Gate Control Research Articles

Doping- and capacitor-less 1T-DRAM cell using reconfigurable feedback mechanism.

In this paper, we propose a doping- and capacitor-less 1T-DRAM cell, which achieved virtual doping by leveraging charge plasma and bias-induced electrostatic doping (bias-ED) techniques in a 5-nm-thick intrinsic silicon body, thereby eliminating doping processes. Platinum was in contact with the drain, while aluminum was in contact with the source, enabling virtual doping of the silicon body into a p*-i-n* configuration via the charge-plasma technique. Two coupled polarity gates and one control gate are positioned above the intrinsic channel region. The intrinsic channel region is virtually doped through the bias-ED by applying voltages to the gates, forming potential wells inside the channel. The voltage applied to the two coupled polarity gates determines whether the device operates in the p- or n-channel mode, whereas the control gate governs the flow of charge carriers. Charge carriers are stored and released in the potential wells inside the channel by adjusting the gate, effectively replacing the capacitor. In this device, the placement of polarity gates on either side of the control gate enables the observation of the reconfigurable characteristics. Moreover, the proposed device utilizes a feedback mechanism, enabling excellent memory characteristics such as a high on/off current ratio of ~10^9, steep switching behavior of ~0.2 µV/dec, short write time of 10 ns, long hold retention of over 100 s, and long read retention of over 600 s.

Predicting arbitrary state properties from single Hamiltonian quench dynamics

Analog quantum simulation is an essential routine for quantum computing and plays a crucial role in studying quantum many-body physics. Typically, the quantum evolution of an analog simulator is largely determined by its physical characteristics, lacking the precise control or versatility of quantum gates. This limitation poses challenges in extracting physical properties on analog quantum simulators, an essential step of quantum simulations. To address this issue, we introduce the protocol, which uses a single quench Hamiltonian for estimating arbitrary state properties, eliminating the need for ancillary systems and random unitaries. Additionally, we derive the sample complexity of this protocol and show that it performs comparably to the classical shadow protocol. The Hamiltonian shadow protocol does not require sophisticated control and can be applied to a wide range of analog quantum simulators. We demonstrate its utility through numerical demonstrations with Rydberg atom arrays under realistic parameter settings. The new protocol significantly broadens the application of randomized measurements for analog quantum simulators without precise control and ancillary systems. Published by the American Physical Society 2024

Alpha Traveling Waves during Working Memory: Disentangling Bottom-up Gating and Top-down Gain Control.

While previous works established the inhibitory role of alpha oscillations during working memory maintenance, it remains an open question whether such an inhibitory control is a top-down process. Here, we attempted to disentangle this issue by considering the spatio-temporal component of waves in the alpha band, i.e., alpha traveling waves. We reanalyzed two pre-existing and open-access EEG datasets (N = 180, 90 males, 80 females, 10 unknown) where participants performed lateralized, visual delayed match-to-sample working memory tasks. In the first dataset, the distractor load was manipulated (2, 4, or 6), whereas in the second dataset, the memory span varied between 1, 3, and 6 items. We focused on the propagation of alpha waves on the anterior-posterior axis during the retention period. Our results reveal an increase in alpha-band forward waves as the distractor load increased, but also an increase in forward waves and a decrease in backward waves as the memory set size increased. Our results also showed a lateralization effect: alpha forward waves exhibited a more pronounced increase in the hemisphere contralateral to the distractors, whereas the reduction in backward waves was stronger in the hemisphere contralateral to the targets. In short, the forward waves were regulated by distractors, whereas targets inversely modulated backward waves. Such a dissociation of goal-related and goal-irrelevant physiological signals suggests the co-existence of bottom-up and top-down inhibitory processes: alpha forward waves might convey a gating effect driven by distractor load, while backward waves may represent direct top-down gain control of downstream visual areas.Significance Statement When exploring the functional role of alpha band neural oscillations during working memory, mostly amplitude modulations have been considered so far, with relatively limited exploration of spatial-temporal dynamics of this rather global brain oscillatory signature. The present study seeks to address this gap by examining the directionality of alpha wave propagation during working memory retention. Our findings offer novel insights into the well-established inhibitory role of alpha waves, demonstrating that this function is manifested differently according to their propagation directions: forward waves seem to facilitate bottom-up gating, while backward waves might mediate top-down gain control.

