Enhancing Electrochemical Sensing through Molecular Engineering of Reduced Graphene Oxide-Solution Interfaces and Remote Floating-Gate FET Analysis.

Two-dimensional nanomaterials such as reduced graphene oxide (rGO) have captured significant attention in the realm of field-effect transistor (FET) sensors due to their inherent high sensitivity and cost-effective manufacturing. Despite their attraction, a comprehensive understanding of rGO-solution interfaces (specifically, electrochemical interfacial properties influenced by linker molecules and surface chemistry) remains challenging, given the limited capability of analytical tools to directly measure intricate solution interface properties. In this study, we introduce an analytical tool designed to directly measure the surface charge density of the rGO-solution interface leveraging the remote floating-gate FET (RFGFET) platform. Our methodology involves characterizing the electrochemical properties of rGO, which are influenced by adhesion layers between SiO2 and rGO, such as (3-aminopropyl)trimethoxysilane (APTMS) and hexamethyldisilazane (HMDS). The hydrophilic nature of APTMS facilitates the acceptance of oxygen-rich rGO, resulting in a noteworthy pH sensitivity of 56.8 mV/pH at the rGO-solution interface. Conversely, hydrophobic HMDS significantly suppresses the pH sensitivity from the rGO-solution interface, attributed to the graphitic carbon-rich surface of rGO. Consequently, the carbon-rich surface facilitates a denser arrangement of 1-pyrenebutyric acid N-hydroxysuccinimide ester linkers for functionalizing capturing probes on rGO, resulting in an enhanced sensitivity of lead ions by 32% in our proof-of-concept test.

Scalable graphene sensor array for real-time toxins monitoring in flowing water.

Risk management for drinking water often requires continuous monitoring of various toxins in flowing water. While they can be readily integrated with existing water infrastructure, two-dimensional (2D) electronic sensors often suffer from device-to-device variations due to the lack of an effective strategy for identifying faulty devices from preselected uniform devices based on electronic properties alone, resulting in sensor inaccuracy and thus slowing down their real-world applications. Here, we report the combination of wet transfer, impedance and noise measurements, and machine learning to facilitate the scalable nanofabrication of graphene-based field-effect transistor (GFET) sensor arrays and the efficient identification of faulty devices. Our sensors were able to perform real-time detection of heavy-metal ions (lead and mercury) and E. coli bacteria simultaneously in flowing tap water. This study offers a reliable quality control protocol to increase the potential of electronic sensors for monitoring pollutants in flowing water.

Rapid, Sensitive, Label-Free Electrical Detection of SARS-CoV-2 in Nasal Swab Samples.

Rapid diagnosis of coronavirus disease 2019 (COVID-19) is key for the long-term control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) amid renewed threats of mutated SARS-CoV-2 around the world. Here, we report on an electrical label-free detection of SARS-CoV-2 in nasopharyngeal swab samples directly collected from outpatients or in saliva-relevant conditions by using a remote floating-gate field-effect transistor (RFGFET) with a 2-dimensional reduced graphene oxide (rGO) sensing membrane. RFGFET sensors demonstrate rapid detection (<5 min), a 90.6% accuracy from 8 nasal swab samples measured by 4 different devices for each sample, and a coefficient of variation (CV) < 6%. Also, RFGFET sensors display a limit of detection (LOD) of pseudo-SARS-CoV-2 that is 10 000-fold lower than enzyme-linked immunosorbent assays, with a comparable LOD to that of reverse transcription-polymerase chain reaction (RT-PCR) for patient samples. To achieve this, comprehensive systematic studies were performed regarding interactions between SARS-CoV-2 and spike proteins, neutralizing antibodies, and angiotensin-converting enzyme 2, as either a biomarker (detection target) or a sensing probe (receptor) functionalized on the rGO sensing membrane. Taken together, this work may have an immense effect on positioning FET bioelectronics for rapid SARS-CoV-2 diagnostics.

