporous MOFs. Seok Jeong et al.51 employed a temperature-driven localized crystallite agglomeration strategy to modulate the pore size of 3-D MOF [Ni(HBTC)(bipy)], controlling the formation of a macro- and mesoporous structure through an “ontologies etching” process (Fig. 3(a)). Pore size analysis and BJH cumulative specific adsorption results indicate that the aging temperature and time can effectively modulate the pore widths within a range of 7–90 nm (Fig. 3(b)–(d)).
image file: d4tc05012f-f3.tif
Fig. 3 (a) Mesopore creation by localized crystallite agglomeration through post-synthetic heat-treatment. (b) N2 adsorption isotherms of 3-D MOF (1) and mesoporous MOFs (MeM-1(T, t)) at 77 K (T is the aging temperature in °C and t is the aging time in hours) and (c) pore size distributions of 3-D MOF and MeM-1(T, t). (d) Correlation between the pore dimensions of MeM-1(T, t) and the aging conditions. Reproduced with permission.51 Copyright 2022, Wiley-VCH.

Meso-macroporous hierarchical porous MOFs can also be synthesized using various soft/hard templates and then removing them as discussed in Section 2.1.2. Recently, a meso-macroporous HP-MOF was prepared through a solvent evaporation-induced strategy using polystyrene-block-poly(ethylene oxide) (PS-b-PEO) as the soft template.52 The PS-b-PEO template provides confined spaces that localize MOF building blocks, and a subsequent THF/methanol rinsing treatment guides the formation of uniform and alternating macropores with diameters ranging from 40 to 95 nm. Usually, these template strategies are not limited to specific categories of metal ions or organic ligands. Therefore, the choice of appropriate etching agents to remove the templates is crucial in controlling the formation, distribution and uniformity of pores. However, the method sometimes inevitably leads to partial structural damage during generation of meso-/macro-HP-MOF structures.53,54

