Capacitive Coupling Research Articles

A Class-E-Based Multichannel Auxiliary Power Supply With Individual Hysteresis Control

A high performance auxiliary power supply (APS) with multiple isolated outputs plays a crucial role in ensuring the effective operation of power converter systems. An isolated resonant current source converter is usually adopted as the APS in medium-voltage (MV) applications with the advantages of low coupling capacitance and high insulation strength. In this paper, a Class E-based multichannel APS, featuring a low component count, modular circuit structure and ease of scalability to multiple output channels, is proposed. The operation principle of the proposed circuit is presented in detail. To overcome the cross-regulation problem in multiple outputs, an individual hysteresis control approach is introduced to regulate each output separately and decouple the multiple outputs. The converter performance under open/short-circuit fault conditions is also explored with the proposed control scheme. Design considerations, including the zero-voltage-switching (ZVS) realization and the output power capabilities, are presented, together with a step-by-step parameter design approach. Finally, an 8 output APS experimental prototype (with different output voltage levels) is presented. The experimental results demonstrate the output voltage decoupled regulation and load independent ZVS performance of the prototype.

A New Cuk-Based DC-DC Converter with Improved Efficiency and Lower Rated Voltage of Coupling Capacitor

DC-DC converters play a crucial role in recent and advanced applications, enabling efficient power conversion and management for renewable energy systems, electric vehicles, portable devices, and advanced communication systems. In line with this, the objective of this paper is to introduce a new DC-DC configuration based on the Cuk converter named as Mahafzah converter, which utilizes a coupling capacitor with a lower rated voltage. The paper aims to demonstrate the effectiveness of the proposed converter in terms of improved efficiency, reduced size, and reduced semiconductor device currents compared to the conventional Cuk converter. The proposed configuration comprises the same components as the Cuk converter, but in a different arrangement, without any additional elements. The main advantage of the proposed converter is using a coupling capacitor with a much lower rated voltage than the Cuk converter, resulting in a smaller capacitor size, reduced printed circuit board (PCB) size, and manufacturing cost. Additionally, the proposed converter reduces the currents of the semiconductor devices compared to those in the Cuk converter. To demonstrate its effectiveness, the converter is operated under continuous current mode (CCM) with a constant duty cycle and switching frequency. The study provides an in-depth discussion of the various operating modes by making use of equations relating to currents, voltages, duty cycles, and voltage gains. It also provides detailed illustrations of the limits between CCM and discontinuous current mode (DCM). The effectiveness of the proposed converter is demonstrated through a design example with operating parameters of 1 kW, 200 V/−300 V, and 20 kHz. Additionally, a low voltage–low power prototype (12/−18 V, 3.24 W, 20 kHz) is established to verify the operation of the proposed converter. Simulation and experimental verification of the proposed configuration achieved the desired results to improve efficiency and reduce the rate. The results clearly indicate that the efficiency of the proposed converter surpasses that of the conventional Cuk converter under identical operating conditions, reaching approximately 88% at rated load conditions.

Automated Extraction of Capacitive Coupling for Quantum Dot Systems

Single electrons trapped on semiconductor-defined quantum dots (QDs) are a promising platform for large-scale quantum computing. The authors demonstrate a reliable, automated method to identify the capacitive coupling between QDs. The approach combines machine learning with traditional fitting, to take advantage of the desirable properties of each. Also, analysis of cross capacitance may be used for automatic identification of the spurious QDs that occasionally form during device tuning. These techniques can autonomously flag devices with spurious dots near the operating regime, which is crucial information for reliable tuning for qubit operations.

Fractional model of the chemical inductor

A multitude of materials and processes of a different nature frequently exhibit, in addition to the classical capacitive arcs, inductive loops in the complex impedance plane. It is a stable and physically robust response originated, from a mathematical perspective, by the introduction of a capacitive coupling in the slow relaxation variable. Nevertheless, the dynamical behavior of such systems shows, in reality, pronounced experimental deviations from the ideal inductive behavior. For this reason, the scientific community in general claims for the development of a novel theory that helps to phenomenologically interpret this pattern change, also encompassing the associated inherent physical complexity that capitalizes on the vast majority of real-world processes. Here, we present a generalization of the classical fast-slow models to naturally explain the anomalous dynamics observed experimentally in different types of measurement techniques, such as the inductance dispersion in impedance, the fractional relaxation processes with negative spike components in the transient responses, and the inverted current-voltage hysteresis. From numerical simulations, we analyze in detail the crossover dynamics from capacitive to inductive properties from the perspective of the constant phase element. Our work devises a useful theoretical framework that explains, in frequency and time domain, the coexistence of dispersive features and the transformation of the electrical behavior in terms of an anomalous bifractional crossover. Finally, we show the dominant role of the fractional-order dynamics in the appearance of inverted hysteresis commonly found in current-voltage curves. Although in literature, everything looks, in a certain manner, simple, the reality is that many real-world materials exhibit an intricate and complex nature that leads to anomalous processes evidenced by dispersive dynamics observed through different measurement techniques. This change of pattern analyzed here is appealing as a mathematical tool to interpret the physical phenomena of many familiar systems.