Remote Floating-Gate Field-Effect Transistor with 2-Dimensional Reduced Graphene Oxide Sensing Layer for Reliable Detection of SARS-CoV-2 Spike Proteins.

Despite intensive research of nanomaterials-based field-effect transistors (FETs) as a rapid diagnostic tool, it remains to be seen for FET sensors to be used for clinical applications due to a lack of stability, reliability, reproducibility, and scalability for mass production. Herein, we propose a remote floating-gate (RFG) FET configuration to eliminate device-to-device variations of two-dimensional reduced graphene oxide (rGO) sensing surfaces and most of the instability at the solution interface. Also, critical mechanistic factors behind the electrochemical instability of rGO such as severe drift and hysteresis were identified through extensive studies on rGO-solution interfaces varied by rGO thickness, coverage, and reduction temperature. rGO surfaces in our RFGFET structure displayed a Nernstian response of 54 mV/pH (from pH 2 to 11) with a 90% yield (9 samples out of total 10), coefficient of variation (CV) < 3%, and a low drift rate of 2%, all of which were calculated from the absolute measurement values. As proof-of-concept, we demonstrated highly reliable, reproducible, and label-free detection of spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a saliva-relevant media with concentrations ranging from 500 fg/mL to 5 µg/mL, with an R2 value of 0.984 and CV < 3%, and a guaranteed limit of detection at a few pg/mL. Taken together, this new platform may have an immense effect on positioning FET bioelectronics in a clinical setting for detecting SARS-CoV-2.

Understanding, discovery, and synthesis of 2D materials enabled by machine learning.

Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on the understanding, discovery, and synthesis of 2D materials enabled by or benefiting from various ML techniques. We introduce the most recent efforts to adopt ML in various fields of study regarding 2D materials and provide an outlook for future research opportunities. The adoption of ML is anticipated to accelerate and transform the study of 2D materials and their heterostructures.

Molecular Engineering of 2D Nanomaterial Field-Effect Transistor Sensors: Fundamentals and Translation across the Innovation Spectrum.

Over the last decade, 2D layered nanomaterials have attracted significant attention across the scientific community due to their rich and exotic properties. Various nanoelectronic devices based on these 2D nanomaterials have been explored and demonstrated, including those for environmental applications. Here, the fundamental attributes of 2D layered nanomaterials for field-effect transistor (FET) sensors and tunneling FET (TFET) sensors, which provide versatile detection of water contaminants such as heavy-metal ions, bacteria, nutrients, and organic pollutants, are discussed. The major challenges and opportunities are also outlined for designing and fabricating 2D nanomaterial FET/TFET sensors with superior performance. Translation of these FET/TFET sensors from fundamental research to applied technology is illustrated through a case study on graphene-based real-time FET water sensors. A second case study centers on large-scale sensor networks for water-quality monitoring to enable intelligent drinking water and river-water systems. Overall, 2D nanomaterial FET sensors have significant potential for enabling a human-centered intelligent water system that can likely be applied to other precarious water supplies around the globe.

Quantitative analysis of the synergistic effect of Au nanoparticles on SnO2-rGO nanocomposites for room temperature hydrogen sensing.

Hydrogen detection devices based on gold-tin oxide/reduced graphene oxide (Au-SnO2/rGO) nanohybrids were fabricated by combining a hydrothermal method with sputter coating. The gas sensing performance of the Au-SnO2/rGO sensor was investigated under different concentrations of hydrogen from 0.04% to 1% at room temperature, which indicated a notable sensitive response even for 0.04% hydrogen. The activation energies of hydrogen adsorption/desorption were extracted via Arrhenius analysis which revealed the acceleration effect of gold dopants. This acceleration led to a faster response and recovery during hydrogen sensing. The activation energy analysis provided a more comprehensive understanding on the gas sensing mechanism. A hydrogen detection handheld device is demonstrated by integrating the sensor chip with a portable digital meter for direct readout of test results.

Wastewater-Based Epidemiology for Managing the COVID-19 Pandemic.