2.2 Chemical regulation

Beyond the aforementioned pore-opening engineering of HP-MOFs, chemical etching of MOFs can also regulate MOF components and achieve defect modification in targeted regions.55–58 Precise screening of etching agents on specific MOFs poses a significant challenge in implementing this kind of chemical etching strategy. Here, we present a comprehensive classification of various etching strategies to help readers quickly customize synthesis approaches based on specific types of MOFs and etching requirements, thereby enhancing the accessibility and applicability of this knowledge.
2.2.1 Etching with acid. Inorganic acids and organic acids often produce distinct results in etching MOFs. The etching behaviors of inorganic acids depend on the pore size of the MOFs and the specific types of acid used.59 The size of inorganic protonic acid molecules is smaller than the pore size of MOFs, and the H+ proton will diffuse into the porous structure, facilitating the dissolution of the metal nodes and ensuring a continuous release of metal cations. For instance, Wang et al.60 reported a modified acid etching method, in which inorganic phosphoric acid was used to disassemble metal nodes and benzene-1,3,5-tricarboxylic acid (BTC) linkers, yielding nanocrystals with various morphologies. After etching for 72 h, the bulk HKUST-1 became a flower-like lamellar structure. Moreover, Luo and co-workers introduced a HNO3 etching method that enables the directional engraving of UiO-66-(OH)2 from the inside to outside, leading to the formation of a single-crystalline hollow UiO-66 structure.61 Consequently, the strategic selection of inorganic acids for etching of specific MOFs offers the potential for fine control over their various structures and morphologies. MOFs with typical hollow or core–shell structures are generally formed in the presence of organic acid molecules. For instance, tannic acid can interact with the four exposed {100} facets of NH2-MIL-125(Ti) and then small water molecules can pass through the channels of NH2-MIL-125(Ti) to bind with titanium species, resulting in the formation of a hollow TiO2@MOF structure.62 Tannic acid can also be used to etch ZIF series of MOFs. Typically, ZIF-8 crystals dispersed in tannic acid solutions of varying concentrations and stirred for different durations can form either a core–shell or even a hollow structure.63,64
2.2.2 Etching with alkaline etchants. Alkali etching agents can also induce the cleavage of metal–oxygen bonds, creating highly active sites within the MOF structure. However, the mechanism of alkali etching differs from that of acid etching. For instance, a defective MOF-808-X framework can be obtained by quantitatively adding the alkaline etchant NaOH to the precursor solutions.65 The addition competes with the trimesic acid (BTC) linkers for coordination with Zr clusters, resulting in linker deficiency. Simultaneously, hydroxyl groups coordinate with the zirconium clusters to form Zr–OH active sites (Fig. 4(a)). This strategy can also be applied for progressive formation of defective two-dimensional MOFs. Zhou et al.66 applied a high-concentration potassium hydroxide solution to etch and produce highly defective Ni(II)-MOF nanosheet arrays after breaking Ni–O bonds, accompanied by the generation of active open metal sites (Fig. 4(b)). Compared with parent MOFs, alkali-induced etching effectively preserves the structural integrity and morphological consistency of defect-rich MOFs.
image file: d4tc05012f-f4.tif
Fig. 4 (a) Schematic diagram of the degree of etching for MOF-808 and the series of MOF-808-X (X: 0.04–0.10). Reproduced with permission.65 Copyright 2023, Royal Society of Chemistry. (b) Schematic presentation of fabricating a defect-rich Ni(II)-based MOF nanosheet array through alkaline etching. Reproduced with permission.66 Copyright 2020, Wiley-VCH.
2.2.3 Etching with anions. Anions can serve as both etchants and functional sites to afford the synthesis of functionalized MOFs with an optimized electronic structure, high surface area, and numerous accessible active sites while maintaining structural stability. Recently, our research group successfully prepared a defect-rich Cu-BTC using MoO42− inorganic oxoanions through a top-down etching method, and the pore size increases with the rising proportion of MoO42− ions.67 Similarly, Xu et al. demonstrated that TeOx2− and SeOx2− can induce different anisotropic etching effects on CAU-17 to realize morphological evolution (Fig. 5(a)). Especially, a hollow tubular superstructure of CAU-17 was achieved by simply controlling the etching time with TeOx2− containing solution (Fig. 5(b)). Some small guests can also etch crystalline MOF materials with relatively weak coordination bonds. For example, iodine ions were found to be able to attack the Zn(II) ions in Zn-MOF structures, thereby creating additional mesopores and macropores in Zn-IPDA following a post-treatment method (Fig. 5(c)). As depicted in Fig. 5(d), the surface morphology of Zn-IPDA becomes increasingly coarse with greater iodine adsorption.
image file: d4tc05012f-f5.tif
Fig. 5 (a) The schematic anisotropic etching processes of CAU-17 by TeOx2− and SeOx2− anions. (b) TEM images of CAU-17 etched by TeO32− as a function of etching time. The bar sizes of the TEM images and their corresponding insets are 5 μm and 500 nm, respectively. Reproduced with permission.68 Copyright 2024, Elsevier B.V. (c) A schematic illustration of the adsorption of iodine by a nonporous CP. (d) SEM images of Zn-IPDA and I2@ Zn-IPDA-x (x = 50% and 100%) influenced by iodine adsorption. Reproduced with permission.69 Copyright 2024, Royal Society of Chemistry.
2.2.4 Etching with organic solvents. The organic solvent etching strategy is not suitable for all types of MOF materials. Generally, this process involves two fundamental steps: (1) the solvent acts as an etchant to coordinate with the metal centers, and (2) the subsequent dissolution of the metal nodes bonded to the etchant. However, the organic solvents may evoke swelling, deformation, and destruction of the MOF structure. Fan et al. demonstrated that DMF-induced etching initiates from the outer layer and progresses toward the central facets of the MOF microrods, where DMF molecules exhibit high attachment energies for surface adsorption, leading to the initial and primary hollowing out of the interior (Fig. 6(a)). As the reaction time extends, crystals with a hollow tubular structure are fully formed (Fig. 6(b)–(d)).
image file: d4tc05012f-f6.tif
Fig. 6 (a) Transformation process of 1D Cu-HMOF crystals. SEM images of 1D Cu-HMOF crystals at different reaction times: (b) 1 d, (c) 3 d, and (d) 5 d. Reproduced with permission.70 Copyright 2023, American Chemical Society.
2.2.5 Chelation-assisted selective etching (CASE). The CASE strategy presents a feasible approach for designing diverse hierarchical MOFs by utilizing the uniform chelation effect of the chelating agent on metal nodes. For example, Zhang et al.71 explored the selective etching of {100} crystal planes within NENU-3a ([Cu12(BTC)8]–[H3PW12O40]) through the adjustment of proton concentration in the chelator, achieving a hierarchical polyoxometalate-based metal–organic framework (POM@MOF). The chelating agent of ethylenediaminetetraacetic dianion EdtaH22− is able to combine with protons to release a low initial proton concentration (Fig. 7(a)), which are located at polar crystal facet locations in POM@MOF to induce selective etching. Then, as released metal ions in solution are chelated (Fig. 7(b)), additional protons are released to enhance the etching selectivity. The strategically controllable proton concentration regulated by CASE strategies enables precise control over MOF crystallography.
image file: d4tc05012f-f7.tif
Fig. 7 (a) A chelation-assisted selective etching (CASE) strategy of NENU-3a ([Cu12(BTC)8]-[H3PW12O40]). (b) The etching mechanism of EdtaH22− as an aided-etching. Reproduced with permission.71 Copyright 2020, American Chemical Society.
2.2.6 Cationic etching technique: exchange of central ions. A controllable cationic etching technique of MOFs is the most popular method for removing coordination center ions. The process requires that the binding strength between the etchant and the ligand should be greater than or at least comparable to the coordination strength between the metal ion in the original MOF and ligand. Fine-tuned heterogeneous interfaces in MOFs can also be formed by employing varying concentration gradients of metal cation exchange caused by lattice stress and distortions. In most cases, etching MOFs with metal ions can induce changes in the crystalline structure and even leads to different morphology evolution. In Cheng's work,72 Ni–Cu bimetallic organic frameworks are prepared by incorporating Ni ions into Cu-based frameworks through a straightforward solvothermal route. The MOFs exhibit various morphologies depending on the Ni2+/Cu2+ ratios (Fig. 8(a)). As the ratio of Ni ions increases, the bimetallic CuxNi1−x-MOF transforms from a folded honeycomb morphology (Fig. 8(b1) and (c1)) to a lamellar nanosheet structure (Fig. 8(b2) and (c2)), then to a typical cuboid structure (Fig. 8(b3) and (c3)), and finally to a pyramidal block structure (Fig. 8(b4) and (c4)). When only Ni ions are used as the metal source, the resulting product shows an irregular rod/belt-like structure (Fig. 8(b5) and (c5)). Yohei et al.73 controlled the crystal sizes and defects of Al-based MIL-53 using Cr(NO3)3 as an etchant. This process involves ligand transfer from the MIL-53 skeleton to Cr3+ ions, which were then released as Cr3+ complexes into the solution (Fig. 8(d)). The morphologies of the etching products can be well sustained with metal ions with strong coordination effects (Fig. 8(e1) and (e6)). Controlling spatial distribution of multiple metals in etched MOFs requires a deeper understanding of the crystal exchange process and the interactions between metals and linkers.
image file: d4tc05012f-f8.tif
Fig. 8 (a) Schematic diagram of the regulation and reaction in the preparation of bimetal CuxNi1−x-MOF. Morphological and structural analysis of CuxNi1−x-MOF. (a1–5) SEM and (b1–5) TEM images of CuxNi1−x-MOF. Reproduced with permission.72 Copyright 2022 Wiley-VCH GmbH. (d) Cr3+ ion exchange reaction-based etching in Al-based MIL-53 MOF. SEM images of compounds (e1) Bulk-MIL-53-NH2, (e2) Bulk-MIL-53-NH2(25), (e3) Bulk-MIL-53-NH2(50), (e4) Bulk-MIL-53-NH2(75), (e5) Bulk-MIL-53-NH2(100), and (e6) Bulk-MIL-53-NH2(200). Reproduced with permission.73 Copyright 2024 American Chemical Society.
2.2.7 Exchange of ligands. Chemical modification of ligands is another feasible strategy for regulating the texture of MOFs. The deformation of coordination bonds and replacement of linkers enable the tuning of spatial defects within the framework at the molecular level, so the characteristics of the defect structure are largely influenced by the post-synthetic transformation process. Krause et al.74 introduced defects into the DUT-49 framework by substituting the tetradentate 9,9′-([1,1′-[biphenyl]-4,4′-diyl)][bis(9H-carbazole-3,6-dicarboxylate) (bbcdc)] ligands with bidentate 9H-carbazole-3,6-dicarboxylate (cdc) ligands (Fig. 9(a)). The linker segments in Fig. 9(b), or even the entire building blocks of MOP (Fig. 9(c)), can be cleaved depending on the cdc substitution concentration (Fig. 9(d1)–(d4)). This process includes a comprehensive analysis of ligand exchange principles in coordination chemistry, which can also be viewed as the chemical etching of MOF structures using organic ligands as the etchant. By introducing new ligands into the framework, it is possible to modify the electronic structure, thereby tuning the electrochemical properties of MOFs.
image file: d4tc05012f-f9.tif
Fig. 9 (a)–(c) Method applied to introduce defects into the DUT-49 lattice by replacement of bbcdc by cdc in the defect free DUT-49 crystal lattice (a) with cdc generating defects (purple) of missing linkers (b) or missing clusters (c). Color code: C, gray; O, red; H, white; N, blue; and Cu, turquoise. SEM images of defDUT-49(0) (d1), defDUT-49(1) (d2), defDUT-49(2) (d3), and defDUT-49(3) (d4); orange scale bar 2 μm. Reproduced with permission.75 Copyright 2023, American Chemical Society.
2.2.8 Other external resource-assisted etching: physical method. Physical treatment involves the use of additional energy to introduce defects into ordered MOF crystals. To date, various laser sources have been employed to remove the “photolabile” linkers while preserving the overall crystallinity and structural integrity of the original MOF structure. The etching principle involves creating missing-cluster defects, which can be tuned by adjusting the laser exposure time and the ratio of photolabile to robust linkers. For example, Wang et al.76 selected four different powers of Ar radio frequency plasma to construct the defects of terminal OH and H2O within Fe-based MOFs (MIL-53(Fe), MIL-88B(Fe), MIL-100(Fe) and MIL-101(Fe)), resulting in the formation of different coordinatively unsaturated Fe centers (Fig. 10(a)). The pristine MIL-100(Fe) exhibits an octahedral morphology (Fig. 10(b) and (d)), whereas the samples modified by plasma treatment become highly porous (Fig. 10(c) and (e)). The generated unsaturated metal sites with an electron-rich structure are conducive to providing more accessible active sites. Wang et al.77 proposed to produce MOF defects by eliminating “photolabile” linkers in UiO-66 upon ultraviolet (UV) laser irradiation. The results showed that the ratio of mesopores/micropores increased with elongated exposure time and incorporation of photolabile linkers. In summary, physical techniques such as plasma and laser etching can induce systematic structural modifications in MOF materials at both nanoscale and atomic levels.
image file: d4tc05012f-f10.tif
Fig. 10 (a) Schematic illustration of the plasma-assisted synthesis of MOF catalysts with different types of defects. SEM and TEM images of (b), (d) the pristine MIL-100(Fe) and (c), (e) MIL-100(Fe)-200W. Reproduced with permission.76 Copyright 2024, Wiley-VCH.

3. Etching strategy in conversion of MOFs

Controllable composition, tunable structure, and high porosity of MOF materials make them excellent candidates for functional nanomaterials in gas sensing applications. Meanwhile, derivatives of MOFs including metal oxides, sulfides/selenides, phosphides, and carbon-based composites have also been demonstrated to have high chemical stability and good electrical conductivity.77,78 Several post-treatment procedures including surface growth, multiple metal doping, anion alteration, and pyralysis treatment have been developed to prepare MOF derivatives, which are inseparable from the calcination method.79–82 These MOF derived derivatives can be prepared through the calcination method under different atmospheres, such as air, O2, H2, sulfur/selenium vapor, NH3, PH3, and Ar, N2, Cl2. These materials typically have a large number of accessible active sites and a porous electron transport path, which is expected to enhance the gas sensing performance. Here, we systematically provide a comprehensive overview of the MOF-derived materials obtained through a chemical etching strategy combined with post-heating treatment.

