Carbon Nanotube-based Field Effect Transistors Research Articles

Single-Walled Carbon Nanotube Based Field-Effect Transistors Functionalized with Odorant Receptors for Biosensing Applications

Bioelectronic detection of volatile organic compounds (VOC) has been demonstrated in a wide range of applications, with early reports focusing on environmental exogenous VOCs due to their adverse effects on human health; bacterial VOC signatures used as disease biomarkers, etc. Carbon nanotube field-effect transistors (CNT-FETs) are considered promising devices for bioelectronic detection due to their sensitivity, robustness and compatibility with microelectronic fabrication technologies. However, implementation of CNT-FETs still faces many challenges. Current VOCs detection approaches rely on separation techniques coupled with mass spectrometry, necessitating expensive equipment, labor-intensive preparation steps and trained personnel, and are not suitable for field use. Overcoming the challenges in the development of bioelectronic CNT-FET sensors holds great promise for high-throughput screening of VOCs.The natural insect odorant receptors (ORs) are highly attractive probes, potentially allowing ultrahigh specificity for VOC biosensing. Insect ORs exhibit remarkable sensitivities and the ability to selectively detect a vast number of VOCs. We have recently developed OR-functionalized carbon nanotube field-effect transistor (FET) devices. These FET devices comprise an isolated single-walled carbon nanotube (SWCNT), serving as the conducting channel material, functionalized with multiple insect ORs. These hybrid devices are capable of transducing ligand binding into an electronic current, without amplification. The insect OR-functionalized CNT FET were applied for the detection of several markers of environmental and clinical importance including Indole, Skatole, Octen-3-ol and Nonyl-aldehyde.We have developed a bioelectronic assay platform that contains a chip with 61 ORs-functionalized CNT-FET devices. Our unique functionalization method is based on directing the attachment of a native ORs-containing nanovesicles (which we have exogenously expressed and functionally characterized) to a generated CNT-FET point defect. Target binding-induced ionic current and conformational changes of ORs affect an electric field that modulates the device conductance.

(Invited) Norfentanyl Detection with Carbon Nanotube-Based Field-Effect Transistors

The opioid crisis, propelled predominantly by synthetic opioids such as illicit fentanyl, constitutes a significant global public health threat. To meet the critical demand for a sensitive and portable analytical tool for detecting fentanyl exposure, we have developed two types of biosensors based on single-walled carbon nanotubes (SWCNTs).The first biosensor is a field-effect transistor (FET) device with semiconductor-enriched SWCNTs, functionalized with norfentanyl antibody.1 This antibody-SWCNT-FET biosensor exhibits ultrasensitive detection of norfentanyl, the primary inactive metabolite of fentanyl, in urine samples. Various sensor configurations were investigated to optimize sensing results. The use of a "reduced" antibody facilitated oriented immobilization, enhancing the proximity of the antigen-antibody interaction to the sensor surface and resulting in improved sensitivity. These norfentanyl biosensors demonstrate remarkable sensitivity, with a limit of detection in the fg/mL range in both calibration and synthetic urine samples, showcasing their potential as highly reliable detection tools.While capture probes like antibodies enhance chemical sensitivity and selectivity, the stability of nanotube-based biosensors is constrained by the activity of these capture probes. To address this limitation, we have explored an alternative approach involving sensor arrays consisting of different metal-organic frameworks (MOFs) on SWCNTs, which act as nonspecific receptors. With the assistance of machine learning-driven discrimination, such sensor arrays hold the potential to generate unique signals for different analytes.In pursuit of this objective, size-based norfentanyl detection was achieved using SWCNT@MOF composites in FET biosensors.2 Four SWCNT@MOF composites were synthesized, with SWCNT@UiO-67 demonstrating the highest sensing response to norfentanyl due to a size-matching effect within the MOF channel. Composites with smaller pore sizes such as SWCNT@UiO-66 and SWCNT@UiO-66-NH2 did not exhibit sensitivity improvement compared to bare SWCNT. We have also demonstrated selectivity of these biosensors for norfentanyl over norhydrocodone and benzoylecgonine, which are major metabolites of hydrocodone and cocaine, respectively.Moreover, we successfully applied our sensor fabrication with a flexible FET electrode and a portable sensing setup, showing significant potential for developing a portable device for on-site detection of fentanyl exposure with improved sensitivity. Therefore, we envision our norfentanyl biosensors can enhance the safety and security of both first responders and overdose victims and provide a platform technology that can contribute to the development of effective tools for addressing the opioid crisis.[1] Shao, W.; Zeng, Z.; Star A., An Ultrasensitive Norfentanyl Sensor Based on a Carbon Nanotube-Based Field-Effect Transistor for the Detection of Fentanyl Exposure. ACS Appl. Mater. Interfaces 2023, 15, 37784–37793.[2] Zeng, Z.; Islamov, M.; He, Y.; Day, B. A.; Rosi, N. L.; Wilmer, C. E.; Star, A., Size-Based Norfentanyl Detection with SWCNT @ UiO-MOF Composites. ACS Appl. Mater. Interfaces 2023, accepted.