SARS-CoV-2 is shed by COVID-19 patients and can be detected in wastewater. Thus, testing wastewater for the virus provides a depiction of disease prevalence in a community. Virus concentration data can be utilized to monitor infection trends, identify hot spots, and inform decision makers regarding reopening efforts and directing resources. This perspective aims to shed light on the current situation relating to SARS-CoV-2 in the wastewater system and the opportunity to utilize wastewater to collect useful epidemiological data. First, the survivability of SARS-CoV-2 in different water matrices is examined through the lens of surrogate viruses. Second, the effect of wastewater treatment processes on SARS-CoV-2 is investigated. Current standards for sufficient reduction of the virus and the risk of exposure that arises at each stage in the wastewater treatment process are discussed. Third, the immense potential of wastewater-based epidemiology (WBE) for managing the ongoing COVID-19 pandemic is analyzed. Studies that have tested wastewater or sludge for SARS-CoV-2 are discussed, and results are tabulated. Lastly, the current limitations of WBE and opportunities of future research are explored. Using the wealth of knowledge that the scientific community now has about WBE, wastewater testing should be considered by regional governments and private institutions.

Sensitive field-effect transistor sensors with atomically thin black phosphorus nanosheets.

Atomically thin black phosphorus (BP) field-effect transistors have excellent potential for sensing applications. However, commercial scaling of PFET sensors is still in the early stage due to various technical challenges, such as tedious fabrication, low response% caused by rapid oxidation, non-ideal response output (spike/bidirectional), and large device variation due to poor control over layer thickness among devices. Attempts have been made to address these issues. First, a theoretical model for response% dependence on the number of layers is developed to show the role of atomically thin BP for better responses. A position-tracked, selected-area-exfoliation method has been developed to rapidly produce thin BP layers with a narrow distribution (∼1-7 layers), which can harness excellent gate control over the PFET channel. The typical current on/off ratio is in the range of ∼300-500. The cysteine-modified Al2O3-gated PFET sensors show high responses (∼30-900%) toward a wide detection range (∼1-400 ppb) of lead ions in water with a typical response time of ∼10-30 s. A strategy to minimize device variation is proposed by correlating PFETs' on/off ratio with sensitivity parameters. The thickness variation of the gate oxide is investigated to explain non-ideal and ideal response transient kinetics.

Ultratrace antibiotic sensing using aptamer/graphene-based field-effect transistors.

Antibiotic residue, as emerging pollution resulting from antibiotic abuse, poses a serious threat on ecosystem and human health. Conventional methods for antibiotic detection, e.g., liquid/gas chromatography, are based on complicated instruments and time-consuming; therefore, efforts have been made to realize in situ and real-time monitoring of antibiotics. Here, a miniaturized and integratable electronic antibiotic sensor based on field-effect transistor (FET) is reported. The reduced graphene oxide (rGO) nanosheet is used as the channel material and the aptamer RNA for tobramycin is modified onto rGO as the probe. A novel sensor design with 6-mercapto-1-hexanol (MCH)/1-pyrenebutanol (PBA) blocking layer (BL) for structure optimization is applied to enhance the sensor reliability and specificity. This rGO/aptamer/BL sensor shows an ultra-sensitivity to tobramycin with a lower detection limit of 0.3 nM and a quick response within 5 s, as well as a high specificity over other antibiotics such as kanamycin, streptomycin, ciprofloxacin, and tetracycline. The sensing mechanism based on the deformation of the charged aptamer probe is proposed via an in-depth analysis of the interactions between aptamer, tobramycin and rGO. In addition, sensing test performed under controlled microfluidic flow conditions demonstrates a great potential of the sensors in practical applications.

Resonance-Frequency Modulation for Rapid, Point-of-Care Ebola-Glycoprotein Diagnosis with a Graphene-Based Field-Effect Biotransistor.