3.1 Conversion to monometallic or polymetallic oxides

Large numbers of MOF materials after heating in an air atmosphere are capable of generating a large variety of metal oxides, which inherit the abundant structural geometries of the MOF precursors with distinctive electronic structures.83–85 When MOFs are post-treated in air, the metallic nuclei are thermally triggered that grow into oxide nanostructures, whereas organic linkers start to decompose and are converted to CO2 gas in situ during calcination. It has been noted that the resulting texture of metal oxide particles such as morphologies, porosity and grain size can be significantly influenced by the selection of precursors and pyrolysis conditions. For instance, Ren et al. successfully produced MOF-derived porous and hollow ZnO nanocubes by precise control of the pyrolysis temperature.86 In addition, polymetallic oxides with unique hierarchical structures87 can be obtained by introducing other metals into MOFs. These MOF-derived polymetallic oxides offer adjustable carrier concentrations, more active sites, and hierarchical pore structures owing to their complex component optimization and unique structure characteristics, which have been widely used in gas sensing materials.

Pyrolysis in an inert atmosphere can help to preserve the carbon skeleton in most cases, and some unique nanostructures with single- or multi-components such as collapsed hollow structures,88 core–shell structures,89 yolk–shell structures,90,91 and particle close packing structures92 of metal based carbonitrides or other hybrids93 can also be prepared. In 2021, Chen et al.94 reported a hierarchical Co–Ni–Fe spinel oxide-carbonitride hybrid (CoNiFeOx-NC) (Fig. 11). Starting with Fe-MIL-101-NH2 as the precursor, Co2+ and Ni2+ were introduced via an ion-exchange process. The cationic etching process can induce isotropic inward or outward contraction of Fe-MOF precursors, leading to the formation of a collapsed nanoflower structure of CoNiFeOx-NC after pyrolysis. The MOF-derived carbon framework synergistically possesses π-rich-electrons, high surface area, and large hierarchical pore volume, arousing great research interest for gas sensing applications.


image file: d4tc05012f-f11.tif
Fig. 11 Schematic of the synthesis of CoNiFeOx-NC from Fe-MIL-101-NH2 MOFs. Reproduced with permission.94 Copyright 2021, Elsevier B.V.

3.2 Conversion to metal phosphides

MOF-derived transition metal phosphide (TMP) materials prepared by an etching process and high temperature pyrolysis usually have an intriguing hollow structure and desired composition. This synthesis avoids the use of flammable and toxic phosphating reagents, thus offering a large number of accessible active sites and facilitating efficient charge transport, which are beneficial for the acceleration of gas sensing reactions. For example, atomic-level uniform distribution of metal nodes within ultra-thin 2D TMP composites can be achieved by removing linkers from MOFs though an in situ etching process in the presence of the phosphate group or oxometrophosphate radical. Yang et al.95 synthesized a hollow FeP/Fe2P/Cu3P–N, P co-doped carbon (Fe–P/Cu3P–NPC) hybrid using an in situ “etching-adsorption-phosphatization” strategy (Fig. 12(a) and (b)). Similarly, Lv et al.96 reported on Cr-doped cobalt phosphide and MOF-derived phosphor-nitrogenated porous carbon with an amorphous sheet-like structure via a typical in situ etching and phosphorization process, which perfectly inherited the unique structure of the precursor (Fig. 12(c)). Therefore, by using a MOF as a metal-loading template and subjecting it to etching and annealing treatments, the derived metal phosphide structures effectively prevent the metal ion aggregation while maintaining high surface activity.
image file: d4tc05012f-f12.tif
Fig. 12 (a) Schematic illustration of the synthesis process of Fe–P/Cu3P–NPC, (b1), (b2) ZIF-8@PA, and (b3), and (b4) Fe–P/Cu3P–NPC. Reproduced with permission.95 Copyright 2023, Wiley-VCH. (c) Schematic of the formation mechanism of the Co-MOF derived Cr–Co–P composite.96 Copyright 2023, Wiley-VCH.

3.3 Conversion to metal sulfides/selenides

Thanks to their unique electronic structures, strong metallic properties, and diverse valence states, metal sulfides/selenides boast high conductivity and rich active sites, showing great potential for gas sensing applications.97,98 A large amount of literature studies reported the use of etching-induced metal sulfide/selenide for gas sensing. Wet chemical sulfuration and vapor sulfuration methods are generally used for chemically generating MOF-derived sulfides/selenides. Li et al.99 rationally designed a defect-rich, hierarchical Fe7S8/C@d-MoS2 hybrid nanocage derived from the sulfuration of polypyrrole–phosphomolybdic acid (PPy–PMo12) functionalized hollow TA-MIL-88B(Fe) crystals. Wang et al.100 reported a two-step MOF-assisted synthesis method to construct hierarchical FeCoS2–CoS2 double-shelled nanotubes (DSNTs). The process involves cationic etching that converts the Fe-based MOF (MIL-88A) into Fe–Co hydroxide DSNTs, followed by sulfidation. Yan et al.101 proposed the preparation of CuS/Cu-MOF through hydrothermal treatment of a truncated octahedral Cu-BTC MOF with thioacetamide, followed by annealing under an Ar atmosphere (Fig. 13). Thiopolybdic acid, thioacetamide, L-cysteine and Na2S can also be used as etching agents prior to the annealing treatment for the preparation of MOF derived metal sulfides. These MOF-derived metal sulfides and selenides exposing more active sites are conducive to the adsorption of target gas molecules, and their improved conductivity facilitates the transfer of electric charges between gas molecules and sensing materials.
image file: d4tc05012f-f13.tif
Fig. 13 Schematic representation of the preparation of porous CuSx/C nanospheres. Reproduced with permission.101 Copyright 2023, Elsevier B.V.

3.4 Conversion to metal nitrides

N atoms can be incorporated into the interstitial lattice of MOF derivatives generally by bonding covalently to the metal atoms, achieving metal-like features such as better conductivities and stabilities.102–104 The formation of a metal–nitrogen bond can regulate the density of states for the metal d-band, affording the metal nitrides an electron-donating character, which may contribute to the REDOX reactions with oxidizing gases. Recently, several techniques such as hydrothermal/solvothermal methods, direct/indirect pyrolysis, direct/indirect ammonolysis, magnetron sputtering, and atomic layer deposition have been used to prepare metal nitrides based on a MOF sacrificial templating method.105,106 Chen et al.107 directly nitridated Co-based ZIF in the presence of flowing NH3 gas. The Co2+ ions liberated from ZIF-67 reacted with NH3 to form Co5.47N nanoparticles. Simultaneously, the coordinated organic ligands underwent in situ decomposition and carbonization to form Co5.47N NP@N–PC. Thus, ammonia served as both an etchant and a source of nitrogen (Fig. 14(a)), and the ultrafine Co5.47N nanoparticles were encapsulated in hybrid Co5.47N NP@N–PC composites (Fig. 14(b)). Wang et al. synthesized ZIF-67 derived ultrathin MoN−Co2N nanosheets by an etching process in the presence of ammonium molybdate, followed by nitridation at 500 °C (Fig. 14(c) and (d)).108 The nitride composites exhibit rich exposed metal active sites, high specific surface area, excellent porosity, and enhanced conductivity. Similarly, many other transition metal nitrides, including vanadium nitride (VN),109–111 titanium nitride (TiN),112–114 chromium nitride (CrN)115–117 and cobalt nitride (CoN)118–120 were prepared from MOF precursors.
image file: d4tc05012f-f14.tif
Fig. 14 (a) Synthesis of Co5.47N NP@N–PC. (b) TEM image of Co5.47N NP@N–PC. Reproduced with permission.107 Copyright 2018, American Chemical Society. (c) Synthesis of MoN–Co2N nanosheets. (d) SEM image of MoN–Co2N. Reproduced with permission.109 Copyright 2022, American Chemical Society.

3.5 Conversion to carbon or carbon-based composites

Various carbon-based porous materials with controllable components are obtained from MOF precursors by combining etching and pyrolysis methods. Mao et al.121 produced a Mn-MOF-derived porous carbon (MDPC) by thermally transforming sheet-like manganese-based MOFs, combined with an acid etching strategy (Fig. 15). The combination of pyrolysis and etching strategies enables the synthesis of highly pure porous carbon-based materials with an enlarged specific surface area. Also, the organic ligands in certain MOFs may contain desirable elements such as phosphorus, boron, sulfur, and nitrogen, etc., which can be utilized to form heteroatom-doped carbon materials.122,123 Compared with pure carbon materials, carbon-based composites formed by high-temperature cracking generally have an interconnected 3D network structure with high porosity, large specific surface area, good dispersion and strong stability, and MOF-derived carbon materials and carbon-based composites via pyrolysis and etching strategies have also been widely used in gas sensing, biomedicine, catalyst carriers, and even gas adsorption and separation applications.
image file: d4tc05012f-f15.tif
Fig. 15 (a) Typical synthetic procedures for the MDPC sample. SEM images of (b) Mn(BDC)(H2O)2, (c) MnO–C composite, and (d) MDPC. Reproduced with permission.121 Copyright 2020 Wiley-VCH GmbH.