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors.

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8fgmL-1.

Diagnostics of Tuberculosis with Single-Walled Carbon Nanotube-Based Field-Effect Transistors.

Tuberculosis (TB) is still threatening millions of people's lives, especially in developing countries. One of the major factors contributing to the ongoing epidemic of TB is the lack of a fast, efficient, and inexpensive diagnostic strategy. In this work, we developed a semiconducting single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) device functionalized with anti-Mycobacterium tuberculosis antigen 85B antibody (Ab85B) to detect the major M. tuberculosis-secreted antigen 85B (Ag85B). Through optimizing the device fabrication process by evaluating the mass of the antibody and the concentration of the gating electrolyte, our Ab85B-SWCNT FET devices achieved the detection of the Ag85B spiked in phosphate-buffered saline (calibration samples) with a limit of detection (LOD) of 0.05 fg/mL. This SWCNT FET biosensor also showed good sensing performance in biological matrices including artificial sputum and can identify Ag85B in serum after introducing bovine serum albumin (BSA) into the blocking layer. Furthermore, our BSA-blocked Ab85B-SWCNT FET devices can distinguish between TB-positive and -negative clinical samples, promising the application of SWCNT FET devices in point-of-care TB diagnostics. Moreover, the robustness of this SWCNT-based biosensor to the TB diagnosis in blood serum was enhanced by blocking SWCNT devices directly with a glutaraldehyde cross-linked BSA layer, enabling future applications of these SWCNT-based biosensors in clinical testing.

Theoretical approaches toward designing sensitive materials for carbon nanotube-based field-effect transistor gas sensors

Screening sensitive materials is one of the keys to designing high-performance carbon nanotube-based field-effect transistor gas sensors. Here, we proposed a reliable way (e.g., H2S) to design sensitive materials with high efficiency based on theory and experiment. Our results demonstrated that the interaction between H2S and the sensitive materials must satisfy both energy level and parity match, and the maximum overlap of the orbital wave function. Especially, the gas ΔQ exhibits a strong linear scaling with the metal φ (ΔQ∝φ). Meanwhile, Δφ will result in changes in the threshold voltage of the sensor (ΔVth∝Δφ) in experiments, which would lead to different response intensities. Therefore, the greater the ΔQ, the more changes in the threshold voltage, and corresponding higher response intensity. Expectedly, our experimental results show that the response intensity at equivalent concentrations is in high agreement with the theory (Pt > Pd > Ag), and the limit of H2S detection is low to 20 ppb.

Rapid and Easy Detection of Microcystin-LR Using a Bioactivated Multi-Walled Carbon Nanotube-Based Field-Effect Transistor Sensor.