Recent outbreaks of Ebola-virus infections in several countries demand a rapid point-of-care (POC)-detection strategy. This paper reports on an innovative pathway founded on electronic-resonance-frequency modulation to detect Ebola glycoprotein (GP), on the basis of a carrier-injection-trapping-release-transfer mechanism and the standard antibody-antigen-interaction principle within a dielectric-gated reduced graphene oxide (rGO) field-effect transistor (GFET). The sensitivity of Ebola detection can be significantly enhanced by monitoring the device's electronic-resonance frequency, such as its inflection frequency ( fi), where the phase angle reaches a maximum (θmax). In addition to excellent selectivity, a sensitivity of ∼36-160% and ∼17-40% for 0.001-3.401 mg/L Ebola GP can be achieved at high and low inflection-resonance frequencies, respectively, which are several orders of magnitude higher than the sensitivity from other electronic parameters (e.g., resistance-based sensitivity). Using equivalent circuit modeling for contributions from channel and contact, analytical equations for resonance shifts have been generalized. When matching with the incoming ac-measurement signal, electronic resonance from the phase-angle spectrum evolves from various relaxation processes (e.g., trap and release of injected charges at surface-trap sites of the channel-gate oxide and channel-source or drain interfaces) that are associated with a characteristic emission frequency. Using charge-relaxation dynamics, a high-performance bio-FET sensing platform for healthcare and bioelectronic applications is realized through resonance shifting.

Organometallic Precursor-Derived SnO2/Sn-Reduced Graphene Oxide Sandwiched Nanocomposite Anode with Superior Lithium Storage Capacity.

Benefiting from the reversible conversion reaction upon delithiation, nanosized SnO2, with its theoretical capacity of 1494 mA h g-1, has gained special attention as a promising anode material. Here, we report a self-assembled SnO2/Sn-reduced graphene oxide (rGO) sandwich nanocomposite developed by organometallic precursor coating and in situ transformation. Ultrafine SnO2 nanoparticles with an average diameter of 5 nm are sandwiched within the rGO/carbonaceous network, which not only greatly alleviates the volume changes upon lithiation and aggregation of SnO2 nanoparticles but also facilitates the charge transfer and reaction kinetics of SnO2 upon lithiation/delithiation. As a result, the SnO2/Sn-rGO nanocomposite exhibited a superior lithium storage capacity with a reversible capacity of 1307 mA h g-1 at a current density of 80 mA g-1 in the potential window of 0.01-2.5 V versus Li+/Li and showed a reversible capacity of 767 mA h g-1 over 200 cycles at a current density of 400 mA g-1. When cycling at a higher current density of 1600 mA g-1, the SnO2/Sn-rGO nanocomposite showed a highly stable capacity of 449 mA g-1 without obvious decay after 400 cycles.

Impedimetric phosphorene field-effect transistors for rapid detection of lead ions.

Stimuli-responsive field-effect transistors (FETs) based on 2D nanomaterials have been considered as attractive candidates for sensing applications due to their rapid response, high sensitivity, and real-time monitoring capabilities. Here we report on an impedance spectroscopy technique for FET sensor applications with ultra-high sensitivity and good reproducibility. An alumina-gated FET, using an ultra-thin black phosphorus flake as the channel material, shows significantly improved stability and ultra-high sensitivity to lead ions in water. In addition, the phase angle in the low frequency region was found to change significantly in the presence of lead ion solutions, whereas it was almost unchanged in the high frequency region. The dominant sensing performance was found at low frequency phase spectrum around 50 Hz and a systematic change in the phase angle in different lead ion concentrations was found. Applying the impedance spectroscopy technique to insulator-gated FET sensors could open a new avenue for real-world sensor applications.

Rapid detection of single E. coli bacteria using a graphene-based field-effect transistor device.

