Nanoscale-localized multiplexed biological activation of field effect transistors for biosensing applications

Abstract

The rise in antibiotic-resistant pathogens, highly infectious viruses, and chronic diseases has prompted the search for rapid and versatile medical tests that can be performed by the patient. Field-effect transistor (FET)-based electronic biosensing platforms are particularly attractive due to their sensitivity, fast turn-around time, potential for parallel detection of multiple pathogens, and compatibility with semiconductor manufacturing. However, an unmet critical need is a scalable, site-selective multiplexed biofunctionalization method with nanoscale precision for immobilizing different types of pathogen-specific bioreceptors on individual FETs, preventing parallel detection of multiple targets. Here, we propose a paradigm shift in FET biofunctionalization using thermal scanning probe lithography (tSPL) with a thermochemically sensitive polymer. This polymer can be spin-coated on fully-fabricated FET chips, making this approach applicable to any FET sensor material and technology. Crucially, we demonstrate the spatially selective multiplexed functionalization capability of this method by immobilizing different types of bioreceptors at prescribed locations on a chip with sub-20 nm resolution, paving the way for massively parallel FET detection of multiple pathogens. Antibody- and aptamer-modified graphene FET sensors are then realized, achieving ultra-sensitive detection of a minimum measured concentrations of 3 aM of SARS-CoV-2 spike proteins and 10 human SARS-CoV-2 infectious live virus particles per ml, and selectivity against human influenza A (H1N1) live virus.

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Introduction

A variety of global health threats, such as highly infectious viruses, chronic diseases, and increasing prevalence of antibiotic-resistant pathogens, require rapid and versatile tests which can be performed by the patient. Field-effect transistors (FETs) configured as biosensors serve as a suitable platform, compatible with modern semiconductor manufacturing, for label-free rapid sensing by converting interactions between target analytes and surfaces into real-time electrical signals.^1–5

Furthermore, the detection limits of FET-based sensors have been pushed to ultralow concentrations (i.e., femto-molar or less) by adapting nanoscale materials such as nanowires,^6,7 In₂O₃,⁸ and graphene.^9–11 The progress in this direction promises new applications for FET-based sensor technologies in drug discovery^12,13 and clinical diagnostics.^14–17

Despite continuous progress, the application of FET-based sensors for highly parallel detection of multiple distinct pathogens or biomarkers remains elusive. At present, functionalization of FET biosensors commonly involves the drop casting method without any or limited spatial selectivity, which must be specialized for a given FET material. Therefore an unmet critical need is a FET material independent and scalable surface chemistry fabrication strategy that can allow modification of each FET on a chip on-demand with distinct pathogen/biomarker-specific bioreceptors, such as antibodies^18–20 and aptamers.^8,21,22 Overcoming this challenge will enable portable and wearable rapid diagnostic tests with unprecedented capabilities.

Several key limitations of existing surface functionalization strategies present barriers to realizing a highly parallel multiplexed FET sensor chip. A primary limitation is the lack of a scalable spatially selective methodology that provides nanoscale precision. Indeed, significant research is ongoing to implement multiplexed FET biosensors, highlighting the need for site-selective functionalization. Recent examples include electrografting-enabled site-selective functionalization of graphene FETs,²³ application of bioactive hydrogel as local gates on graphene FETs,²⁴ and implementation of physical macroscopic barriers for separating FETs^8,10,25,26 (see ESI Table 1† for a review). Despite progress on site-selective functionalization, no methodology yet offers scalable biochemical multiplexing for biosensing (i.e., several different bioreceptors on different FETs) and nanoscale precision in modifying the surface chemistry of the FET sensors. Modern semiconductor manufacturing can integrate billions of sub-100 nm size FETs into functional microchip products. Therefore, a paradigm shift in biofunctionalization that enables scalable site-selective multiplexed chemical modifications with nanoscale precision has the potential to transform modern chips into advanced sensing platforms by configuring each individual nanoscale FET into a distinct pathogen/biomarker-specific biosensor.

Surface functionalization with nanoscale precision capability could significantly enhance the robustness, reproducibility, and uniformity of the functionalization outcome across an array of FETs as well as among different chips. Existing functionalization methodologies are largely vulnerable to microscopic and nanoscopic surface non-idealities such as contaminations and variations in defect species of the surface.

Another limitation of existing functionalization approaches pertains to the development of surface chemistry processes that are FET-material independent. For instance, attaching a given antibody or aptamer to a graphene film will involve different processing steps compared to an oxide film. Functionalizing graphene requires, for example, creating either ester or vinyl sulfone groups on the surface,²⁷ which react with the primary amine groups of the receptor-antibodies. On the other hand, a different approach is needed for functionalizing In₂O₃ FETs sensors with aptamers, involving the covalent modification of In₂O₃ with dopamine or serotonin aptamers using silane chemistry.⁸ Therefore, as FET sensor technologies evolve, for example to achieve higher sensitivity or improved manufacturability, their adaptation into a biosensing platform may require development of new surface chemistry processes. Therefore, a FET material independent chemical modification process facilitates the adaptation of different FET technologies.

To address the above-mentioned limitations, here, we introduce a scalable, FET material independent functionalization strategy that permit local bioreceptor functionalization of individual FETs on the same chip with nanoscale spatial precision. Our strategy involves the use of thermal scanning probe lithography (tSPL) with a thermochemically sensitive polymer. This tSPL method is capable of chemically patterning a polymer-coated chip surface at prescribed locations, enabling multiplexed functionalization of different bioreceptors from antibodies to aptamers, at sub-20 nm resolution and 200 nm pitch, a distance comparable to the pitch of modern FETs array in CMOS chips. In a typical FET biosensor, the trapping of a target analyte by a specific bioreceptor results in the change of electronic charge at the channel region, generating a measurable electronic signal. We show that the capture of the target analytes at the surface of the polymer-coated FET sensors in our experiments equally gives rise to detectable electronic signals due to the effective capacitive behavior of the polymer film. Furthermore, patterning individual FETs allows for in situ differential sensing, a key ingredient to ensure signal fidelity. The feasibility of this platform is established through the detection of a single pathogen type using both antibody- and aptamer-modified FET sensors. Specifically, the tSPL-functionalized FET sensors achieve an ultra-sensitive detection of a minimum measured concentration of 3 aM of SARS-CoV-2 spike proteins and 10 human SARS-CoV-2 infectious virus particles per ml, and selectivity against human influenza A (H1N1) live virus.