Device to circuit level implementation of JL-NSFET for DC/analog/RF applications at sub-5nm technology node: design optimization and temperature analysis

Abstract This manuscript introduces, for the first time, a novel approach that incorporates a comprehensive analysis of sheet variations (1–5) and every individual sheet wise temperature variation, and as well as an investigation of various GS high-k gate dielectrics in Junction-less (JL) Nanosheet FET (JL-NSFET). The study starting from device level (Digital/Analog/Radio Frequency) to circuit (CMOS Inverter and ring oscillator) as a whole package is investigated through well calibrated TCAD simulation and the results portrayed. NSFETs are the ultimate choice for integrated circuits (ICs) at sub-5 nm technology node. The notion of this paper is to design and optimization of NSFET with GS high-k gate dielectrics (Al2O3, HfO2, ZrO2 and TiO2) Initially. The switching/analog and RF metric revels that HfO2 is superior in terms SS, switching applications and more compactable with CMOS process. Further, adding number of sheets and temperature variation has been done later. As number of sheets increases, the effective channel width increases, electric field distribution takes place evenly and enhanced gate control owing to improved I O N , I O N / I O F F r a t i o , SS and DIBL. However, increasing the number of vertical channel layers (sheets) more than 2 results into diminished analog/RF performance of JL-NSFET owing to increased parasitic capacitances. Further, the impact of temperature variations (250 K to 450 K) studied for different sheet variations (1 to 5) and noticed that analog/RF such as gm, gds, fT, TFP and GTFP are enhanced by 40.82%, 28.76%, 40.69%, 64.62% and 70.59%, respectively at lower temperature (250 K) when compared to high temperature (450 K). These enhancements make the device is ideal for applications in cryogenic computing systems, satellites, deep space probes, and other aerospace technologies. Furthermore, as the circuit level implementation CMOS inverter and 5-stage ring oscillator (RO) are examined for different sheets and observed as sheets increase delay and EDP increases. For a CMOS inverter the NMH (0.295 V) and NML (0.280 V) are better at 2 sheets with a highest gain of 9.38 V/V. Hence, it is advised to use two or three sheets-based JL-NSFETs for high-performance and lower-power analog/RF applications.

Ultra-sensitive dengue NS1 protein detection via asymmetric source-drain, heterojunction and dual-dielectric cavities in a uniform tunnel FET biosensor

In this paper, we present a unique Asymmetric Source-Drain Heterojunction Dual-Dielectric Uniform Tunnel Field Effect Transistor (A-SD-HJ-DD-UTFET) based biosensor tailored for the early detection of dengue NS1 protein during the acute phase of infection offering early diagnosis and potentially life-saving intervention. The proposed biosensor design features simplified fabrication, a narrow drain region, and a dual material control gate, enhancing specificity and sensitivity for dengue virus detection. Using a heterojunction configuration, this device optimizes electron flow for improved detection accuracy. The roles of Tunnel Gate (TG) and Auxiliary Gate (AG) are studied in terms of band energy, electric field, electrostatic potential, and other sensitivity parameters. Sentaurus TCAD tool is utilized for analyzing the characteristics of the proposed A-SD-HJ-DD-UTFET biosensor. Simulation results indicate that the designed A-SD-HJ-DD-UTFET biosensor achieves a superior Subthreshold Swing (SS) of 15.4 mV/dec and an enhanced ION/IOFF sensitivity of about 2.25 × 10¹¹ with a maximum ON and minimum OFF state currents of 2.28 × 10–4 A/μm and 1.28 × 10–16 A/μm respectively for detecting NS1 protein of dengue. Additionally, it boasts a high switch ratio in the order of 1012. The proposed biosensor outperforms conventional devices, including the state-of-the-art Junctionless (JL)-TFET biosensors. The superior electrical characteristics of the proposed A-SD-HJ-DD-UTFET biosensor make it a promising device for early detection of the dengue NS1 protein, providing a potent solution for mitigating the spread of dengue infections.