In this study, we developed a multi-walled carbon nanotube (MWCNT)-based field-effect transistor (MWCNT-FET) sensor with high sensitivity and selectivity for microcystin-LR (MC-LR). Carboxylated MWCNTs were activated with an MC-LR-targeting aptamer (MCTA). Subsequently the bioactivated MWCNTs were immobilized between interdigitated drain (D) and source (S) electrodes through self-assembly. The top-gated MWCNT-FET sensor was configured by dropping the sample solution onto the D and S electrodes and immersing a Ag/AgCl electrode in the sample solution as a gate (G) electrode. We believe that the FET sensor's conduction path arises from the interplay between the MCTAs, with the applied gate potential modulating this path. Using standard instruments and a personal computer, the sensor's response was detected in real-time within a 10 min time frame. This label-free FET sensor demonstrated an impressive detection capability for MC-LR in the concentration range of 0.1-0.5 ng/mL, exhibiting a lower detection limit of 0.11 ng/mL. Additionally, the MWCNT-FET sensor displayed consistent reproducibility, a robust selectivity for MC-LR over its congeners, and minimal matrix interferences. Given these attributes, this easily mass-producible FET sensor is a promising tool for rapid, straightforward, and sensitive MC-LR detection in freshwater environments.

Ternary arithmetic and logic unit with carbon nanotube-based field-effect transistors for ultra-low power and high-speed applications

<span>The number of consumers for different applications has expanded tremendously as a result of the growth of consumer electronics-related applications in numerous sectors. Customers often need high-speed applications that use a minimal amount of power for a variety of applications like signal processing, picture processing, communication systems, and so on. The speed of a ternary logic-based design might be greater than that of a binary logic-based one. In this study, a novel architecture for arithmetic and logic units (ALUs) is proposed. The design makes use of ternary logic. In order to accomplish both low power consumption and high performance, methodologies for designing carbon nanotube-based field-effect transistors (CNTFETs) are employed. The method that has been suggested is able to carry out operations such as addition, subtraction, multiplication, reasoning, and comparison. After developing the recommended model, it is compared to earlier designs for power delay product (PDP), average power consumption, and maximum delay duration. The simulation findings show that the carbon nanotube field effect transistors (CNTFET) based ternary ALU circuits outperformed conventional ternary full adder circuits. The suggested design had a delay time of 13.94 ps and a PDP of 5.32 aJ, while the old design had a delay time of 17.67 ps and a PDP of 51.38 aJ.</span>

Cobalt ferrite/semiconducting single-walled carbon nanotubes based field-effect transistor for determination of carbamate pesticides

Carbaryl and carbofuran are the carbamate pesticides which have been widely used worldwide to control insects in crops and house. If the pesticides entered in to the food products and drinking water, they could cause serious health effects in humans. Therefore, the development of a rapid, simple, sensitive and selective analytical device for on-site detection of carbamates is crucial to evaluate food and environmental samples. Recently, semiconducting single-walled carbon nanotube-based field effect transistors (s-SWCNT/FETs) have shown several advantages such as high carrier mobility, good on/off ratio, quasi ballistic electron transport, label-free detection and real-time response. Herein, cobalt ferrite (CFO) nanoparticles decorated s-SWCNTs have been prepared and used to bridge the source and drain electrodes. As-prepared CFO/s-SWCNT/FET had been used for the non-enzymatic detection of carbaryl and carbofuran. When used as a sensing platform, the CFO/s-SWCNT hybrid film exhibited high sensitivity, and selectivity with a wide linear range of detection from 10 to 100 fMand the lowest limit of detections for carbaryl (0.11 fM) and carbofuran (0.07 fM) were estimated. This sensor was also used to detect carbaryl in tomato and cabbage samples, which confirmed its practical acceptance. Such performance may be attributed to the oxidation of carbamates by potent catalytic activity of CFO, which led to the changes in the charge transfer reaction on the s-SWCNTs/FET conduction channel. This work presents a novel CFO/s-SWCNT based sensing system which could be used to quantify pesticide residues in food samples.

An Ultrasensitive Norfentanyl Sensor Based on a Carbon Nanotube-Based Field-Effect Transistor for the Detection of Fentanyl Exposure.