Experimental methods

Graphene FET devices fabrication

The graphene FETs (gFETs) are fabricated using a four-stage process. The first stage involves the preparation of the substrate and graphene material. The substrate is prepared by covering SiO₂-coated silicon substrates with a 10 nm aluminum oxide (Al₂O₃) film grown by atomic layer deposition at 270 °C, followed by the densification of Al₂O₃ at 500 °C for 1 hour in an oxygen ambient. Commercially available single-layer graphene films (ACS Material), grown by chemical vapor deposition (CVD) on copper metal substrates, are then transferred on the Al₂O₃-coated substrates using a standard PMMA-based transfer method²⁸ (details in ESI Note 3†). In the second stage, graphene islands constituting the channel region of FETs are patterned using a combination of electron beam lithography (EBL) and plasma cleaning (details in ESI Note 3†). In the third stage, fabrication of gFET array is complete through the formation of source and drain metal electrodes using a combination of EBL patterning, e-beam evaporation of 5 nm Cr/20 nm Ti/25 nm Au metal stack, and lift-off in acetone, followed by covering the metal electrodes with an EBL-patterned SU8 isolation film. Stable connections are made from the contact pads to external test circuit using spring loaded pogo pins. The contact pads are designed to lie outside the microfluidic chamber during electrical measurements. More details about gFET fabrication can be found in Deshmukh et al. (2024).²⁹

Polymer synthesis

A solution of I-3-(4-(3-methoxy-3-oxoprop-1-en-1-yl)phenoxy)propyl methacrylate (Mcoum), 2-((((tetrahydro-2H-pyran-2-yl)oxy)carbonyl)amino)ethyl methacrylate (Mcarb), and azobisisobutyronitrile (AIBN) is prepared in THF in a glovebox (Mcoum : M-carb : AIBN = 40 : 160 : 1). This solution is stirred at 70 °C in the glovebox for 16 hours, after which, the solution is exposed to air and purified by adding dichloromethane, precipitating from cold hexanes, filtering, and drying under vacuum to isolate poly((tetrahydropyran-2-yl-N-(2-methacryloxyethyl)carbamate)-co-(methyl-4-(3-methacryloyloxypropoxy)cinnamate)) (PMCC) as a white solid. More information is reported in ref. 30–34. The purity is determined via¹H nuclear magnetic resonance spectroscopy.

Two-polymer resist stack

The two-polymer resist stack is spin coated on the desired chip in a two-step process. First, a PMCC film (approximately 70 nm thick) is spin-coated on the chip. The PMCC film is obtained by using a 15 mg ml⁻¹ solution of PMCC dissolved in cyclohexanone.^33,35 The chips are spun at 1000 RPM for 5 seconds and 1500 RPM for 15 seconds to disperse the PMCC solution, then 4000 RPM for 30 seconds to evenly apply a ∼70 nm thin film to the substrate. The chips are then treated with 302 nm UV light to crosslink the polymer and increase adhesion to the substrate. Second, a PPA film (10–20 nm thick) is spin coated on PMCC. PMCC coated chips are spin-coated with a solution of 0.5% PPA in anisole to cover the PMCC surface. The spin-coating of PPA is performed at 6000 RPM for 30 seconds.

Thermal scanning probe lithography and microscopy

Patterning of the PMCC/PPA polymeric stack is performed using a commercial tSPL system (NanoFrazor, Heidelberg Instruments, Germany), which utilizes a heated silicon probe.³⁶ For patterning, the probe on the head of the thermal cantilever is heated up by a resistive micron-heater. The probe works as a separate thermal reading sensor for in situ topography thermal imaging when the micro-heater is turned off. This is a key feature that allows imaging of the FETs underneath the polymer resist, permitting the local functionalization without the need of markers. During the patterning, the thermal reading sensor probes the topography of the patterned structure right after each patterning line when retracing back in contact mode, which leads to the simultaneous patterning and imaging capability of the NanoFrazor system as well as a closed feedback loop correction.^32,33,35 The probe temperature is automatically calibrated through the system software according to the current–voltage characteristics of the Si tip.³⁷ The tSPL patterning parameters (such as write temperature, dwell time, and load) are adjusted to achieve the amine deprotection on the PMCC surface and PPA removal, while controlling the depth of the lithographic indentation. Details on the calibration of the optimal tSPL writing temperature, load and dwell time are reported in the ESI Note 5.†

Nanoscale local biochemical functionalization

The biotin–streptavidin interaction is used as the bio-conjugation strategy to attach ad-hoc bioreceptors in designated regions of chips. Following the tSPL patterning to expose surface amine (–NH₂) groups, the chip is covered with a solution of 100 nM NHS–biotin in dimethyl sulfoxide (DMSO) and incubated for 1 hour. The NHS ester groups react with the surface NH₂ groups, conjugating the biotin to the surface. The chip is then washed with a 1× phosphate buffered saline solution (PBS) and DI–H₂O to remove any non-reacted material, and dried using compressed N₂ gas. The chip is then functionalized with 100 nM streptavidin in 1× PBS for 30 min. Following this step, the sample is functionalized with the desired biotinylated bioreceptor: 100 nM anti-SARS-CoV-2 antibody in 1× PBS, 100 nM anti-SARS-CoV-2 aptamer in DI water or 100 nM Influenza A anti-hemagglutinin aptamer in DI water. The above concentrations and functionalization times were chosen to ensure saturation of available sites, preventing interference with multiple rounds of functionalization.

All solvents are acquired from Sigma-Aldritch, unless stated otherwise. The (+)-biotin N-hydroxysuccinimide (NHS) ester, DyLight™-conjugated esters, streptavidin are acquired from ThermoFisher Scientific. Biotinylated Anti-SARS-CoV-2 Spike RBD Neutralizing Antibody (S1N-VM226), as well as SARS-CoV-2 spike proteins for detection are purchased from ACRO Biosystems. Aptamers are synthesized per order from Integrated DNA Technologies (IDT) using the following sequences from previous studies:^38,39 Anti-SARS-CoV-2 Aptamer-6C3 5′-CGCAGCAC CCAAGAAC AAGGACTG CTTAGGAT TGCGATAG GTTCGG-3′ (see Fig. S6†).³⁸ Anti-hemagglutinin (HA) aptamer-RHA-0006 (Integrated DNA Technologies, 5′-GGGTTTGG GTTGGGTT GGGTTTTT GGGTTTGG GTTGGGTT GGGAAAAA-3′, see Fig. S7†).³⁹ Aptamers are modified with biotin on the 5′ end and tagged with TYE™ 665 (Aptamer-6C3) or 6-carboxyfluorescein (Aptamer-RHA-0006) fluorescent dye on the 3′ end, formulated by Integrated DNA Technologies, Inc.^8,9 and purified using high performance liquid chromatography (HPLC).³⁸ See ESI Note 4† for further details on the functionalization, incubation process and aptamers.