Contamination of surface and drinking water due to the presence of Escherichia coli bacteria is a major cause of water-borne disease outbreak. To address unmet challenges for practical pathogen detection in contaminated samples, we report fabrication of thermally reduced graphene oxide-based field-effect transistor (rGO FET) passivated with an ultrathin layer of Al2O3 for real-time detection of E. coli bacteria. The sensor could detect a single E. coli cell within 50 s in a 1 µL sample volume. The ultrathin layer of Al2O3 acted as a barrier between rGO and potential interferents present in the sample. E. coli specific antibodies anchored on gold nanoparticles acted as probes for selective capture of E. coli. The high density of negative charge on the surface of E. coli cells strongly modulates the concentration of majority charge carriers in the rGO monolayer, thereby allowing real-time monitoring of E. coli concentration in a given sample. With a low detection limit of single cell, the FET sensor had a linear range of 1-100 CFU in 1 µL volume of sample (i.e., 103 to 105 CFU/ mL). The biosensor with good selectivity and rapid detection was further successfully demonstrated for E. coli sensing in river water. The rGO-based FET sensor provides a low cost and label-free approach, and can be mass produced for detection of a broad spectrum of pathogens in water or other liquid media.

In Operando Impedance Spectroscopic Analysis on NiO-WO3 Nanorod Heterojunction Random Networks for Room-Temperature H2S Detection.

The use of metal-oxide sensors for effectively detecting hydrogen sulfide (H2S) gas at room temperature is currently hindered by their inadequate sensitivity and selectivity. Using a lucid fabrication strategy, we report a room-temperature, highly sensitive, and selective H2S gas sensor using NiO-modified WO3 nanorod (one-dimensional-one-dimensional) random networks. The observed improvements in gas-sensing sensitivity stem from the synergistic effects of various contributions inside the sensing heterostructure, such as bulk nanorod, p-n heterojunction at the interface of these two dissimilar oxides, and gas-induced conducting species due to sulfurization (WS2-x and NiS1-x ). An in situ impedance measurement during gas exposure was used to investigate the influence of these effects. The analysis revealed that these contributing factors can be either cooperating or competing and lead to either increased or decreased sensitivity, respectively. The presence of semimetallic species (NiS, WS2) was further confirmed by in situ X-ray diffraction analysis of the heterostructure nanorod sample with H2S gas exposure. The related sensing mechanism in the heterostructures is presented with a conduction pathway model. The room-temperature-operated nanorod heterostructure sensors showed a lower detection limit of H2S at ∼0.5 ppm, which is significantly lower than its toxicity limiting value ∼10 ppm, per the Environmental Protection Agency. The nanorod heterostructure sensors can be used for real-time, low-cost, room-temperature alarms in an H2S monitoring system.

Pulse-Driven Capacitive Lead Ion Detection with Reduced Graphene Oxide Field-Effect Transistor Integrated with an Analyzing Device for Rapid Water Quality Monitoring.

Rapid and real-time detection of heavy metals in water with a portable microsystem is a growing demand in the field of environmental monitoring, food safety, and future cyber-physical infrastructure. Here, we report a novel ultrasensitive pulse-driven capacitance-based lead ion sensor using self-assembled graphene oxide (GO) monolayer deposition strategy to recognize the heavy metal ions in water. The overall field-effect transistor (FET) structure consists of a thermally reduced graphene oxide (rGO) channel with a thin layer of Al2O3 passivation as a top gate combined with sputtered gold nanoparticles that link with the glutathione (GSH) probe to attract Pb2+ ions in water. Using a preprogrammed microcontroller, chemo-capacitance based detection of lead ions has been demonstrated with this FET sensor. With a rapid response (∼1-2 s) and negligible signal drift, a limit of detection (LOD) < 1 ppb and excellent selectivity (with a sensitivity to lead ions 1 order of magnitude higher than that of interfering ions) can be achieved for Pb2+ measurements. The overall assay time (∼10 s) for background water stabilization followed by lead ion testing and calculation is much shorter than common FET resistance/current measurements (∼minutes) and other conventional methods, such as optical and inductively coupled plasma methods (∼hours). An approximate linear operational range (5-20 ppb) around 15 ppb (the maximum contaminant limit by US Environmental Protection Agency (EPA) for lead in drinking water) makes it especially suitable for drinking water quality monitoring. The validity of the pulse method is confirmed by quantifying Pb2+ in various real water samples such as tap, lake, and river water with an accuracy ∼75%. This capacitance measurement strategy is promising and can be readily extended to various FET-based sensor devices for other targets.