Evolution mechanism of physical morphology of oxbow lake in the middle Yangtze River

Oxbow lakes, formed through river meandering cutoffs, are recognized as key components of river ecosystems, characterized by both fluvial and lacustrine features. The focus of previous research has been placed primarily on post-disconnection changes, leaving gaps in the understanding of their long-term morphological evolution. This gap is addressed through a comparative analysis of gate-controlled and naturally connected oxbow lakes over a 30-year period. In this study, Tian’ezhou Lake (gate-controlled) and Shangchewan Lake (naturally connected), located in the middle Yangtze River, are investigated. Key morphological parameters such as curvature, shoreline development index, and shrinkage rate were measured using Google Earth Engine (GEE). The influence of hydrological and meteorological factors on lake morphology was analyzed through Redundancy Analysis (RDA). Significant morphological changes were observed from 1990 to 2000. During this period, Tian’ezhou’s curvature was found to increase by 0.003/year, while Shangchewan’s curvature decreased by 0.011/year. After the construction of the Three Gorges Dam (TGD), a reduction in the rate of morphological evolution was detected, particularly between 2000 and 2010, when Tian’ezhou’s curvature decreased by 0.071/year and Shangchewan’s increased by 0.04/year. Post-2010, no significant changes in planar morphology were recorded in either lake. It was revealed by RDA that annual precipitation from 1990 to 1999 played a dominant role in influencing the morphological evolution of both lakes. From 2000 to 2020, water level fluctuations and hydrological connectivity emerged as the primary drivers. Gate control at Tian’ezhou Lake mitigated extreme water level fluctuations, contributing to a more stable environment and a slower rate of morphological evolution compared to Shangchewan. The findings underscore the importance of balanced water management strategies, integrating both natural and engineered hydrological interventions. Practical guidance is provided for ecological restoration and river management, with an emphasis on maintaining stable habitats and ensuring ecosystem resilience in response to hydrological changes.

Multi-point temperature or humidity prediction for office building indoor environment based on CGC-BiLSTM deep neural network

The aim of this study is to predict the temperature or humidity changes at multiple relevant points in a building using a deep neural network architecture with multi-task learning to provide more reference information for the design and optimal operation of heating and ventilation systems. For this purpose, traditional multi-task prediction algorithm architecture is combined with Customized Gate Control and other neural networks to build deep neural network architectures for indoor environments with multi-point temperature or humidity prediction tasks. To test the prediction effectiveness of the architecture, a task of predicting temperature or humidity 24h in advance was designed on a real office building indoor environment dataset, and the prediction results were compared with other single-task and multi-task prediction models. Two experimental conditions were designed for this study, one using the complete training set and the other reducing the training set at a certain point. Through the final prediction results, it is found that the multi-task prediction architecture used in this paper shows better or nearly optimal results compared to other prediction models under both working conditions. This study provides some reference value for the application of multi-task prediction algorithms to the task of predicting indoor environments in buildings.

Scrambler Therapy: thinking beyond the gate control theory

Scrambler Therapy: thinking beyond the gate control theory

Gate control of superconducting current: Mechanisms, parameters, and technological potential

In conventional metal-oxide semiconductor (CMOS) electronics, the logic state of a device is set by a gate voltage (VG). The superconducting equivalent of such effect had remained unknown until it was recently shown that a VG can tune the superconducting current (supercurrent) flowing through a nanoconstriction in a superconductor. This gate-controlled supercurrent (GCS) can lead to superconducting logics like CMOS logics, but with lower energy dissipation. The physical mechanism underlying the GCS, however, remains under debate. In this review article, we illustrate the main mechanisms proposed for the GCS, and the material and device parameters that mostly affect it based on the evidence reported. We conclude that different mechanisms are at play in the different studies reported so far. We then outline studies that can help answer open questions on the effect and achieve control over it, which is key for applications. We finally give insights into the impact that the GCS can have toward high-performance computing with low-energy dissipation and quantum technologies.

Analytical Modeling of Silicon Nanowire Dielectric Modulated Reconfigurable FET Biosensor

Abstract In this paper, we present an analytical modeling of a Silicon Nanowire Dielectric Modulated Reconfigurable FET (SiNW-DMRFET) biosensor having a cavity under the control gate. By employing the 2D Poisson equation, we accurately model the electrostatic characteristics of the proposed biosensor such as surface potential, threshold voltage, electric field, and drain current. The main parameters used to identify biomolecules present in the cavity are the variations detected in the threshold voltage (VTH ) and ON-current. The simulated and analytical results are compared with the performance of the published literature. We validate the reliability of our analytical approach by conducting simulations of the proposed device on Silvaco TCAD tool. The research conducted through both theoretical and experimental studies indicated that the proposed biosensor exhibited significant improvements in its sensitivity to ION and VTH . Specifically, there was a rise of 54.65% in ION sensitivity and 85.71% in VTH sensitivity. Furthermore, we show that our model is accurate and reliable by carefully comparing the results of our analysis with the results of the simulation.