Electrical measurements

The gFET chip is placed inside a custom-made microfluidic chamber with a ∼350 μl volume, (shown in ESI Fig. S8†) and the gFETs are then covered with a buffer solution. An external Ag/AgCl reference electrode is utilized as the gate electrode. The FET electrical response is continuously monitored by means of a custom-made Printed Circuit Board. This circuit converts the drain–source current into a voltage using a transimpedance amplifier, and subsequently, the output voltage is digitized with a data acquisition instrument (NI USB6353X series, National Instruments). A custom LabVIEW control interface is employed to operate these instruments. The transfer curve of the device is measured multiple times for reproducibility. The drain–source voltage (V_ds) is set to 50 mV throughout the experiments. For each measurement, 200 μl of buffer is placed in the microfluidic chamber at the start of the measurement. 20 μl of the analyte is injected at increasing concentrations. The values indicated in Fig. 3–5 are calculated values to account for dilution in the chamber.

Live virus experiments

Viral stocks have been prepared ahead of the experiments conducted in the ViroStatics facility in Alghero, Italy, within a Biosafety Level 3 Laboratory. A VERO E6 cell line (Cercopithecus aethiops, kidney) was purchased from American Type Culture Collection (ATCC) and was cultured in Dulbecco's modified Eagle's medium (DMEM, https://biowest.net/wp-content/uploads/2022/08/DMEM-High-Glucose.pdf) supplemented with 10% fetal bovine serum (FBS) (Biowest), 1% antibiotic solution penicillin/streptomycin (Biowest), 1% L-glutamine (Biowest), i.e., complete medium, at 37 °C with 5% CO₂. Human 2019-nCoV strain 2019-nCoV/Italy-INMI1, isolated in Italy (ex-China) from a sample collected on January 29, 2020, was provided by the Istituto Lazzaro Spallanzani, Rome, Italy (Archive E, “Human 2019-nCoV strain 2019-nCoV/Italy-INMI1, clade V” 2020, available online at https://www.european-virus-archive.com/virus/human-2019-ncov-strain-2019-ncovitaly-inmi1-clade-v). The virus was propagated in Vero E6 cells as described above to obtain high titer virus (>10 × 10⁶ TCID₅₀ per mL) and was stored in DMEM 2% FBS at −80° C until use. Tissue culture infectious dose (TCID₅₀) is defined as the dilution of a virus required to infect 50% of a given cell culture.

Similarly, a high titer (>10 × 10⁶ TCID₅₀ per mL) viral suspension of H1N1 (A/PR/8/34) was produced from infected cultured of MDCK (Madin-Darby canine kidney). DMEM 2% FBS was used to store the virus at −80 °C. Live virus suspensions for the gFETs experiments are prepared using a buffer containing 1 mM HEPES and 0.6 mM NaCl.

SPR experiments

Putative interactions between probes and target analytes are confirmed using a 2-Channel Surface Plasmon Resonance System (Reichert® 2SPR, Reichert Inc, NY). SPR system is equilibrated with the target buffer system and all the subsequent probes, analyte samples, and blank samples are produced with the same buffer. Biotin-conjugated aptamers (IDT Corporation, IA) and antibodies (Acro Biosystems, DE) are used as probes (100 μL injection, 100 nM) and immobilized onto streptavidin-coated gold chips (Reichert Inc). Only the left channel is functionalized with the probe while the right channel is used as a reference. Analyte interactions is assessed by flowing through (25 μL min⁻¹) solutions of target analyte samples SAR Cov-19 spike protein (Acro Biosystems) and live Covid particle (patient nasal swabs) with increasing concentrations through both channels. All experiments are run at 37 °C.

Fluorescence microscopy

Fig. 1d–f are taken using a Zeiss LSM 880 Airyscan Fast Live Cell confocal microscopy unit, Plan Apo 40×/1.2 Type W Oil objective and submersion, and the HeNe 633 nm laser line. Fig. 2b–f fluorescence imaging is done using a Nikon Ti2-E Motorized Microscope equipped with a 7-line solid state light source, CFI60 Plan Apochromat Lambda 10× and 40× lenses and ORCA-Fusion Gen-III sCMOS camera.

Fig. 1 Sub-20 nm resolution biochemical functionalization of FETs by tSPL. (a) 3D-Render of the NanoBioFET platform for FET-based multiplexed nanoscale biosensing. (b) Schematic showing the steps of fabrication in the NanoBioFET platform, from polymer deposition onto the FETs, to tSPL nanoscale activation of amine groups, and bioreceptor bioconjugation. (c) Thermal SPM topographical image of a tSPL nanoscale amine pattern fabricated in PPA/PMCC. In the inset, the depth profile of the corresponding cross section AA′, showing a FWHM of 15 nm for each sensor pixel. (d) and (e) Fluorescence microscopy image of biotinylated aptamers terminated with a red dye on a PPA/PMCC SiO₂/Si chip. Specifically, the image shows Biotinylated anti-SARS-CoV-2 aptamer. After tSPL patterning, the sample is covered with a solution of 100 nM NHS–biotin in DMSO and incubated for 1 hour. The sample is then functionalized with 100 nM streptavidin in 1× PBS for 30 min. After washing and drying, the sample is functionalized with the red-dye tagged aptamer. (f) and (g) tSPL topography (f) and friction AFM (g) images of four PPA/PMCC coated gFETs with a channel width of 1 μm, where the areas above the gFET's channel (graphene) sensors have been patterned by tSPL to remove PPA and activate amine groups on PMCC.