4. Chemiresistive sensing applications

MOFs and their derivatives have garnered significant attention in the field of gas sensing. A systematic and comprehensive understanding regarding the sensitive gas sensing performance is significant to improve their chemiresistive sensing applications. As we have discussed above, three distinct groups of chemical etching strategies of MOFs are present, including pore opening, defect modification, and the self-templated transformation. These resultant MOF-based sensing materials obtained by etching strategies exhibit unique advantages in gas-sensing devices due to the fact that the multi-level hierarchical porous structures enable a high transport path for the target gas, facilitating enhanced penetration and absorption. Controllable defects inside MOFs and precise control over the morphology of MOF derivatives afford them large specific surface areas, and rich active sites for promising gas sensing applications.

We will focus in this part on the different sensing mechanisms of MOF based gas sensors. To date, most studies in the field of MOF gas sensing have employed a combination of various synthetic strategies to develop novel structural gas sensors. However, it is hard to clearly set apart these different strategies when designing new schemes, leading to confusion about the correlation between “strategy and performance”. Thus, a targeted and comprehensive review that can clarify the self-regulatory and auxiliary regulatory role of MOFs, as well as their significance in sensing applications is greatly required, and our current work aims to fill this gap.

4.1 Hierarchical pore structure in MOFs: improving selectivity

Selectivity is a crucial parameter to consider during the fabrication and development of gas sensors. It refers to a sensor's ability to distinguish the specific target gas from a mixture of gases. Low selectivity in gas sensors hinders their ability to detect a single target gas. Selectivity can be defined as,
image file: d4tc05012f-t1.tif

The selection capacity of MOFs to sensing molecules depends on their pore size.124,125 For example, Wang and colleagues developed a solvent-coordination-directed structure swelling method to modulate the ratio between the large and narrow pore phases in the flexible MOF, MIL-88B. The resulting MIL-88B-20% sample, which has an optimal proportion of the large pore phase, exhibits a high specific surface area and a rough surface, demonstrating unique selectivity towards H2S gas. Gases with kinetic diameters significantly exceeding 3.6 Å are unable to enter the pores of MIL-88B (Fig. 16). In our recent research work, we also developed a highly selective NO2 sensor using sodium molybdate-etched defective porous Cu-MOF@MXene sensors,126 where NO2 interacts with the ordered reduction states of metal active sites through chemical coordination interactions. These studies highlight the pertinent role of MOFs in enhancing selectivity for target gases through their pore molecular sieving effect or coordinating with unsaturated metal sites.


image file: d4tc05012f-f16.tif
Fig. 16 Illustration of the solvent-coordination directed structure swelling method for the preparation of narrow pore (np) phase and large pore (lp) phase MIL-88B and their pore-size dependent gas sensing properties. Reproduced with permission.127 Copyright 2023, Wiley-VCH.

4.2 MOF derived metal oxides/sulfur/nitrogen/phosphide in gas sensing: improving sensitivity

The sensitivity of a sensor also plays a crucial role in determining its response capability.128 For n-type materials, sensitivity is defined as the ratio between the resistance change of the sensor in the target gas and its resistance in the air atmosphere. For p-type materials, sensitivity is defined as the ratio between the resistance change of the sensor in the target gas and its resistance when exposed to air (eqn (1)). Mathematically speaking, sensitivity can be expressed as a percentage value as in eqn (2):129
 
S = Ra/Rg or Rg/Ra(1)
 
S = [(RaRg)/Rg] × 100%(2)
where Rg and Ra represent the sensor resistance in the target gas and in the air, respectively. For the chemiresistor gas sensors, the sensitivity of a device is frequently influenced by the capacity in terms of gas molecule chemisorption and consequent charge transfer across the gas–solid interface, which is closely related to the specific surface area, the acidity or alkalinity of the surface, and the redox properties of the sensing materials.

Different MOF derivatives exhibit varied responses to different gases. Derivatives formed by oxidation, vulcanization, nitridation, and phosphorization exhibit enhanced sensitivity towards oxidizing gases due to the strong charge transfer between the lone pairs of electrons in O, S, N, and P elements and the gases. Additionally, the stratified mesoporous structure formed by calcination, along with a high specific surface area, defects, and the narrowing band gap also contribute to the high sensitivity. Park et al.130 utilized rhombic dodecahedral ZIF-67 as a “template” and immersed it in polyoxotungstate solutions. Simultaneously, the ZIF-67 surface was gradually etched, allowing the released Co cations to approach the adsorbed [PW12O40]3− and precipitate on the surface. Consequently, a well-defined Co3O4@polyoxometalate yolk–shell structure was fabricated, showing an excellent chemiresistive response (180.6) for isoprene and a satisfactory conversion efficiency (η) of 50% (Fig. 17(a) and (b)). The outstanding performance of the yolk–shell 3-Co3O4@CoPW nanoreactor stems from the electronic sensitization effect and its role in the gas reforming reaction of isoprene (Fig. 17(c)).


image file: d4tc05012f-f17.tif
Fig. 17 (a) Gas responses (Rg/Ra − 1) of thin-CoPW, 3-Co3O4@CoPW, and c-Co3O4/CoPW sensors to various biomarker gases. (b) Conversion efficiency of isoprene in the absence and presence of 3-Co3O4@CoPW. (c) Schematic of the gas reforming reaction. Reproduced with permission.130 Copyright 2023, American Chemical Society.

4.3 MOF-derived carbon-based materials: improving the response rate

The response rate generally refers to how efficiently charge transfer converts into a change in electrical resistance within a sensor. This is influenced by many factors, such as the electronic conduction properties, carrier concentration and mobility, as well as the grain size, and porosity of gas-sensitive materials. The response rate is defined by the time it takes for the sensor's electrical output to reach 90% of its final value after exposure to a change in the analyte concentration. Optimizing materials’ design and structure can significantly improve the adsorption kinetics of the sensing layer towards the target gas molecules.

Hyeongtae Lim et al.131 fabricated homogeneous and precise micropatterns of MOx/C crystals through laser processing. Therein, numerous p–p junctions are formed within CuO/C nanoparticles (Fig. 18(a)). During gas adsorption, the decrease in carbon's Fermi level reduces the energy barrier, enhancing the hole conduction, which accelerates the frequency at which ethanol molecule levels are converted to electrical signals for sensitive detection (Fig. 18(b)). Additionally, Xian et al.132 prepared ZIF-8-derived ZnO micro-dodecahedra/flower structures (ZnO-DFs) through sulfuric acid (H2SO4) modification, which exhibited a fast response time (∼0.95 s). The key to enhancing sensing performance is the effect of morphological changes in ZnO-DFs on the thickness of the electron depletion layer. Thus, the fast response rate of the ZnO-DFs-2.5 sensor can be attributed to the increased thickness of the depletion layer and the grain-to-grain barrier between air and acetone. It is mentioned in some other references that a larger specific surface area can provide more oxygen species, which enhances sensor reactivity. Smaller crystal sizes and uniform pore spaces shorten the gas diffusion path. To sum up, these factors improve the sensor's adsorption and charge transfer capacity for oxygen species and regulate the response rate of the gas sensor.


image file: d4tc05012f-f18.tif
Fig. 18 (a) Schematic representation of the fabrication of the MOF-derived metal oxide/carbon composite (MOx/C) by a laser process. (b) Comparison of the response and recovery time of pristine Cu3HHTP2 and CuO/C under exposure to ethanol. (c) Energy band diagram illustrating the formation of a junction between carbon and copper oxide. Reproduced with permission.131 Copyright 2024, Springer.

4.4 Reversibility and long-term stability

The reliability of a sensor in maintaining stable response and sensitivity can be assessed by evaluating signal quality over a period of operation. Reversibility testing involves measuring the response–recovery cycles using the same concentration of target gas at a fixed operating temperature, and then analysing any amplitude changes between the response and recovery curves. Long-term stability testing entails running the sensor for several days or more, plotting its response against time to assess stability.