The opioid crisis is a worldwide public health crisis that has affected millions of people. In recent years, synthetic opioids, primarily illicit fentanyl, have become the primary driver of overdose deaths. There is a great need for a highly sensitive, portable, and inexpensive analytical tool that can quickly indicate the presence and relative threat of fentanyl. In this work, we develop a semiconductor enriched (sc-) single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) biosensor functionalized with norfentanyl antibodies for the sensitive detection of norfentanyl, the primary inactive metabolite of fentanyl, in urine samples. Different sensor configurations were explored in order to obtain the most optimized sensing results. Moreover, by employing the "reduced" antibody, we achieved orientated immobilization of the norfentanyl antibody and thus brought the antigen-antibody interaction closer to the sensor surface, further improving the sensitivity. The reported norfentanyl biosensors have a limit of detection in the fg/mL region in both calibration samples and synthetic urine samples, showing ultrasensitivity and high reliability.

Hydrogel-based Bioelectronic Tongue for the Evaluation of Umami Taste in Fermented Fish.

Bioelectronic tongues based on umami taste receptors have recently been reported for versatile applications such as food analyses. However, their practical applications are still limited, partly due to their limited stability and non-specific responses in real sample environments. Herein, we have developed a hydrogel-based bioelectronic tongue for the sensitive assessment of umami intensity in fish extract samples. In this study, the T1R1 venus flytrap of an umami taste receptor was immobilized on the gold floating electrodes of a carbon nanotube-based field-effect transistor. A polyacrylamide conducting hydrogel film was further hybridized on the sensor surface via physical adsorption, which could provide a good physiological environment to maintain the activity of receptors due to its excellent hydrophilicity and biocompatibility. The bioelectronic tongue with a receptor-embedded hydrogel structure showed a sensitive detection of umami substances down to 1 fM, and it also had a wide detection range of 10-15-10-2 M for monosodium glutamate and disodium inosinate, which covers the human taste threshold. More importantly, the proposed sensor could significantly reduce the non-specific binding of non-target molecules to a carbon nanotube channel as well as exhibit long-term stability, enabling sensitive detection of umami substances even in fish extract samples. Our hydrogel-based bioelectronic tongue provides a promising platform for future applications such as the flavor evaluation of foods and beverages.

Intense pH Sensitivity Modulation in Carbon Nanotube-Based Field-Effect Transistor by Non-Covalent Polyfluorene Functionalization.

We compare the pH sensing performance of non-functionalized carbon nanotubes (CNT) field-effect transistors (p-CNTFET) and CNTFET functionalized with a conjugated polyfluorene polymer (labeled FF-UR) bearing urea-based moieties (f-CNTFET). The devices are electrolyte-gated, PMMA-passivated, 5 µm-channel FETs with unsorted, inkjet-printed single-walled CNT. In phosphate (PBS) and borate (BBS) buffer solutions, the p-CNTFETs exhibit a p-type operation while f-CNTFETs exhibit p-type behavior in BBS and ambipolarity in PBS. The sensitivity to pH is evaluated by measuring the drain current at a gate and drain voltage of -0.8 V. In PBS, p-CNTFETs show a linear, reversible pH response between pH 3 and pH 9 with a sensitivity of 26 ± 2.2%/pH unit; while f-CNTFETs have a much stronger, reversible pH response (373%/pH unit), but only over the range of pH 7 to pH 9. In BBS, both p-CNTFET and f-CNTFET show a linear pH response between pH 5 and 9, with sensitivities of 56%/pH and 96%/pH, respectively. Analysis of the I-V curves as a function of pH suggests that the increased pH sensitivity of f-CNTFET is consistent with interactions of FF-UR with phosphate ions in PBS and boric acid in BBS, with the ratio and charge of the complexed species depending on pH. The complexation affects the efficiency of electrolyte gating and the surface charge around the CNT, both of which modify the I-V response of the CNTFET, leading to the observed current sensitivity as a function of pH. The performances of p-CNTFET in PBS are comparable to the best results in the literature, while the performances of the f-CNTFET far exceed the current state-of-the-art by a factor of four in BBS and more than 10 over a limited range of pH in BBS. This is the first time that a functionalization other than carboxylate moieties has significantly improved the state-of-the-art of pH sensing with CNTFET or CNT chemistors. On the other hand, this study also highlights the challenge of transferring this performance to a real water matrix, where many different species may compete for interactions with FF-UR.