Fig. 2 NanoBioFET fabrication for multiplexed biofunctionalization. (a) Schematics of consecutive tSPL patterning and functionalization rounds to fabricate adjacent FETs, each functionalized with a different bioreceptor, enabling multiplexed biochemical activation. (b) Fluorescence microscopy image of four different NHS–ester terminated dyes (red, orange, sky-blue and green) attached to amine moieties patterned by tSPL on a PPA/PMCC SiO₂/Si chip. Note that negligible bleed is observed, indicating saturation of exposed amines at each functionalization round. (c) Fluorescence microscopy image of four representative graphene-based FETs functionalized with four different types of NHS–ester terminated dyes (green, sky-blue, red and orange). (d and e) Fluorescence microscopy images of two different biotinylated aptamers with terminated red and green dyes on a PPA/PMCC/SiO₂/Si chip. Specifically, the images show biotinylated anti-SARS-CoV-2 aptamer (red) and biotinylated anti-hemagglutinin (HA) aptamer (green). The image in (e) shows a two-aptamer pattern of 500 nm circles. (f) From left to right: first, in situ tSPL topographical image of a matrix of circles produced after a first round of tSPL on a PPA/PMCC/SiO₂/Si chip; second, in situ tSPL topographical image of the same area after conjugation of the surface with bioreceptor 1 (HA aptamer) using biotin/streptavidin as cross linker and after a second round of tSPL to pattern a second matrix of 20 nm dashes; third, in situ tSPL topographical image of the same area after conjugation of bioreceptor 2 (CoV-2 aptamer) using biotin/streptavidin as cross linker. The respective cross section images show the registry and robustness of multiplexed patterning and the change in depth of the patterns after functionalization due to the filling of each pattern with the NHS–biotin/streptavidin/aptamer molecules (approximately 10–15 nm).

Results and discussion

Nanoscale thermal biofunctionalization: the NanoBioFET platform

To enable a scalable, site-selective multiplexed strategy capable of locally functionalizing individual FETs at sub-100 nm resolution with desired bioreceptors (from antibodies to aptamers), and applicable to any channel material (e.g., graphene, oxides, or silicon), we use thermal scanning probe lithography (tSPL).^36,40 In our approach, tSPL uses a hot nanotip to expose amine groups with nanoscale resolution on a thermally sensitive biocompatible polymer resist,^30–34 which is spin coated on a target substrate containing fully-fabricated FETs (see Fig. 1b). This spatially selective activation process enables subsequent modification of individual or a group of FETs with a desired bioreceptor, resulting in an array of FET-based biosensors configured for simultaneously detecting various target analytes (see Fig. 1a). We name this platform NanoBioFET.

The implementation of the NanoBioFET platform begins by fabricating a FET array. As shown in Fig. 1b, we adopt monolayer graphene for realizing the FET-based sensors (see Experimental methods), due to its potential for ultrahigh sensitivity.^41,42 We then cover the fully fabricated graphene FETs (gFETs) by spin coating two thermally sensitive polymer resist films (see Experimental methods). The stack comprises a first film of about 70 nm-thick polymethacrylate–carbamate–cinnamate copolymer (PMCC),^31–33 which provides amine groups on demand in designated FET regions upon local heating by tSPL. PMCC can be locally patterned through local heat-induced deprotection of amine groups from tetrahydropyranyl carbamates in the carbamate block of PMCC^30–34 (see Experimental methods). The second film is poly(phthalaldehyde) (PPA)^36,43 which serves as a top layer resist (10–20 nm thick) to reduce non-specific binding outside the FET channel region (see ESI Note 1†).

After forming the bilayer polymer resist stack, we proceed with the localized functionalization of individual FETs with desired bioreceptors. Employing tSPL, we modify the bilayer polymer resist stack atop the channel region of each target gFET with amine groups. This process utilizes a hot nano-tip in a commercial tSPL system (see Experimental methods), which removes PPA completely above the channel region, while simultaneously applying heat to the PMCC polymer surface above the amine deprotection temperature (∼120 °C), exposing amine groups in the desired area (Fig. 1b). For differential sensing, we pattern only the FET used as a sensor, while leaving the un-patterned FET as a control device. Ensuring signal fidelity is a key challenge for commercialization of FET-based biosensors. Hence, providing a platform that allows for in situ differential sensing is a key milestone. Using standard conjugation strategies, the amine groups in the channel region can subsequentially be functionalized with ad-hoc bioreceptors such as antibodies or aptamers (see Experimental methods for details). At this point, the sensor/control FETs are ready for biodetection of a specific target, such as SARS-CoV-2 virus. As discussed later, when the FET sensor is exposed to a specific target, the target is immobilized by the bioreceptor near the polymer surface, giving rise to a change in the electronic signal of FET-based sensors.

In Fig. 1c, we demonstrate the resolution of the NanoBioFET fabrication method. Specifically, Fig. 1c shows an in situ tSPL topographical image (see Experimental methods) of an amine pattern produced by tSPL in a PPA/PMCC bilayer polymer resist stack deposited on a blank SiO₂/Si substrate (i.e., without gFETs). The pattern consists of a 10 × 10 matrix of 15 nm-diameter amine circles with 40 nm pitch, comparable to that of an advanced-node silicon FET technology. Importantly, this image is taken in situ during the tSPL patterning process, since thermal probes can also allow local nanoscale imaging (Experimental methods). This feature enables localization of target regions on a chip with nanoscale precision without requiring sophisticated and costly pattern alignment procedures.

To demonstrate the ability of the NanoBioFET fabrication method to pattern relevant biomarkers with high reproducibility and precision, Fig. 1d and e present two fluorescence optical microscopy images of one-hundred squares (with 5 μm and 500 nm sides, respectively) of biotinylated anti-SARS-CoV-2 aptamers, which have been fluorescently tagged with a red dye (see Experimental methods for details on the aptamers used here). These aptamer patterns have been produced first by exposing amine groups by tSPL on the surface of the PPA/PMCC polymer resist, and then by conjugating the amine groups to NHS–biotin, followed by streptavidin, and biotinylated aptamers (the details of the chemical functionalization steps are reported in the Experimental methods). Note that the PPA/PMCC double polymer stack in these experiments is spin-coated on a on a blank SiO₂/Si substrate (i.e., without gFETs).