The only constant is change: Stable vs. variable aspects of food approach bias relate differently to food craving and intake

The tendency to approach food faster than to avoid it (i.e., approach bias) is thought to facilitate food intake, particularly foods that conflict with one's dietary goals. However, this relationship has been difficult to demonstrate, which ties into an ongoing debate about whether such cognitive-behavioral biases represent stable traits or fluctuating states. We thus investigated the temporal fluctuations of food approach bias (1), its within-participant association with food craving (2) and intake (3), and the role of top-down control in this bias-intake association (4). The 76 participants completed an impulsivity questionnaire and performed a smartphone-based approach-avoidance task on nine days. Every day, they also reported their daily craving, intake, and dietary intentions for 12 personalized foods they wanted to eat less or more often over the study period. Approach bias varied considerably within individuals (1), and correlated in unexpected ways with food craving (2) and intake (3); this association of approach bias with intake was moderated by inter-individual differences (rather than day-to-day fluctuations) in dietary intentions and impulsivity (4). Results emphasize the need to re-conceptualize approach bias as comprising both state and trait components, and indicate that the more trait-like aspects of top-down control gate the relationship of approach bias with intake. The large day-to-day variation in approach bias may explain why single-session bias measures often do not predict distal outcomes like body weight. Furthermore, our results suggest that interventions targeting approach bias may be most effective for certain timepoints (high-risk situations) and individuals (those with weak dietary intentions).

A Study on the Channel Holes’ Diameter Effects of High-Performance Vertical-Channel Flash Memory Cells

Abstract High-performance vertical-channel flash (HVF) memory cells were fabricated on the single crystalline Si (c-Si) sidewalls of the cylindrical deep wells in c-Si substrate. To investigate the diameter effects of the cylindrical deep wells, namely channel holes, on HVF cells, the channel holes with different diameters, ranging from 65 nm to 260 nm, were made. Memory gate stacks of SiO2/ Al2O3/HfO2/Al2O3/TiN/W were formed by ozone oxidation and then ALD with the deposition thicknesses of 1/5/7/8/2/150 nm, respectively. For the devices with their diameters equal to or greater than 150 nm, their electrical properties, such as Vt, SS, DIBL, and program/erase characteristics, are close. As expected, DIBL and SS become better as the diameter increasing due to better gate control with larger diameter. However, large changes were occurred for the devices with the diameters of 90 nm and 65 nm. A simple model based on cylinder bulk for vertical flash memory devices was presented to obtain an approximate analytical solution for depletion-width and explain our experimental data. For the devices with the diameters of 150 nm, the high On/Off current ratio of 107 and relatively large memory window of 4.5 V were achieved. However, programming/erasing efficiency were degraded with hole diameter decreasing.

A framework for a low-cost system of automated gate control in assays of spatial cognition in fishes.

Automation of experimental setups is a promising direction in behavioral research because it can facilitate the acquisition of data while increasing its repeatability and reliability. For example, research in spatial cognition can benefit from automated control by systematic manipulation of sensory cues and more efficient execution of training procedures. However, commercial solutions are often costly, restricted to specific platforms, and mainly focused on the automation of data acquisition, stimulus presentation, and reward delivery. Animal welfare considerations as well as experimental demands may require automating the access of an animal or animals to the experimental arena. Here, we provide and test a low-cost, versatile Raspberry Pi-based solution for such use cases. We provide four application scenarios of varying complexities, based on our research of spatial orientation and navigation in weakly electric fish, with step-by-step protocols for the control of gates in the experimental setups. This easy-to-implement, platform-independent approach can be adapted to various experimental needs, including closed-loop as well as field experiments. As such, it can contribute to the optimization and standardization of experiments in a variety of species, thereby enhancing the comparability of data.