Next-Generation Hybrid RF Front-End with MoS2-FET Supply Management Circuit, CNT-FET Amplifiers, and Graphene Thin-Film Antennas

One-dimensional (1D) and two-dimensional (2D) materials represent the emerging technologies for transistor electronics in view of their attractive electrical (high power gain, high cut-off frequency, low power dissipation) and mechanical properties. This work investigates the integration of carbon-nanotube-based field-effect transistors (CNT-FETs) and molybdenum disulphide (MoS2)-based FETs with standard CMOS technology for designing a simple analog system integrating a power switching circuit for the supply management of a 10 GHz transmitting/receiving (T/R) module that embeds a low-noise amplifier (LNA) and a high-power amplifier (HPA), both of which loaded by nanocrystalline graphene (NCG)-based patch antennas. Verilog-A models, tuned to the technology that will be used to manufacture the FETs, were implemented to perform electrical simulations of the MoS2 and CNT devices using a commercial integrated circuit software simulator. The obtained simulation results prove the potential of hybrid CNT-MoS2-FET circuits as building blocks for next-generation integrated circuits for radio frequency (RF) applications, such as radars or IoT systems.

(Invited) Cerebrospinal Fluid Leakage Detection with Carbon Nanotube-Based Field-Effect Transistors

Cerebrospinal fluid (CSF) leakage is a life-threatening medical condition that could result in significant morbidity and mortality if left untreated. However, the gold-standard test for confirming CSF leakage by detecting beta2-transferrin (β2-Tf) proteins using gel electrophoresis and Western blot is labor intensive and requires 3–6 hours. Carbon nanotube-based field-effect transistors (NTFET) are promising candidates for point-of-care diagnostic devices, owing to the outstanding electronic and mechanical properties of carbon nanotubes. The use of enriched semiconducting (sc) single-walled carbon nanotubes (SWCNT) significantly improves the performance of NTFET devices and enables label-free protein detection. To demonstrate that sensitive and specific detection of β2-Tf in biological fluids can be achieved by using NTFET biosensor platform, we have developed a three-step strategy for β2-Tf detection using NTFET devices. The three-step strategy for β2-Tf detection includes two steps of affinity chromatography to isolate β2-Tf and a rapid β2-Tf sensing step utilizing a high-purity sc-SWCNT FET device. Three different sensing configurations for the sc-SWCNT FET sensor were investigated for obtaining the optimal β2-Tf sensing results. Compared to current methods for CSF leak diagnosis, such as electrophoresis and imaging methods, our three-step strategy can offer high quality CSF leak detection with a short turnaround time (around 1 hour), easy instrument access and simple operations, which could potentially benefit medical treatment of traumatic brain injury (TBI) patients and other people in need. The versatility of our sensing platform could also open opportunities for point-of-care applications for other disease-related protein detection, as we have recently demonstrated by rapid detection of SARS-CoV-2 antigens for COVID-19 testing.

Detection of Stress Hormone with Semiconducting Single-Walled Carbon Nanotube-Based Field-Effect Transistors

Non-invasive detection and quantification of the stress hormone cortisol not only provide the assessment of stress level but also enable close monitoring of mental and physical health. In this work, we report two types of field-effect transistors (FETs) based on semiconducting single-walled carbon nanotubes (sc-SWCNTs) as selective cortisol sensors. In one FET device configuration cortisol antibody is directly attached to sc-SWCNTs, the other one is using gold nanoparticles (Au NPs) as linkers in between antibody and sc-SWCNTs to enhance the device conductance. We fabricated and characterized both device configurations to investigate how the nanomaterial interface to cortisol antibody influences the biosensor performance. We tested the sensors in artificial sweat and compared these two types of sensors in terms of limit of detection and sensitivity, and the results indicate that direct binding between antibody and sc-SWCNTs yields better biosensor characteristics.