In Fig. 1f and g, we show how the NanoBioFET fabrication process is implemented on a gFET array chip. For this purpose, we fabricate an array of four gFETs with a channel length of 1 μm, where each sensor FET is adjacent to a control FET. The PPA and PMCC resists are then spin-coated on the gFETs, and tSPL is used to remove PPA and pattern amine groups in the channel region of the two gFET sensors, leaving the FET controls un-patterned. In Fig. 1f and g we show, respectively, an in situ tSPL topographical image, and an ex situ friction atomic force microscopy (AFM) image of the resulting gFET sensors and controls after tSPL patterning. The graphene region underneath the polymer is indicated with a dashed red rectangle. In Fig. 1f, the tSPL topography image shows that the patterns above the channel region of the gFET sensors are at a depth of approximately 10 nm, corresponding to the thickness of the PPA film, which is sublimated during tSPL patterning. It is important to note that since tSPL allows in situ imaging of the FET underneath the dual polymer stack, we are able to locate the channel region of each FET and pattern where required without the need of markers. The AFM friction image in Fig. 1g is particularly revealing since it shows clear friction contrast in the sensor area due to the change in hydrophilicity upon the thermal deprotection of the amine moiety. This agrees with a more hydrophilic surface where the amine groups have been exposed, and the consequent presence of larger friction forces at the nanoscale due to larger capillary forces.^40,44

Biochemical multiplexing capability of the NanoBioFET platform

To fully exploit the potential of having a massive number of FET biosensors in a microchip, it is necessary to functionalize each FET with distinct bioreceptors so as to allow detection of different types of target biomolecules, such as different viruses. In Fig. 2, we demonstrate the capability of the NanoBioFET fabrication process for the site-selective attachment of distinct types of bioreceptors at different locations on a given target surface (e.g., SiO₂ and graphene here). Fig. 2a shows the concept by means of a schematic representing the steps involved in implementing the biochemical multiplexing. Initially, we spin-coat a PPA/PMCC polymer stack on a target substrate, consisting of an FET array. Then a first round of site-selective functionalization in this process, as depicted in Fig. 1b, is performed on FET-1 to attach bioreceptor-1 (red square), followed by a second round to attach bioreceptor-2 (green square) to FET-2, and so on until all FETs are functionalized up to the desired n-number of bioreceptors. Each round of site-selective functionalization in NanoBioFET platform includes: first, in situ tSPL topographical imaging of the surface to locate where the pattern needs to be made (e.g., the desired FET); second, tSPL local patterning of the polymer stack above an individual FET channel; third, a series of biochemical functionalization steps, and selective attachment of the desired bioreceptor to the target FET as described in the Experimental methods section.

In Fig. 2b we present a fluorescence optical microscopy image of biochemical patterns generated by four sequential rounds of the site-selective functionalization process as depicted in Fig. 2a. In particular, Fig. 2b shows the fluorescence of four types of NHS-esters terminated dyes (red, yellow, green and sky-blue) attached directly to the amine moieties exposed during the tSPL process on the surface of the PPA/PMCC polymer resist deposited on a blank SiO₂/Si substrate (i.e., without gFETs). Fig. 2c shows the implementation of the multiplexed chemical patterning in an array of gFETs. Specifically, the channel regions of four representative gFETs have been functionalized with four different types of NHS-esters terminated dyes (red, yellow, green, and sky-blue) attached directly to the amine moieties exposed by tSPL on the surface of a PPA/PMCC polymer resist spin-coated on a gFET chip.

Fig. 2d and e demonstrate the capability of this fabrication method to produce independent patterns of different types of bioreceptors (here aptamers) sensitive to different types of target molecules, e.g., different viruses. In particular, here we show a fluorescence image of patterns of two types of fluorescently labelled aptamers, influenza A anti-hemagglutinin (HA) aptamer tagged with a green fluorophore, and anti-SARS-CoV-2 aptamer (tagged with a red fluorophore). The patterns are created by exposing amine groups by tSPL, and subsequently by attaching NHS–ester biotin to the amine patterns. Biotin patterns are then exposed to streptavidin, and finally to the biotinylated HA aptamer (green). A second identical round of site-selective functionalization is performed to attach the biotinylated CoV-2 aptamer (red) to the desired area on the surface. The details are reported in the Experimental methods.

Fig. 2e and f demonstrate the high spatial resolution with which patterns/bits of different bioreceptors can be fabricated, demonstrating the potential of this approach for site-selective functionalization of nanoscale FETs. In particular, following the same process as in Fig. 2d and e, we produce patterns of two types of aptamers (HA and CoV-2 aptamers) on a blank SiO₂/Si substrate. The fluorescence image in Fig. 2e shows green-aptamer and red-aptamer patterns with a “bit” dimension of 500 nm. Because of the limited resolution offered by optical microscopy, we also fabricate two-aptamer circle/dash patterns with a 20 nm width and a minimum 200 nm pitch, i.e., minimum distance between circle (HA aptamer) and dash (CoV-2 aptamer) pattern centers. We then image them in situ by tSPL imaging (Fig. 2f). We perform three measurements on the PPA/PMCC surface. First, we image pattern type-circle after a first round of tSPL. Second, we functionalize pattern type-circle with NHS–biotin/streptavidin/HA aptamer and image the pattern region after a second round of tSPL to produce pattern type-dash. Third, we image the polymer surface after functionalization of pattern type-dash with NHS–biotin/streptavidin/CoV-2 aptamer. The cross-sections show the high registry and robustness of the fabrication process and the change in depth of the patterns after functionalization due to the filling of each pattern with the NHS–biotin/streptavidin/aptamer molecules (approximately 10–15 nm). The two types of patterns have been produced with different shapes to add clarity to the image and show that tSPL can also produce patterns at different depths and shape. See also ESI Fig. S9.† We remark that the same platform can be adapted to be used with different chemical bioconjugation strategies to link the biomarkers on the surface, such as click-chemistry conjugation.

Electronic sensing on site-selective functionalized gFETs

Having established the versatility and nanoscale spatial precision of the NanoBioFET fabrication strategy, we next examine its feasibility in electronic detection of target analytes. Specifically, we investigate whether the implementation of the proposed site-selective functionalization results in a successful electronic sensing of target analytes. The central hypothesis of the NanoBioFET platform is that the PMCC polymer will serve as a capacitor that will allow effective coupling between the charges due to biochemical reactions on its surface with the FET. We will test this hypothesis through sensing experiments tailored for the detection of the SARS-CoV-2 virus. This choice is motivated by the commercial availability of bioreceptors for this virus, including different antibodies and aptamers.

Fig. 3a shows the schematic illustration of an antibody-modified gFET, where the graphene channel is separated from the bioreceptor by the PMMC polymer (the blue rectangle). The sensor is solution-gated, where a fixed bias gate voltage (V_gs) is applied to the solution (300 mV in our experiments) using an external Ag/AgCl reference electrode. A small bias voltage (V_ds = 50 mV) is simultaneously applied between the source and drain electrodes, generating a current flow (I_ds) in the gFET, which is monitored in real time.