Design and Development of a Prototype Water Level Control System for Early Flood Detection Based on The Internet of Things: a Case Study of Kambaniru Dam

Flooding can occur due to overflowing water during the rainy season, therefore early detection of the water level in dams as water runoff processing structures is needed. When heavy rain occurs it can result in flood disasters that are detrimental to communities, dam infrastructure and agricultural land. This research aims to monitor water levels online as initial information about impending flood disasters. Monitoring using Internet of Things (IoT) based technology is intended to obtain water level information in real time. In this device the HC-SR04 ultrasonic sensor is used as a water level reader, a waterflow sensor as a water discharge reader and a servo motor as a sluice gate controller. The results of this research are a prototype of a water level detection device that can provide water level information and can control sluice gates. automatically and can be controlled manually or remotely via the latest notifications in the Blynk application using the MQTT protocol. This research was carried out by taking information based on the results of direct observations and interviews with officers at Kambaniru Dam, Lambanapu Village, Kambera District. In this way, the prototype of this detection tool will be easy to use as initial information about the possibility of flooding.

High-Performance Dual-Gate Transistors Based on Aligned Carbon Nanotubes.

Aligned carbon nanotubes (A-CNTs), with atomic-scale thickness and ultrahigh carrier mobility, hold promise for constructing future sub-1 nm node integrated circuits (ICs) with higher speed and lower power consumption. However, the fabricated A-CNT transistors often suffer from the disorder of high-density CNT, which degrade the off-characteristic deviating significantly from theoretical values. Introducing a dual-gate (DG) configuration can provide higher gate control efficiency compared to conventional single-gate (SG) transistors and is expected to enhance the overall performance of A-CNT transistors. However, the reported A-CNT dual-gate field-effect transistors (DG-FETs) still exhibit nonideal switching behavior, and systematic exploration and optimizations for constructing high-performance A-CNT DG structures have been lacking so far. In this work, we conducted a detailed study on the matching issues between the top-gate (TG) and bottom-gate (BG) stacks. By optimizing the gate metal materials and dielectric layer thickness, we enabled 20 nm channel A-CNT DG-FETs to achieve leading switching characteristics, including an on-state current density (Ion) of up to 1.47 mA/μm, a peak transconductance (Gm) of 2 mS/μm, a subthreshold slope (SS) as low as 83 mV/decade, and a current on/off ratio of 106. This study provides critical experimental guidance for constructing outstanding A-CNT DG-FETs at advanced technology nodes to compete with cutting-edge silicon-based chips and is also valid for two-dimensional channels.

Efficacy for aspiration prevention through thickening of liquid foods evaluated using a swallowing model apparatus

Abstract An apparatus simulating the swallowing process of liquid foods was constructed using a flow channel. In the channel, a circular cylindrical obstruction was fixed to serve as an epiglottis in the mesopharynx. The apparatus was designed with an adjustable gate for flow control to represent the processes of healthy swallowing and dysphagia. The parameters considered were the holding time and flow resistance controlled by the gate, which were assumed to indicate the swallowing reflex and power, respectively. When a Newtonian liquid with relatively low viscosity was used, the flow experiment performed using the apparatus under conditions of shorter holding time and larger flow resistance successfully reproduced a phenomenon similar to aspiration in a patient with dysphagia. In addition to a Newtonian liquid with high viscosity, non-Newtonian liquids thickened to various concentrations using commercially available thickeners were used. In flow experiments with these test liquids, the efficacy for aspiration prevention was inferred based not only on the viscosity of the liquid but also its elasticity, depending on its viscosity.

Task-Level Customized Pruning for Image Classification on Edge Devices

Convolutional neural networks (CNNs) are widely utilized in image classification. Nevertheless, CNNs typically require substantial computational resources, posing challenges for deployment on resource-constrained edge devices and limiting the spread of AI-driven applications. While various pruning approaches have been proposed to mitigate this issue, they often overlook a critical fact that edge devices are typically tasked with handling only a subset of classes rather than the entire set. Moreover, the specific combinations of subcategories that each device must discern vary, highlighting the need for fine-grained task-specific adjustments. Unfortunately, these oversights result in pruned models that still contain unnecessary category redundancies, thereby impeding the potential for further model optimization and lightweight design. To bridge this gap, we propose a task-level customized pruning (TLCP) method via utilizing task-level information, i.e., class combination information relevant to edge devices. Specifically, TLCP first introduces channel control gates to assess the importance of each convolutional channel for individual classes. These class-level control gates are then aggregated through linear combinations, resulting in a pruned model customized to the specific tasks of edge devices. Experiments on various customized tasks demonstrate that TLCP can significantly reduce the number of parameters, by up to 33.9% on CIFAR-10 and 14.0% on CIFAR-100, compared to other baseline methods, while maintaining almost the same inference accuracy.