Threshold voltage control of carbon nanotube-based synaptic transistors via chemical doping for plasticity modulation and symmetry improvement

Threshold voltage control of two-dimensional semiconductors enabled field-effect transistors (FETs) exhibits great potential for high-performance electronic and optoelectronic devices. However, few studies have paid attention to the threshold voltage tunability for the plasticity modulation of neuromorphic devices. Herein, a feasible chemical doping method was demonstrated to effectively modulate the electrical property of carbon nanotube-based FETs (CNFETs). The threshold voltage of CNFETs could be gradually adjusted by varying the doping concentration, annealing temperature, and annealing time. Moreover, pronounced hysteretic behaviors induced by the charge trapping/de-trapping process via the interface exhibited a strong dependence on AuCl3 doping, which provided a unique opportunity to emulate tunable synaptic plasticity. By AuCl3 doping, both excitatory and inhibitory synaptic behaviors were enhanced and an improved symmetry contributed to an increased recognition accuracy (∼98%) for the recognition of handwritten digits. This work provides an alternative strategy for plasticity modulation by chemical doping to develop future neuromorphic devices.

Machine learning-assisted calibration of Hg2+ sensors based on carbon nanotube field-effect transistors

Nanomaterial-based electronic sensors have demonstrated ultra-low detection limits, down to parts-per-billion (ppb) or parts-per-trillion (ppt) concentrations. However, these extreme sensitivities also make them susceptible to signal saturation at higher concentrations and restrict their usage primarily to low concentrations. Here, we report machine learning techniques to create a calibration method for carbon nanotube-based field-effect transistor (FET) devices. We started with linear regression, followed by regression splines to capture the non-linearity in the data. Further improvements in model performance were obtained with regression trees. Finally we lowered the model variance and further boosted the model performance by introducing random forest. The resulting performance as measured by R2 was estimated to be 0.8260 using out-of-bag error. The methodology avoids saturation and extends the dynamic range of the nanosensors up to 12 orders of magnitude in analyte concentrations. Further investigations of the sensing mechanism include analysis of feature importance in each of the model we tested. Functionalized nanosensors demonstrate selective detection of Hg2+ ions with detection limits 10−14.36±0.78 M, and maintain calibration to concentrations as high as 1 mM. Application of machine learning techniques to investigate which features in the FET signal maximally correlate with concentration changes provide valuable insight into the carbon nanotube sensing mechanism and assist in the rational design of future nanosensors.

Modulation of electrical properties in carbon nanotube field-effect transistors through AuCl<sub>3</sub> doping

Carbon nanotube-based field-effect transistors (CNFETs), as a new generation of nanodevices, are still difficult to apply to actual logic circuits due to the lack of a mature threshold voltage control mechanism. Here in this work, a feasible and large-scale processing surface doping method is demonstrated to effectively modulate the threshold voltage of CNFETs through the p-type doping effect of gold chloride (AuCl<sub>3</sub>). A comprehensive mapping from electrical parameters (<i>I</i><sub>on</sub>/<i>I</i><sub>off</sub>, <i>V</i><sub>th</sub> and mobility) to doping concentration is carefully investigated, demonstrating a p-doping effect induced by surface charge transfer between Au<sup>3+</sup> and carbon nanotube networks (CNTs). Threshold voltage of CNFETs can be effectively adjusted by varying the doping concentration. More importantly, the devices doped with low concentration AuCl<sub>3 </sub>exhibit good electrical properties including greatly improved electrical conductivity, 2–3 times higher in mobility than intrinsic carbon nanotubes. Furthermore, the effects of annealing on the electrical properties of the AuCl<sub>3</sub>-doping CNFETs are studied, demonstrating that the p-type doping effect reaches the optimized state at a temperature of 50 °C. Finally, first-principles calculation method is used to verify the doping control mechanism of Au<sup>3+ </sup>to carbon nanotubes. This research provides important guidance for realizing large-area low-power logic circuits and high-performance electronic devices in the future.