Fig. 3 Spike protein–antibody capture on the NanoBioFET platform. (a) Schematic of a gFET functionalized with SARS-CoV-2 antibody using the NanoBioFET platform. The device structure, electrical measurement setup and Debye length at 1 mM HEPES buffer are indicated. (b) Simplified capacitor circuit model of the sensing platform for detection of a charge ΔQ, demonstrating capacitive coupling through the polymer (with capacitance C_pol). Double-layer capacitance (C_DL) and quantum capacitance (C_q) are shown. (c) SPR measurement at 1 mM HEPES buffer, demonstrating successful interaction between the antibody and spike protein. (d) Transfer characteristics of the gFET device. The p-branch and n-branch are indicated. The current and voltage range used in the transient measurement in panel d is indicated by the dashed box. (e) Calibrated transient response of the antibody-modified gFET in 1 mM HEPES. Black circle and red diamond symbols denote, respectively, injections of buffer and spike protein of increasing concentrations. The measurement is split across two panels with different vertical scales. Dashed lines are a guide-to-the-eye of the measured signal. (f) Sensitivity plot of the gFET, obtained from a Hill fit to the calibrated sensor response data at different spike protein concentrations. The gray rectangle represents the limit of detection based on noise analysis (see ESI†).

Fig. 3b illustrates the simplified capacitor circuit model of the bioreceptor-modified gFET in our experiment. The conjugation of target analytes (e.g., spike protein or virus) with bioreceptors results in the change of charge (denoted as ΔQ in Fig. 3b) on the surface of the polymer. As shown in this circuit model, the PMCC capacitance (C_pol) allows the compensation of charged carriers in the graphene channel due to ΔQ, thereby resulting in a measurable change in I_ds (i.e., ΔI_ds) due to the biochemical reaction. This recorded I_ds signal can be used to quantify the concentration of target analytes through creation of a sensitivity calibration curve, as we explain later. We note that the PMCC polymer in the hydrated state (i.e., exposed to the buffer solution) provides a high capacitance (μF cm⁻² range, see ESI Fig. S12†), which is consistent with the previous reports on the significant increase in the relative permittivity of other polymers in hydrated states.⁴⁵

A key experimental challenge in FET-based biosensing is the electronic screening of charges with increasing distance from the surface, characterized by the Debye length λ_Debye, with multiple mitigation strategies proposed in the literature.^8,46–49 A common approach for overcoming this limitation is to adjust the ionic strength of the buffer environment,^46,50 thereby increasing λ_Debye. In the experiments below, we adopt a similar strategy, modifying the buffer solution and its ionic strength based on the choice of the bioreceptor (i.e., antibody or aptamer).

SARS-CoV-2 sensing using antibody-modified gFETs

All electronic sensing experiments begin by employing the fabrication and biofunctionalization protocols described in Fig. 1 and 2, which involve anchoring NHS–biotin–streptavidin chains onto the thermochemically activated amine groups on the PMCC polymer, above the channel region of the gFETs. Our initial investigations focus on the use of biotinylated antibodies as a bioreceptor, which attach to the NHS–biotin–streptavidin chains. In this configuration, detecting an electronic signal induced by the antibody–analyte interaction requires λ_Debye of at least ∼10 nm. To accommodate this requirement, we use a 1 mM HEPES buffer solution as the sensing environment (see Experimental methods).⁶ Whereas a lower ionic strength enhances λ_Debye, the reduction of ion concentration in the sensing environment may negatively affect the efficacy of the antibody–analyte interaction.

We select biotinylated anti-SARS-CoV-2 spike RBD neutralizing antibody (see Experimental methods) for these electronic sensing experiments. The feasibility of its binding affinity to SARS CoV-2 spike protein at 1 mM HEPES buffer, which provides λ_Debye = 10 nm, is validated by surface plasmon resonance (SPR) measurements (Fig. 3c). In these SPR experiments, the concentration of spike proteins is limited to a low nanomolar range, which is the typical sensitivity of this type of measurements.^51,52 Although the SPR traces for the spike protein against the antibody probe confirm affinity, they also indicate a lower response compared to typical buffers with physiological salinity levels (e.g., 1× PBS). Furthermore, the SPR data indicate a deviation from the ideal curve shape expected for the interactions, which we attribute to the low ionic strength of the buffer used. Therefore, we use the SPR data only as qualitative indication of the viability of the affinity at 1 mM HEPES. However, detailed kinetic analysis may not be reliable because the very low ionic strength causes some artifacts producing poor curve fitting to the kinetic data (see ESI Fig. S13†).

We then proceed to perform the electronic sensing measurements. In all sensing experiments, the bioreceptor-modified gFETs are placed in a microfluidic chamber (see Experimental methods). We then perform an initial screening of a gFET sensor quality by measuring its transfer characteristics (I_dsvs. V_gs) using a buffer solution gate. In Fig. 3d, we show the typical transfer characteristics of an antibody-modified gFET, obtained by sweeping the solution gate voltage, V_gs, and recording I_ds at a fixed V_ds of 50 mV. V_gs modulates the gFET charge carrier concentration and carrier type, from holes in the p-branch, to electrons in the n-branch, passing through the charge neutrality point (at V_CNP). For simplicity the data are centered around V_CNP. When an analyte is captured by the bioreceptor in the channel region, the local change in charge produces a shift of the I_dsvs. V_gs characteristics and therefore a change in I_ds is measured at fixed V_g.

We next monitor the real-time electronic response of a SARS-CoV-2 antibody-modified gFET sensor to different concentrations of spike protein. The experiment involves recording I_ds continuously in time at a fixed V_gs of 300 mV while injecting analytes at different times into the microfluidic chamber. The objective of this experiment is to quantify the sensitivity of this antibody-modified gFET and evaluate its limit of detection. In Fig. 3e, we show the corresponding transient response of the gFET. To account for device-to-device variation, we normalize the change in I_ds by the device transconductance to obtain a calibrated signal, tracking the change in V_CNP (see ESI Note 6† for more details). We monitor the transient sensor response due to injections of the spike protein (see Experimental methods for discussion on the concentrations). Upon each spike injection, we observe a strong decrease in the sensor signal that follows an apparent exponential behavior (marked with dashed exponential fits). The subsequent spike injection occurs once the sensor signal establishes a new steady-state baseline. Each of the spike protein injections generates a qualitatively similar response, with decreasing magnitude as the sensor starts to saturate.