Two-dimensional nanomaterial-based field-effect transistors for chemical and biological sensing.

Meeting the increasing demand for sensors with high sensitivity, high selectivity, and rapid detection presents many challenges. In the last decade, electronic sensors based on field-effect transistors (FETs) have been widely studied due to their high sensitivity, rapid detection, and simple test procedure. Among these sensors, two-dimensional (2D) nanomaterial-based FET sensors have been demonstrated with tremendous potential for the detection of a wide range of analytes which is attributed to the unique structural and electronic properties of 2D nanomaterials. This comprehensive review discusses the recent progress in graphene-, 2D transition metal dichalcogenide-, and 2D black phosphorus-based FET sensors, with an emphasis on rapid and low-concentration detection of gases, biomolecules, and water contaminants.

Field-Effect Transistor Biosensor for Rapid Detection of Ebola Antigen.

The Ebola virus transmits a highly contagious, frequently fatal human disease for which there is no specific antiviral treatment. Therefore, rapid, accurate, and early diagnosis of Ebola virus disease (EVD) is critical to public health containment efforts, particularly in developing countries where resources are few and EVD is endemic. We have developed a reduced graphene oxide-based field-effect transistor method for real-time detection of the Ebola virus antigen. This method uses the attractive semiconductor characteristics of graphene-based material, and instantaneously yields highly sensitive and specific detection of Ebola glycoprotein. The feasibility of this method for clinical application in point-of-care technology is evaluated using Ebola glycoprotein suspended in diluted PBS buffer, human serum, and plasma. These results demonstrate the successful fabrication of a promising field-effect transistor biosensor for EVD diagnosis.

Field-effect transistor biosensors with two-dimensional black phosphorus nanosheets.

A black phosphorous (BP)-based field-effect transistor (FET) biosensor was fabricated by using few-layer BP nanosheets labeled with gold nanoparticle-antibody conjugates. BP nanosheets were mechanically exfoliated and used as the sensing/conducting channel in the FET, with an Al2O3 thin film as the dielectric layer for surface passivation. Antibody probes were conjugated with gold nanoparticles that were sputtered on the BP through surface functionalization. The sensor response was measured by the change in the BP's electrical resistance after antigens were introduced. The adsorbed antigens through specific antigen-antibody binding interactions induced a gate potential, thereby changing the drain-source current. The as-produced BP biosensor showed both high sensitivity (lower limit of detection ~10ng/ml) and selectivity towards human immunoglobulin G. Results from this study demonstrate the outstanding performance of BP as a sensing channel for FET biosensor applications.

Ultrahigh sensitivity and layer-dependent sensing performance of phosphorene-based gas sensors.

Two-dimensional (2D) layered materials have attracted significant attention for device applications because of their unique structures and outstanding properties. Here, a field-effect transistor (FET) sensor device is fabricated based on 2D phosphorene nanosheets (PNSs). The PNS sensor exhibits an ultrahigh sensitivity to NO2 in dry air and the sensitivity is dependent on its thickness. A maximum response is observed for 4.8-nm-thick PNS, with a sensitivity up to 190% at 20 parts per billion (p.p.b.) at room temperature. First-principles calculations combined with the statistical thermodynamics modelling predict that the adsorption density is ∼10(15) cm(-2) for the 4.8-nm-thick PNS when exposed to 20 p.p.b. NO2 at 300 K. Our sensitivity modelling further suggests that the dependence of sensitivity on the PNS thickness is dictated by the band gap for thinner sheets (<10 nm) and by the effective thickness on gas adsorption for thicker sheets (>10 nm).