Hafnium oxide layer-enhanced single-walled carbon nanotube field-effect transistor-based sensing platform

Single-walled carbon nanotube-based field effect transistors (SWCNT-FETs) are ideal candidates for fabricating sensors and have been widely used for chemical sensing applications. SWCNT-FETs have low selectivity because of the environmentally sensitive electronic properties of SWCNTs, and SWCNT-FETs also show a high noise signal and poor sensitivity because of charge trapping from Si–OH hydration of the SiO2/Si substrate on the SWCNTs. Herein, poly (4-vinylpyridine) (P4VP) was used for noncovalent attachment to SWCNTs and selective binding to copper ions (Cu2+). Importantly, the introduction of a hafnium-oxide (HfO2) layer through atomic layer deposition (ALD) overcame the charge trapping by SiO2 hydration and remarkably decreased the interference signal. The sensitivity of the P4VP/SWCNT/HfO2-FET sensor for Cu2+ was 7.9 μA μM−1, which was approximately 100 times higher than that of the P4VP/SWCNT/SiO2-FET sensor, and its limit of detection (LOD) was as low as 33 pmol L−1. Thus, the P4VP/SWCNT/HfO2-FET sensor is a promising candidate for the development of Cu2+-selective sensors and can be designed for the large-scale manufacturing of custom-made sensors in the future.

Sensitivity control of carbon nanotube-based piezoresistive sensors by drain-induced barrier thinning

The sensor characteristics of a membrane-based carbon nanotube (CNT) sensor showing maximum gauge factors of up to 810 is analyzed by a device study combining technological and theoretical approaches. Drain-induced barrier thinning (DIBT) is found to contribute significantly to this high sensitivity by a modification of the Schottky barrier width at the CNT-metal junctions. A high threshold voltage roll-off of (1370±130) mV⋅V-1 and degradation of subthreshold swing is observed even for channel length of 200 nm. The piezoresistive behavior of the CNT sensor running in the DIBT regime shows up as a complex and input-voltage dependent interplay of strain-dependent Fowler-Nordheim tunneling and the intrinsic thermionic resistance change. We demonstrate, that this interplay can be controlled by the applied bias voltages VGS and VDS in such a way, that the overall gauge factor is enhanced up to 150% with respect to the intrinsic effect. The control of the gauge factor via VDS is enabled by the DIBT effect, which appears for our CNT device at remarkably long CNT-channels.The experimental findings are retraced by a simplified transport model, which combines a numerical device solver with an electronic charge transport model for strained carbon nanotube based field-effect transistors (CNT-FETs) considering thermionic as well as tunneling contributions to the overall conductance. Strain dependent tunneling through the Schottky barriers appears to be the key contribution to the strain sensitivity in our model. Device characteristics have been derived from the model which reproduce the experimental findings emphasizing the significance of tunneling processes in combination with DIBT for the superior strain sensitivity of our device.

Machine-Learning Identification of the Sensing Descriptors Relevant in Molecular Interactions with Metal Nanoparticle-Decorated Nanotube Field-Effect Transistors.

Carbon nanotube-based field-effect transistors (NTFETs) are ideal sensor devices as they provide rich information regarding carbon nanotube interactions with target analytes and have potential for miniaturization in diverse applications in medical, safety, environmental, and energy sectors. Herein, we investigate chemical detection with cross-sensitive NTFETs sensor arrays comprised of metal nanoparticle-decorated single-walled carbon nanotubes (SWCNTs). By combining analysis of NTFET device characteristics with supervised machine-learning algorithms, we have successfully discriminated among five selected purine compounds, adenine, guanine, xanthine, uric acid, and caffeine. Interactions of purine compounds with metal nanoparticle-decorated SWCNTs were corroborated by density functional theory calculations. Furthermore, by testing a variety of prepared as well as commercial solutions with and without caffeine, our approach accurately discerns the presence of caffeine in 95% of the samples with 48 features using a linear discriminant analysis and in 93.4% of the samples with only 11 features when using a support vector machine analysis. We also performed recursive feature elimination and identified three NTFET parameters, transconductance, threshold voltage, and minimum conductance, as the most crucial features to analyte prediction accuracy.