Fig. 3f shows the sensitivity plot of the antibody-modified gFET, plotting the cumulative sensor response against its corresponding spike concentration (on a log-scale). Also included in the plot are data points from a second measurement on a different device, demonstrating reproducibility of our measurements (see ESI Fig. S10†). To evaluate the sensor limits of detection and saturation, we fit the calibrated signal response to a Hill model of the form V = V_max[A]ⁿ/(Kⁿ_d + [A]ⁿ), where V is the signal strength, saturating at value V_max, [A] is the analyte (spike protein) concentration, K_d is the equilibrium dissociation rate of the receptor–analyte pair, and n is the Hill coefficient, limited to a maximum value of 2 (for two receptor sites per antibody). We obtain an excellent fit to the data with, with the sensor response starting to saturate near 100 aM (V_max = 16 mV), and n = 1.5 indicating cooperative binding of spike proteins to antibodies. Analysis of the electronic noise in these measurements reveals a 1.8 mV_rms input-referred noise, corresponding to an estimated limit of detection of 1 aM based on the Hill fit (see ESI Note 2†). The excellent sensitivity of these gFETs, which could be further optimized in terms of electrical characteristics, reinforces the prospects of NanoBioFETs platform for site-selective functionalization of FET sensors.

CoV-2 Sensing using aptamer-modified gFETs

We next examine the versatility of the NanoBioFET platform in adapting aptamers as bioreceptors for detecting spike proteins. In recent years, aptamers have become increasingly appealing as capturing probes due to their cost-effectiveness and durability.⁸ More critically, modifying FET-based sensors with aptamers has proven to be an effective strategy in significantly relaxing the requirements on λ_Debye and, consequently, the ionic strength of the sensing environment.⁵³ Recent demonstrations have revealed the utility of aptamer-modified FET sensors in detecting analytes at physiological ionic strength,²¹ which has a λ_Debye of 0.7 nm. The sensing mechanism of an aptamer-modified FET-based sensor is attributed to the fact that the analyte-induced conformational changes of the aptamer alter the surface charge within λ_Debye, generating a detectable electronic signal. In our experiments, explained below, we demonstrate the successful electronic detection of spike proteins in buffers solutions having a λ_Debye of ∼2 nm.

We implement aptamer-modified gFETs following an identical tSPL fabrication and biofunctionalization procedure as in the experiments in Fig. 1 and 2, and we use a biotinylated anti-SARS-CoV-2 aptamer as bioreceptor (see Experimental methods for details). Before the electrical sensing experiments, we employ fluorescent microscopy to confirm the aptamer attachment in the channel region of the gFETs designated as biosensors. Indeed, the strong fluorescence in the channel region (20 × 50 μm²) of an aptamer-modified gFET (see left panel in Fig. 4b) confirms the effectiveness of our procedure in locally attaching aptamers. In this experiment, we also demonstrate the versatility of this approach in implementing control gFETs on the same chip by leveraging the spatial-selective biofunctionalization capability of tSPL. Control devices are produced simply by skipping the tSPL step in the channel region of a few select gFETs, while subjecting these gFETs to the same subsequent surface chemistry treatments as sensor gFETs. The fluorescent microscopy results for the control gFET (see right panel in Fig. 4b) confirm the chemical inactivity of the channel region in the control gFET with minimal non-specific binding.

Fig. 4 Spike protein–aptamer capture on the NanoBioFET platform. (a) Schematic of a gFET functionalized with SARS-CoV-2 aptamer using the NanoBioFET platform paired with a control device. (b) Florescence microscopy of the sensor and control gFET devices, demonstrating successful immobilization of the fluorescently tagged aptamer exclusively on the sensor channel. The yellow dashed lines denote the metal electrodes of the gFET devices, and the white rectangle denotes the graphene channel. Scale bar is 20 μm. (c) SPR measurement at 0.1× PBS of binding between the aptamer and spike protein. Graphene channel is denoted with a solid box. (d) Transient responses of the aptamer-modified gFET and the adjacent control gFET in 0.1× PBS. The capability of the NanoBioFET platform in simultaneously monitoring the transient characteristics of the sensor and control gFETs gives confidence in fidelity of the detected signal by the sensor in response to the spike protein injections. Black circle and red diamond symbols denote, respectively, injections of buffer and spike protein of increasing concentrations. Dashed lines are a guide-to-the-eye of the measurement signal. (e) Sensitivity plot of the gFET, obtained from a Hill fit to the calibrated sensor response data at different spike protein concentrations.

In Fig. 4c, similarly to experiments of antibody in Fig. 3, we perform SPR experiments for validation of the binding between the anti-SARS-CoV-2 aptamer and spike protein in 0.1× PBS (λ_Debye of 2 nm). The subsequent electronic sensing experiments in a microfluidic chamber demonstrate the ability of aptamer-modified gFETs in generating detectable electronic signals in response to spike protein injections in the same buffer concentrations (see Fig. 4d). The simultaneous monitoring of an adjacent control device in this experiment provides confidence about the fidelity of the electronic signals generated by the gFET biosensor. This key feature of the NanoBioFET platform in enabling differential detection and simultaneous monitoring of non-specific binding is an important step toward achieving robust analyte detection using FET-based biosensors.

A closer look at the results in Fig. 4d reveals two important observations. The first observation is the significantly weaker signal amplitude of the aptamer-modified gFET compared to its antibody-modified counterpart in Fig. 3e. Whereas the antibody-modified gFET generates a 4 mV signal in response to 3 aM of spike concentration, the aptamer-modified counterpart produces only a 1.3 mV signal when exposed to 500 aM of spike protein. We attribute this characteristic primarily to the significantly smaller λ_Debye at 0.1× PBS. We expect that ongoing research in the field, focused on increasing the λ_Debye at a given ionic strength⁴⁶ and developing alternative chemical conjugation strategies beyond biotin–streptavidin will directly benefit future experiments utilizing aptamer-modified gFETs. The second observation pertains to the relationship between the signal amplitude and the spike protein concentration. The data indicate a nearly diminishing response with the subsequent spike protein injections at higher concentrations. This observation suggests that the capturing aptamers on the gFET are reaching full occupancy, wherein the captured surface proteins block the interactions of incoming proteins with the surface probes. To quantify this, we plot the calibrated signal responses as a function of the analyte concentration (log-scale) in Fig. 4e, and fit the data with a Hill model as before. From the fit we estimate V_max = 6 ± 2 mV, indicating a lower sensitivity of the aptamer-modified gFET in 0.1× PBS. The fit also returns a Hill coefficient of 0.38, indicating negative cooperativity. A full understanding of the nature of observed binding interactions in these experiments is a focus of future studies.