The primary strategies for enhancing the chemical stability of MOFs include reinforcing coordination bonds, incorporating hydrophobic groups, rigid ligands, and increasing connectivity. Compared to MOFs built from mononuclear metal ions, metal cluster-based MOFs provide a wider range of structural diversity and improve material stability through enhanced connectivity. For instance, Chungseong Park et al. proposed a robust solution to the stability limitations by creating a microenvironment for Pd single-atom catalysts (SACs) within the cMOF via the electrochemical deposition of metal precursors (Fig. 19(a)). The microenvironment protects cMOFs from irreversible structural distortion and facilitates reversible charge transfer with NO2, resulting in a fully recoverable NO2 response (Fig. 19(b)). This level of reversibility was scarcely achieved with other functionalization methods in 2D-cMOFs of this category.


image file: d4tc05012f-f19.tif
Fig. 19 Schematic illustration of (a) advantages of the SAC-functionalized cMOF compared to the NP-decorated counterpart. Dynamic response traces of cMOF and Pd1-cMOF (b) upon 10 cycles of 1 ppm of NO2 exposure and subsequent recovery in air. Reproduced with permission.133 Copyright 2024, American Chemical Society.

4.5 Limit of detection (LOD): ligand functionalization in MOFs

LOD plays a vital role in gas sensors, especially those used for monitoring air quality. The thresholds set by the European Union (EU) and U.S. National Ambient Air Quality Standards (NAAQS) define acceptable levels of significant air pollutants, ranging from several ppb to several ppm.134 An extremely low detection limit is related to the target gas adsorption mechanism within a MOF. By tuning defects in a MOF, adjusting active sites and topological features particularly pore sizes, we can jointly reduce the adsorption energy of gas, allowing trace gas molecules to reach the interior through the pores, and ultimately reducing the detection limit.

Zhai et al.135 reported a post-synthesis modification approach to incorporate 2,3,4-trihydroxybenzaldehyde (THBA) into the UiO-66-NH2 framework, and subsequently load it onto a polyacrylonitrile nanofiber membrane (PAN NM) to obtain a gas sensor for detecting trace amounts of SO2 gas. This modification process involves covalent cross-linking between NH2 on the UiO-66-NH2 ligand and the –CHO group of THBA, forming a Schiff base via an aldimine condensation reaction (Fig. 20(a)). The additional hydroxyl groups on UiO-66-NH2/PAN provide suitable adsorption sites for targeted SO2 without affecting the integrity of MOFs (Fig. 20(b)).


image file: d4tc05012f-f20.tif
Fig. 20 (a) Schematic of the synthesis of UiO-66-THB. (b) Schematic of the targeted SO2 gas adsorption mechanism. Reproduced with permission.135 Copyright 2022, Published by Elsevier B.V.

5. Outlook (perspectives and challenges)

MOFs and their derivatives offer tremendous versatility and flexibility in detecting hazardous gases. This review provides a summary and classification for various etching strategies using different etching agents and an in-depth understanding of the etching mechanisms. It also shows that the physical/chemical sensitivity, selectivity, stability, response rates and detection limits of MOFs and their derivatives can be controlled and improved by the precise design of MOFs' structure and chemical composition. The survey of literature indicates that improvement in sensing performance is often inseparable from high surface area, tunable porosity, targeted morphology, creative active sites and even crystal purity in products. To date, the development of MOF-based gas sensors still faces tough challenges for practical and emerging applications. Some key aspects and chances need to be considered for the future research of MOFs in the gas sensing field.

(i) Localized/targeted etching serves as a crucial approach for achieving precise pore engineering and defect design in MOFs.136 Constructing a model of gas adsorption in defective MOF structural units enables us to propose a clear view on how different defect sites affect the adsorption performance, thereby establishing a relationship between etching-induced defects and sensing performance. However, the relevant systematic studies are still limited and worthy of great research efforts.

(ii) Novel gas adsorption mechanisms based on etching-induced MOFs or their derivatives for unconventional hazardous gases remain scarce. This highlights the boundless potential of MOF materials in the field of gas sensing. Theoretical calculations usually cannot show the whole reaction process of gas adsorption and desorption in different framework structures. It is encouraged to research the reaction mechanisms of unconventional hazardous gases through effective in situ characterization methods.

(iii) To date, the signals of MOF-based gas sensors have been mainly monitored by the variation of electric parameters.137,138 Achieving stable and enhanced electrical signals from MOF-based resistance sensors presents a significant challenge. Recent advanced progress in fabricating MOF-based hybrid gels or thin films has opened their potential application in gas sensing. The integration of functional MOF films and conductive polymer gels on a flexible substrate brings new opportunities for flexible sensing applications.

(iv) Current MOF-based gas sensing systems are facing substantial challenges in commercial applications in terms of reproducibilities and long-term efficiencies. This is especially important for multifunctional integrated device matrices designed for real environmental cleanup. The high price and low productivity of MOFs also hinder their large-scale preparation in industry. More efforts are required to develop easy-preparation procedures of MOF materials to narrow the gap between lab scale and industrial production.

(v) Currently, subminiaturized, stretchable, and wearable bioelectronic devices are a future developing trend of cutting-edge equipment. Continuous interdisciplinary collaboration for chemical technologies, medical, biological, engineering and environmental applications is needed to unlock the full potential of functionalized MOF-based sensors. Further exploration of flexible MOF hybrid materials and self-assembly technologies to integrate superior electrical conductivities, high performance and mechanical robustness is essential for designing reliable gas sensing devices.

Data availability

Data are available upon request from the authors.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

The present work was supported by the National Natural Science Foundation of China (grant no. 22171040), Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program (no. RC230784), and Guangdong Basic and Applied Basic Research Foundation (no. 2023A1515140011).