Deep brain stimulation of the motor thalamus relieves experimentally induced air hunger.

We previously reported that Deep Brain Stimulation (DBS) of motor thalamus (MT), in a patient with post-stroke tremor, relieved breathlessness associated with chronic obstructive pulmonary disease. This raised the question of whether MT DBS mitigates the ascending dyspnoea signal. We therefore sought to conduct a fully powered cohort study of experimentally induced air hunger (AH), an uncomfortable urge to breathe in patients with MT DBS ON and OFF. 16 patients (3 females) with DBS of the ventral intermediate nucleus (VIM) as treatment for tremor, underwent hypercapnic AH tests, with DBS "ON" and "OFF". Patients rated AH on a visual analogue scale (VAS) every 15 s. Hypercapnia and ventilation were matched for ON and OFF states (mean±sd 43±4 and 43±4 mmHg for end-tidal PCO2, 13.7 and 13.4 L·min-1 for ventilation). Participants ventilation was constrained to baseline levels by breathing from a 3-litre inspiratory reservoir with fixed flow of fresh gas while targeting their resting breathing frequency to a metronome. Overall steady state AH was 52±28%VAS for "ON" and 67±20%VAS for "OFF" (p=0.002; two-tailed paired t-test). The mean reduction in AH during VIM DBS was -14.4%VAS. MT DBS relieved AH in thirteen patients, heightened AH in two and caused no change in one. MT DBS for tremor relief also mitigates the AH component of dyspnoea. We posit that DBS of the MT heightens the gating control of the thalamus modulating the ascending air hunger signal. Extent of relief suggests that thalamic DBS may prove to be a viable therapy for intractable dyspnoea.

An Efficient Time‐Sensitive Networking Traffic Scheduling Method for Train Communication Network

As a critical system of rail train, the train communication network (TCN) is an integrated central platform that is used to realize the train operation control, condition monitoring, and data transmission. With the development of train intelligence, the scale of data flow in TCN continues to expand, and the control data and monitoring data must be real‐time transmitted to ensure the safe and reliable operation of the train. Time‐sensitive network (TSN) can be applied as the next‐generation TCN solution, which provides end‐to‐end data transmission with extremely low delay and high reliability based on Ethernet. For the application of TSN technology in TCN, a single frame simple scheduling method is proposed to effectively reduce the worst end‐to‐end delay of the entire network, which improve the real‐time performance of TSN‐based TCN. The network topology and data flow characteristics in TCN are analyzed, a series of scheduling constraints are constructed, and the satisfiability modulo theories (SMT) is used to obtain a gate control list (GCL) to ensure the real‐time performance of time‐trigger streams. Finally, the TCN simulation model is established using OMnet++ software, the experiment results show that the proposed method can effectively reduce the overall delay and jitter, and meet the real‐time requirement of TCN. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Label-free biomolecule detection with dielectrically modulated double gate single cavity InGaAs/GaAsSb HTFET: Design considerations and performance evaluation

Dielectrically Modulated Double Gate Single Cavity InGaAs/GaAsSb HTFET (DMDG–SC–InGaAs/GaAsSb HTFET) is a novel label-free, nanocavity embedded dielectrically modulated heterostructure TFET-based biosensor. The III-V heterostructure (InGaAs/GaAsSb) has a high ION/IOFF ratio, better gate control, and higher tunnelling probability. In order to effectively reduce ambipolarity, asymmetrical doping is used at the p+ source and n+ drain, along with gate work function engineering. The stacked layers of HfO2/SiO2 gate oxide help to reduce the fringing electric field. The suggested device utilizes a dielectrically controlled technique to achieve biomolecule conjugation. This is done by etching a single nanogap cavity in the gate dielectric material towards the source end. An evaluation of the dielectric constants [K = 2.1, 2.63, 3.30, 6.3, and 12] of neutral and charged biomolecules compared to air [k = 1] is essential to determine the sensitivity of biosensors in an arid environment. The transconductance-to-current ratio (gm/Ids), switching ratio (ION/IOFF), and threshold voltage are the performance metrics used to evaluate the device sensitivity. The DM-DG–SC–InGaAs/GaAsSb HTFETpromises to be very sensitive while using less power during the detection process. It also shows that it could be a good choice for label-free biosensor applications.