Evaluation of NanoBioFET platform using live human CoV-2 viral particles

Following the success of spike protein detection with bioreceptor-modified gFETs, we perform a final test with human live SARS-CoV-2 viral particles and the SARS-CoV-2 antibody as bioreceptor from earlier, evaluating sensitivity to low viral loads and selectivity of the response to specific viruses. Additionally, the experiments in Fig. 3 confirm the high sensitivity of antibody-modified gFETs in detecting low concentrations of spike proteins. Therefore, we employ the antibody-modified gFETs in experiments involving live viral particle detection.

The measurement setup and procedure are nearly identical to that for the antibody–spike protein measurements earlier, with a 1 mM HEPES buffer (see Fig. 5a and Experimental methods for details). We monitor the temporal changes in I_ds during the course of the sensing experiment. The experimental sensing procedure involves injection of the blank virus medium at the beginning of the experiments, followed by a few alternating injections of SARS-CoV-2 virus and the human H1N1 influenza virus (see Experimental methods for details on these viruses). Fig. 5b shows the transient response of the antibody-modified gFET with live virus injections in 1 mM HEPES. Injections of virus medium (black circle), SARS-CoV-2 virus (red diamond), and H1N1 virus (green star) are marked in Fig. 5b. The data demonstrate the sensitive and selective detection by the SARS-CoV-2 antibody-modified gFET. The SARS-CoV-2 virus (red diamond) and H1N1 virus (green star) in Fig. 5 show that the SARS-CoV-2 virus repeatedly produces an exponential-like response in the sensor, whereas the H1N1 virus (which we use as a negative control) or buffer produce no response. The first four virus injections are at a concentration of 20 TCID₅₀ per ml and the last at 200 TCID₅₀ per ml, estimated to be about 10 infectious virus particles per ml, demonstrating ultra-sensitive detection of the live virus. The insensitivity of the sensor to H1N1 injections highlights the selectivity of the gFET sensor.

Fig. 5 Ultrasensitive and selective detection of live human SARS-CoV-2 virus. (a) Schematic of a gFET functionalized with SARS-CoV-2 antibody using the NanoBioFET platform for detection of live SARS-CoV-2 virus. (b) Transient response of the antibody-modified gFET with live virus injections in 1 mM HEPES. Injections of virus medium (black circle), SARS-CoV-2 virus (red diamond) and H1N1 virus (green star) are indicated. The first four virus injections were at a concentration of 20 TCID₅₀ per ml and the last at 200 TCID₅₀ per ml, estimated to be of the order of 10 live particles in the measurement volume, demonstrating ultra-sensitive detection of the live virus. The insensitivity of the sensor to H1N1 injections highlights the selectivity of the platform. Dashed lines are a guide-to-the-eye of the measurement signal.

Conclusions

In conclusion, the results presented here establish a paradigm shift in functionalization of FETs for biosensing. While so far functionalization of FET-based biosensors is commonly achieved by drop casting with no or limited spatial selectivity, here we show a scalable, semiconductor compatible surface functionalization nanofabrication strategy that allows modification of individual FETs on the same chip with distinct pathogen-specific bioreceptors, with nanoscale resolution. The NanoBioFET platform is implemented through the combination of thermal scanning probe lithography, thermochemically sensitive polymers which are spin-coated on the FETs chip, and in situ thermal imaging. We demonstrate that this methodology can be used to implement site-selective multiplexed functionalization with different bioreceptors. Specifically, this tSPL-enabled approach can provide spatial selective functionalization at precise locations on a chip at sub-20 nm resolution and 200 nm pitch, a distance comparable to the pitch of modern FETs array in CMOS chip. Functionalization of target regions with sub-micron pitch is a significant advance towards achieving massively parallel FET detection of multiple target pathogens. The ability to pattern individual FETs also allows for in situ differential sensing, a key feature to ensure signal fidelity.

The successful electronic sensing experiments for detection of CoV-2 targets confirm the feasibility of integration of the proposed functionalization strategy with FET biosensors. The key to this advance is the effective function of the polymer as a capacitor between the surface-anchored bioreceptors and the buried FET sensors, allowing the electronic detection of interactions between target analytes and specific bioreceptors. The electronic sensing experiments reveal ultrasensitive and selective sensing performance of the gFETs functionalized using the NanoBioFET platform. We achieve detection for 3 aM of SARS-CoV-2 spike proteins and 10 human SARS-CoV-2 infectious live virus particles per mL, as well as selectivity against human influenza A (H1N1) live virus. While this study confirms the feasibility of the NanoBioFET platform, future studies will focus on enabling multiplexed FET sensing using this methodology.

Lastly, we remark on the nanomanufacturing prospects of the proposed NanoBioFET platform. A key asset of this functionalization strategy is its generalizability to various FET materials from silicon to graphene. Indeed, the polymer stack is spin coated atop the fully fabricated chips, a process scalable to commercial silicon and other types of substrates with up to 300 mm diameter. Therefore, the NanoBioFET platform is compatible with commercial semiconductor manufacturing for producing CMOS chips that can contain many FETs (thousands to millions), where each FET or a group of FETs can be modified for detecting a specific target pathogen. To this end, we note that the tSPL process could be parallelized with the use of hot probes arrays, while the scanner head could work in parallel with picoliter piezo-type printing, decreasing the nanopatterning times, which are at present about 10 minutes per FET. Furthermore, tSPL is a flexible and sustainable nanofabrication method that does not require vacuum or high energy or alignment marks since each FET can be imaged in situ during patterning. Finally, we remark that the here-proposed biotin–streptavidin strategy to anchor the biomarkers to the surface can be easily changed with different amine-bioconjugation approaches to meet different device requirements.

Data availability

The data supporting this article have been included as part of the ESI.†

All experimental data are available from the corresponding author upon reasonable request.

Conflicts of interest

The authors acknowledge the following patent application: WO2023178345.

Acknowledgements

This work is supported by funding from Lendlease LLC and Mirimus Inc. The device fabrication was done in part at the Nanofabrication Facility at the Advanced Science Research Center at The Graduate Center of the City University of New York, and in part at the Nanofabrication Cleanroom Facility at the NYU Tandon School of Engineering. E. R. and D. S. thank Dr Alberto Sangiovanni-Vincentelli, Dr Nathalie Pinkerton and Dr Paramjit Arora for the useful discussions.

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Footnotes

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4nr02535k

‡ These authors contributed equally to this work.

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