References

  1. A. Imash, G. Smagulova, B. Kaidar, A. Keneshbekova, R. Kazhdanbekov, L. F. Velasco and Z. Mansurov, Sensors, 2024, 24, 6797 CrossRef CAS PubMed.
  2. X. Li, X. T. Wu, Q. Xu and Q. L. Zhu, Adv. Mater., 2024, 36, 2401926 CrossRef CAS PubMed.
  3. O. M. Yaghi and Z. Rong, Science, 2023, 379, 330–331 CrossRef CAS PubMed.
  4. M. Riaz, R. K. Gupta, D. Sun, M. Azam and P. Cui, Chin. J. Struct. Chem., 2024, 43, 100427 CrossRef.
  5. P. Cheng, C. Wang, Y. V. Kaneti, M. Eguchi, J. Lin, Y. Yamauchi and J. Na, Langmuir, 2020, 36, 4231–4249 CrossRef CAS PubMed.
  6. M. Riaz, D. Acharya, H. Chu, D. Sun, M. Azam and P. Cui, J. Mater. Chem. A, 2024, 12, 28541–28547 RSC.
  7. B. Chen, S. Xiang and G. Qian, Acc. Chem. Res., 2010, 43, 1115–1124 CrossRef CAS PubMed.
  8. S. Zuluaga, P. Canepa, K. Tan, Y. J. Chabal and T. Thonhauser, J. Phys.: Condens. Matter, 2014, 26, 133002 CrossRef PubMed.
  9. R. B. Getman, Y.-S. Bae, C. E. Wilmer and R. Q. Snurr, Chem. Rev., 2012, 112, 703–723 CrossRef CAS PubMed.
  10. A. H. Khan, K. Peikert, F. Hoffmann, M. Fröba and M. Bertmer, J. Phys. Chem. C, 2019, 123, 4299–4307 CrossRef CAS.
  11. Y. Xie, X. Wu, Y. Shi, Y. Peng, H. Zhou, X. Wu, J. Ma, J. Jin, Y. Pi and H. Pang, Small, 2024, 20, 2305548 CrossRef CAS PubMed.
  12. P. Yang, F. Mao, Y. Li, Q. Zhuang and J. Gu, Chem. – Eur. J., 2018, 24, 2962–2970 CrossRef CAS PubMed.
  13. Z. Xue, J. J. Zheng, Y. Nishiyama, M. S. Yao, Y. Aoyama, Z. Fan, P. Wang, T. Kajiwara, Y. Kubota and S. Horike, Angew. Chem., Int. Ed., 2023, 62, e202215234 CrossRef CAS PubMed.
  14. X. H. Li, Y. W. Liu, S. M. Liu, S. Wang, L. Xu, Z. Zhang, F. Luo, Y. Lu and S. X. Liu, J. Mater. Chem. A, 2018, 6, 4678–4685 RSC.
  15. L. Feng, K. Y. Wang, X. L. Lv, T. H. Yan and H. C. Zhou, Natl. Sci. Rev., 2020, 7, 1743–1758 CrossRef CAS PubMed.
  16. S. Yu, J. Dong, H. Wang, S. Li, H. Zhu and T. Yang, J. Mater. Chem. A, 2022, 10, 25453–25462 RSC.
  17. K. Kim, P. G. Choi, T. Itoh and Y. Masuda, Adv. Mater. Interfaces, 2021, 8, 2100283 CrossRef CAS.
  18. N. L. Torad, B. Ding, W. A. El-Said, D. A. El-Hady, W. Alshitari, J. Na, Y. Yamauchi and X. Zhang, Carbon, 2020, 168, 55–64 CrossRef CAS.
  19. X. Liu, L. Zhang and J. Wang, J. Materiomics, 2021, 7, 440–459 CrossRef.
  20. W. Yan, H. Xu, M. Ling, S. Zhou, T. Qiu, Y. Deng, Z. Zhao and E. Zhang, ACS Sens., 2021, 6, 2613–2621 CrossRef CAS PubMed.
  21. D. Degler, U. Weimar and N. Barsan, ACS Sens., 2019, 4, 2228–2249 CrossRef CAS PubMed.
  22. J. M. Walker, S. A. Akbar and P. A. Morris, Sens. Actuators, B, 2019, 286, 624–640 CrossRef CAS.
  23. D. R. Miller, S. A. Akbar and P. A. Morris, Sens. Actuators, B, 2014, 204, 250–272 CrossRef CAS.
  24. A. Mahmood, W. Guo, H. Tabassum and R. Zou, Adv. Energy Mater., 2016, 6, 1600423 CrossRef.
  25. L. Xiao, Z. Wang and J. Guan, Coord. Chem. Rev., 2022, 472, 214777 CrossRef CAS.
  26. S. Sun, Y. Tang, C. Wu and C. Wan, Anal. Chim. Acta, 2020, 1107, 55–62 CrossRef CAS PubMed.
  27. G. Zhuang, Q. Fang, J. Wei, C. Yang, M. Chen, Z. Lyu, Z. Zhuang and Y. Yu, ACS Appl. Mater. Interfaces, 2021, 13, 9804–9813 CrossRef CAS PubMed.
  28. Q. Xiong, Y. Chen, D. Yang, K. Wang, Y. Wang, J. Yang, L. Li and J. Li, Mater. Chem. Front., 2022, 6, 2944–2967 RSC.
  29. C. Wang, H. Zhang, Y. Wang, J. Wu, K. O. Kirlikovali, P. Li, Y. Zhou and O. K. Farha, Small, 2023, 19, 2206116 CrossRef CAS PubMed.
  30. L. Jiao, J. Y. R. Seow, W. S. Skinner, Z. U. Wang and H. L. Jiang, Mater. Today, 2019, 27, 43–68 CrossRef CAS.
  31. G. Cai, P. Yan, L. Zhang, H. C. Zhou and H. L. Jiang, Chem. Rev., 2021, 121, 12278–12326 CrossRef CAS PubMed.
  32. C. He, J. Liang, Y. H. Zou, J. D. Yi, Y. B. Huang and R. Cao, Natl. Sci. Rev., 2022, 9, nwab157 CrossRef CAS PubMed.
  33. X. Zhai, J. Han, L. Shao, Y. Fu and J. Chen, Inorg. Chem., 2022, 61, 8043–8052 CrossRef CAS PubMed.
  34. Y. Yao, X. Zhao, G. Chang, X. Yang and B. Chen, Small Struct., 2023, 4, 2200187 CrossRef CAS.
  35. D. M. Kabtamu, Y. N. Wu and F. Li, J. Hazard. Mater., 2020, 397, 122765 CrossRef CAS PubMed.
  36. L. Feng, J. L. Li, G. S. Day, X. L. Lv and H. C. Zhou, Chem, 2019, 5, 1265–1274 CAS.
  37. Y. Li, H. Chen, H. Zhang, Z. Xiong, L. Chen, J. Zhang, S. Xiang and Z. Zhang, Cryst. Growth Des., 2022, 22, 1521–1527 CrossRef CAS.
  38. M. K. Albolkany, C. Liu, Y. Wang, C. H. Chen, C. Zhu, X. Chen and B. Liu, Angew. Chem., Int. Ed., 2021, 60, 14601–14608 CrossRef CAS PubMed.
  39. X. Zhai, T. Cao, X. Lu, N. Gao, L. Li, F. Liu, Y. Fu and W. Qi, Sci. China Mater., 2022, 65, 3062–3068 CrossRef CAS.
  40. D. Mao, G. Huang, L. Wu, Z. Hu, Y. Y. Lou, W. D. Wu and Z. Wu, Adv. Funct. Mater., 2023, 33, 2303958 CrossRef CAS.
  41. J. W. Liu, S. Y. Lv, Y. N. Gong, X. L. Lin, J. H. Mei, D. C. Zhong and T. B. Lu, Inorg. Chem., 2023, 62, 11611–11617 CrossRef CAS PubMed.
  42. C. C. Hou, Y. Wang, L. Zou, M. Wang, H. Liu, Z. Liu, H. F. Wang, C. Li and Q. Xu, Adv. Mater., 2021, 33, 2101698 CrossRef CAS PubMed.
  43. X. Chen, W. Cai, L. Wang and B. Wang, J. Am. Chem. Soc., 2024, 146, 23138–23145 CrossRef CAS PubMed.
  44. J. Koo, I. C. Hwang, X. Yu, S. Saha, Y. Kim and K. Kim, Chem. Sci., 2017, 8, 6799–6803 RSC.
  45. L. Wu, Y. Li, Z. Fu and B. L. Su, Natl. Sci. Rev., 2020, 7, 1667–1701 CrossRef CAS PubMed.
  46. J. Zhao, H. Li, C. Li, Q. Zhang, J. Sun, X. Wang, J. Guo, L. Xie, J. Xie and B. He, Nano Energy, 2018, 45, 420–431 CrossRef CAS.
  47. K. Wang, S. Pei, Z. He, L. A. Huang, S. Zhu, J. Guo, H. Shao and J. Wang, Chem. Eng. J., 2019, 356, 272–281 CrossRef CAS.
  48. J. Caro, Zeolites and zeolite-like materials, 2016, pp. 283–307 Search PubMed.
  49. H. Ohara, S. Yamamoto, D. Kuzuhara, T. Koganezawa, H. Oikawa and M. Mitsuishi, ACS Appl. Mater. Interfaces, 2020, 12, 50784–50792 CrossRef CAS PubMed.
  50. W. Yao, A. Hu, J. Ding, N. Wang, Z. Qin, X. Yang, K. Shen, L. Chen and Y. Li, Adv. Mater., 2023, 35, 2301894 CrossRef CAS PubMed.
  51. S. Jeong, Y. Sim, J. K. Kim, S. Shin, J. Lim, J. Seong, S. Lee, D. Moon, S. B. Baek and C. U. Kim, Small, 2022, 18, 2107006 CrossRef CAS PubMed.
  52. M. Liu and Z. M. Hudson, Adv. Funct. Mater., 2023, 33, 2214262 CrossRef CAS.
  53. M. Jia, L. Mai, Z. Li and W. Li, Nanoscale, 2020, 12, 14171–14179 RSC.
  54. H. Li, X. Lu, Q. Lu, Y. Liu, X. Cao, Y. Lu, X. He, K. Chen, P. Ouyang and W. Tan, Chem. Commun., 2020, 56, 4724–4727 RSC.
  55. S. Li, W. Han, Q. F. An, K. T. Yong and M. J. Yin, Adv. Funct. Mater., 2023, 33, 2303447 CrossRef CAS.
  56. T. Wang, H. Zhu, Q. Zeng and D. Liu, Adv. Mater. Interfaces, 2019, 6, 1900423 CrossRef.
  57. J. Li, P. M. Bhatt, J. Li, M. Eddaoudi and Y. Liu, Adv. Mater., 2020, 32, 2002563 CrossRef CAS PubMed.
  58. S. Q. Wang, X. Gu, X. Wang, X. Y. Zhang, X. Y. Dao, X. M. Cheng, J. Ma and W. Y. Sun, Chem. Eng. J., 2022, 429, 132157 CrossRef CAS.
  59. M. Hubab and M. A. Al-Ghouti, Biotechnol. Rep., 2024, e00837 CrossRef CAS PubMed.
  60. X. Wang, L. Tian, F. Tao, M. Liu, S. Jin and Z. Liu, Dalton Trans., 2023, 52, 10222–10230 RSC.
  61. L. Luo, W. S. Lo, X. Si, H. Li, Y. Wu, Y. An, Q. Zhu, L. Y. Chou, T. Li and C. K. Tsung, J. Am. Chem. Soc., 2019, 141, 20365–20370 CrossRef CAS PubMed.
  62. L. Sun, Y. Yuan, F. Wang, Y. Zhao, W. Zhan and X. Han, Nano Energy, 2020, 74, 104909 CrossRef CAS.
  63. W. Sun, J. Liu, X. Zha, G. Sun and Y. Wang, J. Colloid Interface Sci., 2024, 654, 1–12 CrossRef CAS PubMed.
  64. Y. Chen, Y. Bai, L. Meng, W. Zhang, J. Xia, Z. Xu, R. Sun, Y. Lv and T. Liu, Chem. Eng. J., 2022, 437, 135289 CrossRef CAS.
  65. H. Dong, L. Li and C. Li, Chem. Sci., 2023, 14, 8507–8513 RSC.
  66. J. Zhou, Y. Dou, X. Q. Wu, A. Zhou, L. Shu and J. R. Li, Small, 2020, 16, 1906564 CrossRef CAS PubMed.
  67. Z. Liu, H. Lv, S. Li, Y. Sun, X. Chen and Y. Xu, J. Mater. Chem. A, 2024, 12, 6318–6328 RSC.
  68. M. Zhang, Y. Qin, F. Zhang, Y. Feng, S. N. Ozer, W. Sun, Y. Zhao and Z. Xu, Chem. Eng. J., 2024, 488, 150867 CrossRef CAS.
  69. C. H. Zhang, B. X. Zhou, X. Lin, J. X. Wu, L. H. Wu, S. Cai, J. Fan, W. G. Zhang, Y. Yan and S. R. Zheng, Inorg. Chem. Front., 2024, 11, 769–778 RSC.
  70. F. Fan, Z. Zhang, J. Guo, L. Zhang, X. Zhang, T. Wang and Y. Fu, Inorg. Chem., 2023, 62, 9019–9024 CrossRef CAS PubMed.
  71. Z. Zhang, Y. Tao, H. Tian, Q. Yue, S. Liu, Y. Liu, X. Li, Y. Lu, Z. Sun and E. Kraka, Chem. Mater., 2020, 32, 5550–5557 CrossRef CAS.
  72. J. Cheng, H. Zhang, H. Wang, Z. Huang, H. Raza, C. Hou, G. Zheng, D. Zhang, Q. Zheng and R. Che, Adv. Funct. Mater., 2022, 32, 2201129 CrossRef CAS.
  73. Y. Takashima, N. Tanabe, S. Tanaka, T. Tsuruoka and K. Akamatsu, Cryst. Growth Des., 2024, 24, 1766–1773 CrossRef CAS.
  74. S. Krause, F. S. Reuter, S. Ehrling, V. Bon, I. Senkovska, S. Kaskel and E. Brunner, Chem. Mater., 2020, 32, 4641–4650 CrossRef CAS PubMed.
  75. X. Wang, G. Fan, S. Guo, R. Gao, Y. Guo, C. Han, Y. Gao, J. Zhang, X. Gu and L. Wu, Angew. Chem., Int. Ed., 2024, 63, e202404258 CrossRef CAS PubMed.
  76. K. Y. Wang, L. Feng, T. H. Yan, S. Wu, E. A. Joseph and H. C. Zhou, Angew. Chem., Int. Ed., 2020, 132, 11445–11450 CrossRef.
  77. X. Yang, S. Wang, Y. Denis and A. L. Rogach, Nano Energy, 2019, 58, 392–398 CrossRef CAS.
  78. Y. Feng and J. Yao, Coord. Chem. Rev., 2022, 470, 214699 CrossRef CAS.
  79. Q. Chen, M. Yao, Y. Zhou, Y. Sun, G. Zhang and H. Pang, Coord. Chem. Rev., 2024, 517, 216016 CrossRef CAS.
  80. F. Parsapour, M. Moradi and A. Bahadoran, Adv. Colloid Interface Sci., 2023, 313, 102865 CrossRef CAS PubMed.
  81. X. F. Lu, B. Y. Xia, S. Q. Zang and X. W. Lou, Angew. Chem., Int. Ed., 2020, 132, 4662–4678 CrossRef.
  82. L. Sun, M. G. Campbell and M. Dinca, Angew. Chem., Int. Ed., 2016, 55, 3566–3579 CrossRef CAS PubMed.
  83. M. Kim, R. Xin, J. Earnshaw, J. Tang, J. P. Hill, A. Ashok, A. K. Nanjundan, J. Kim, C. Young and Y. Sugahara, Nat. Protoc., 2022, 17, 2990–3027 CrossRef CAS PubMed.
  84. W. W. Zhan, Q. Kuang, J. Z. Zhou, X. J. Kong, Z. X. Xie and L. S. Zheng, J. Am. Chem. Soc., 2013, 135, 1926–1933 CrossRef CAS PubMed.
  85. P. Sindhu, K. Ananthram, A. Jain, K. Tarafder and N. Ballav, Nat. Commun., 2023, 14, 2857 CrossRef CAS PubMed.
  86. X. Ren, Z. Xu, D. Liu, Y. Li, Z. Zhang and Z. Tang, Sens. Actuators, B, 2022, 357, 131384 CrossRef CAS.
  87. Q. Yu, R. Jin, L. Zhao, T. Wang, F. Liu, X. Yan, C. Wang, P. Sun and G. Lu, ACS Sens., 2021, 6, 3451–3461 CrossRef CAS PubMed.
  88. J. He, H. Meng, Y. Xu and L. Feng, Sens. Actuators, B, 2024, 418, 136336 CrossRef CAS.
  89. F. Saleki, A. Mohammadi, S. E. Moosavifard, A. Hafizi and M. R. Rahimpour, J. Colloid Interface Sci., 2019, 556, 83–91 CrossRef CAS PubMed.
  90. Z. Yu, Y. Bai, Y. Liu, S. Zhang, D. Chen, N. Zhang and K. Sun, ACS Appl. Mater. Interfaces, 2017, 9, 31777–31785 CrossRef CAS PubMed.
  91. J. Li, D. Yan, S. Hou, T. Lu, Y. Yao, D. H. Chua and L. Pan, Chem. Eng. J., 2018, 335, 579–589 CrossRef CAS.
  92. Y. Zhao, S. Wang, X. Zhai, L. Shao, X. Bai, Y. Liu, T. Wang, Y. Li, L. Zhang and F. Fan, ACS Appl. Mater. Interfaces, 2021, 13, 9206–9215 CrossRef CAS PubMed.
  93. X. Chen, Z. Liu, S. Li, Y. Sun, Y. Zhang and Y. Xu, Sens. Actuators, B, 2024, 418, 136241 CrossRef CAS.
  94. C. Chen, Y. Tuo, Q. Lu, H. Lu, S. Zhang, Y. Zhou, J. Zhang, Z. Liu, Z. Kang and X. Feng, Appl. Catal., B, 2021, 287, 119953 CrossRef CAS.
  95. X. Yang, F. Wang, Z. Jing, M. Chen, B. Wang, L. Wang, G. Qu, Y. Kong and L. Xu, Small, 2023, 19, 2301985 CrossRef CAS PubMed.
  96. Z. Lv, H. Zhang, C. Liu, S. Li, J. Song and J. He, Adv. Sci., 2024, 11, 2306678 CrossRef CAS PubMed.
  97. C. A. Etogo, H. Huang, H. Hong, G. Liu and L. Zhang, Energy Storage Mater., 2020, 24, 167–176 CrossRef.
  98. L. Sun, Y. Liu, M. Yan, Q. Yang, X. Liu and W. Shi, Chem. Eng. J., 2022, 431, 133472 CrossRef CAS.
  99. W. Li, D. Wang, Z. Gong, Z. Yin, X. Guo, J. Liu, C. Mao, Z. Zhang and G. Li, ACS Nano, 2020, 14, 16046–16056 CrossRef CAS PubMed.
  100. Y. Wang, S. Wang, S. L. Zhang and X. W. Lou, Angew. Chem., Int. Ed., 2020, 59, 11918–11922 CrossRef CAS PubMed.
  101. H. Yan, Y. Pan, X. Liao, Y. Zhu, R. Huang and C. Pan, Appl. Surf. Sci., 2023, 607, 155009 CrossRef CAS.
  102. M. S. Balogun, Y. Huang, W. Qiu, H. Yang, H. Ji and Y. Tong, Mater. Today, 2017, 20, 425–451 CrossRef CAS.
  103. J. Xie and Y. Xie, Chem. – Eur. J., 2016, 22, 3588–3598 CrossRef CAS PubMed.
  104. Y. Zhong, X. Xia, F. Shi, J. Zhan, J. Tu and H. J. Fan, Adv. Sci., 2016, 3, 1500286 CrossRef PubMed.
  105. Q. Luo, C. Lu, L. Liu and M. Zhu, Green Energy Environ., 2023, 8, 406–437 CrossRef CAS.
  106. Z. Cheng, A. Saad, H. Guo, C. Wang, S. Liu, T. Thomas and M. Yang, J. Alloys Compd., 2020, 838, 155375 CrossRef CAS.
  107. Z. Chen, Y. Ha, Y. Liu, H. Wang, H. Yang, H. Xu, Y. Li and R. Wu, ACS Appl. Mater. Interfaces, 2018, 10, 7134–7144 CrossRef CAS PubMed.
  108. X. Wang, X. Han, R. Du, C. Xing, X. Qi, Z. Liang, P. Guardia, J. Arbiol, A. Cabot and J. Li, ACS Appl. Mater. Interfaces, 2022, 14, 41924–41933 CrossRef CAS PubMed.
  109. L. Ma, Y. Wang, Z. Wang, J. Wang, Y. Cheng, J. Wu, B. Peng, J. Xu, W. Zhang and Z. Jin, ACS Nano, 2023, 17, 11527–11536 CrossRef CAS PubMed.
  110. A. Jrondi, G. Buvat, F. D. L. Pena, M. Marinova, M. Huvé, T. Brousse, P. Roussel and C. Lethien, Adv. Energy Mater., 2023, 13, 2203462 CrossRef CAS.
  111. S. Li, Z. Zhuang, L. Xia, J. Zhu, Z. Liu, R. He, W. Luo, W. Huang, C. Shi and Y. Zhao, Sci. China Mater., 2023, 66, 160–168 CrossRef CAS.
  112. S. Kim, S. Wu, R. Jian, G. Xiong and T. Luo, ACS Appl. Mater. Interfaces, 2023, 15, 40606–40613 CrossRef CAS PubMed.
  113. C. Li, D. Li, S. Zhang, L. Ma, L. Zhang, J. Zhang and C. Gong, Nano-Micro Lett., 2024, 16, 168 CrossRef CAS PubMed.
  114. Y. Liu, J. Xu, S. Lu and Y. Xiang, Small, 2023, 19, 2300943 CrossRef CAS PubMed.
  115. D. Tang, C. Zhang, H. Zhan, W. Huang, Z. Ding, D. Chen and G. Cui, Coatings, 2023, 13, 1708 CrossRef CAS.
  116. S. Wang, H. Pan, Y. Wang, H. Tang and H. Zhang, Small Struct., 2024, 5, 2400031 CrossRef CAS.
  117. S. Wang, F. Gong, Q. Zhou, Y. Xie, H. Li, M. Li, E. Fu, P. Yang, Y. Jing and R. Xiao, Appl. Catal., B, 2023, 339, 123134 CrossRef CAS.
  118. Y. Yang, R. Zeng, Y. Xiong, F. J. DiSalvo and H. c D. Abruña, J. Am. Chem. Soc., 2019, 141, 19241–19245 CrossRef CAS PubMed.
  119. Y. Zhang, B. Ouyang, J. Xu, G. Jia, S. Chen, R. S. Rawat and H. J. Fan, Angew. Chem., Int. Ed., 2016, 128, 8812–8816 CrossRef.
  120. Y. Sun, K. Mao, Q. Shen, L. Zhao, C. Shi, X. Li, Y. Gao, C. Li, K. Xu and Y. Xie, Adv. Funct. Mater., 2022, 32, 2109792 CrossRef CAS.
  121. M. Shao, C. Li, T. Li, H. Zhao, W. Yu, R. Wang, J. Zhang and L. Yin, Adv. Funct. Mater., 2020, 30, 2006561 CrossRef CAS.
  122. H. Tong, C. Wang, J. Lu, S. Chen, K. Yang, M. Huang, Q. Yuan and Q. Chen, Small, 2020, 16, 2002771 CrossRef CAS PubMed.
  123. F. Zhang, S. Yin, Y. Chen, Q. Zheng, L. Wang and W. Jiang, Chem. Eng. J., 2022, 433, 133586 CrossRef CAS.
  124. R. A. Maia, B. T. Louis, W. Gao and Q. Wang, React. Chem. Eng., 2021, 6, 1118–1133 RSC.
  125. M. Gheytanzadeh, A. Baghban, S. Habibzadeh, A. Esmaeili, O. Abida, A. Mohaddespour and M. T. Munir, Sci. Rep., 2021, 11, 15710 CrossRef CAS PubMed.
  126. Z. Liu, H. Lv, Y. Zhang, J. W. He, L. Han, S. Li, L. Yang and Y. Xu, ACS Sens., 2024, 9, 3641–3651 CrossRef CAS PubMed.
  127. C. Z. Wang, J. Chen, Q. H. Li, G. E. Wang, X. L. Ye, J. Lv and G. Xu, Angew. Chem., Int. Ed., 2023, 135, e202302996 CrossRef.
  128. A. Hierlemann and R. Gutierrez-Osuna, Chem. Rev., 2008, 108, 563–613 CrossRef CAS PubMed.
  129. D. Y. Nadargi, A. Umar, J. D. Nadargi, S. A. Lokare, S. Akbar, I. S. Mulla, S. S. Suryavanshi, N. L. Bhandari and M. G. Chaskar, J. Mater. Sci., 2023, 58, 559–582 CrossRef CAS.
  130. S. J. Park, Y. K. Moon, S. W. Park, S. M. Lee, T. H. Kim, S. Y. Kim, J. H. Lee and Y. M. Jo, ACS Appl. Mater. Interfaces, 2023, 15, 7102–7111 CrossRef CAS PubMed.
  131. H. Lim, H. Kwon, H. Kang, J. E. Jang and H. J. Kwon, Nano-Micro Lett., 2024, 16, 113 CrossRef CAS PubMed.
  132. J. Xian, J. Li, W. Wang, J. Zhu, P. Li, C. M. Leung, M. Zeng, X. Lu, X. Gao and J. M. Liu, Appl. Surf. Sci., 2023, 614, 156175 CrossRef CAS.
  133. C. Park, H. Shin, M. Jeon, S. H. Cho, J. Kim and I. D. Kim, ACS Nano, 2024, 18, 26066–26075 CAS.
  134. Y. Wang, Z. Fan, P. Qian, T. Ala-Nissila and M. A. Caro, Chem. Mater., 2022, 34, 617–628 CrossRef CAS.
  135. Z. Zhai, J. Wang, Y. Sun, X. Hao, B. Niu, H. Xie and C. Li, Appl. Surf. Sci., 2023, 613, 155772 CrossRef CAS.
  136. A. Dsouza, C. Constantinidou, T. N. Arvanitis, D. M. Haddleton, J. r m Charmet and R. A. Hand, ACS Appl. Mater. Interfaces, 2022, 14, 47323–47344 CrossRef CAS PubMed.
  137. L. Huang, W. Li, H. Sun, J. Zhang, B. Wang, Q. Lu, T. Wang, X. Liang, F. Liu and P. Sun, Sens. Actuators, B, 2024, 399, 134808 CrossRef CAS.
  138. B. Wang, H. Li, H. Tan, Y. Gu, L. Chen, L. Ji, Z. Sun, Q. Sun, S. Ding and D. W. Zhang, ACS Appl. Mater. Interfaces, 2022, 14, 42356–42364 CrossRef CAS PubMed.

This journal is © The Royal Society of Chemistry 2025
Click here to see how this site uses Cookies. View our privacy policy here.