CNN-Cap: Effective Convolutional Neural Network-based Capacitance Models for Interconnect Capacitance Extraction

Accurate capacitance extraction is becoming more important for designing integrated circuits under advanced process technology. The pattern matching-based full-chip extraction methodology delivers fast computational speed but suffers from large error and tedious efforts on building capacitance models of the increasing structure patterns. In this work, we propose an effective method for building convolutional neural network (CNN)-based capacitance models (called CNN-Cap) for two-dimensional (2-D) and three -dimensional (3-D) interconnect structures. With a novel grid-based data representation, the proposed method is able to model 2-D pattern structure and 3-D window structure with a variable number of conductors to largely reduce the number of patterns or increase the accuracy. Based on the ability of ResNet architecture on capturing spatial information and the proposed training skills, the obtained CNN-Cap exhibits much better performance over the multilayer perception neural network-based capacitance model while being more versatile. Extensive experiments on a 55 nm and a 15 nm process technologies have demonstrated that the error of total capacitance produced with 2-D CNN-Cap is always within 1.3%, and the error of produced coupling capacitance is less than 10% in over 99.5% probability. For 3-D structures, CNN-Cap predicts the total capacitance with less than 5% error in 99% probability and with a maximum error of 7.7%. For the tested 2-D and 3-D structures, the CNN-Cap run on a GPU server is more than 4,000× and 12,000×, respectively, faster than the conventional field solver Raphael, while consuming negligible memory.

Bio-Inspired Circular-Polarized UHF RFID Tag Design Using Characteristic Mode Analysis

This paper presents a bio-inspired circularly polarized ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna for metallic and low-permittivity substances. This tag design is based on a leaf-shaped radiator, two shorting stubs and slots etched on F4B substrate. Initially, the tag antenna is designed using characteristics mode analysis (CMA) by analyzing the first six CM modes and characteristic angles. The width of orthogonal slots is varied to get the resonance of CM modes in the required US RFID band. Moreover, the edges are blended to get orthogonal current distribution, which is necessary for circular polarization. Additionally, the proposed tag design is optimized further using CST Microwave studio and an RFID chip is exploited as a capacitive coupling element (CCE) to run CM modes with the orthogonal current pattern. This tag can also be tunable to European RFID (EU) band (866 – 868 MHz) by changing the length of shorter diagonal slot. The tag design offers a read range of 7 m and 4.5 m on 100 × 100 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> metals plate and low-permittivity substrates, respectively (for 902 – 928 MHz band). In EU band, the corresponding read ranges are 5.7 m and 3.5 m above metal and low-permittivity objects, respectively. This circularly polarized tag antenna is advantageous in terms of cost, circular polarization feature, and ease of fabrication due to the absence of vias, shorting pins, and matching circuits. Therefore, this tag design is suitable for labeling various low-permittivity objects, industrial conveyer belt applications, baggage handling systems, and IoT applications.

Wearable Triboelectric Nanogenerator with Ground-Coupled Electrode for Biomechanical Energy Harvesting and Sensing.

Harvesting biomechanical energy for electricity as well as physiological monitoring is a major development trend for wearable devices. In this article, we report a wearable triboelectric nanogenerator (TENG) with a ground-coupled electrode. It has a considerable output performance for harvesting human biomechanical energy and can also be used as a human motion sensor. The reference electrode of this device achieves a lower potential by coupling with the ground to form a coupling capacitor. Such a design can significantly improve the TENG's outputs. A maximum output voltage up to 946 V and a short-circuit current of 36.3 μA are achieved. The quantity of the charge that transfers during one step of an adult walking reaches 419.6 nC, while it is only 100.8 nC for the separate single-electrode-structured device. In addition, using the human body as a natural conductor to connect the reference electrode allows the device to drive the shoelaces with integrated LEDs. Finally, the wearable TENG is able to perform motion monitoring and sensing, such as human gait recognition, step count and movement speed calculation. These show great application prospects of the presented TENG device in wearable electronics.

Customized predictions of the installed cost of behind-the-meter battery energy storage systems

Behind-the-meter (BTM) battery energy storage systems (BESS) are undergoing rapid deployment. Simple equations to estimate the installed cost of BTM BESS are often necessary when a rigorous, bottom-up cost estimate is not available or not appropriate, in applications such as energy system modeling, informing a BESS sizing decision, and cost benchmarking. Drawing on project-level data from California, I estimate several predictive regression models of the installed cost of a BTM BESS as a function of energy capacity and power capacity. The models are evaluated for in-sample goodness-of-fit and out-of-sample predictive accuracy. The results of these analyses indicate stronger empirical support for models with natural log transformations of installed cost, energy, and power as compared against widely-used models that posit a linear relationship among the untransformed versions of these variables. Building on these results, I present a logarithmic model that can predict installed cost conditional on energy capacity, power capacity, AC or DC coupling with distributed generation, customer sector, and local wages for electricians. I document how the model can be easily extrapolated to future years, either with forecasts from other sources or by re-estimating the parameters with the latest data.

Modelling and analysis of contactless sensor for TSV fault based on resonant inductive coupling

In order to solve the problems of inefficient detection, high cost, and high damage rate of existing Through Silicon Via (TSV) contact detection, contactless testing techniques are urgently needed to eliminate the many problems associated with contact. In this paper, a contactless antenna utilizing resonant inductive coupling is presented. This coupling method, as compared to the conventional capacitive coupling technique allows faults detect from longer distances. The results of 3D full wave simulations in the High Frequency Structure Simulator (HFSS) and Advanced Design System (ADS) show that various faults, such as voids and pinholes, can be detected when the distance between the TSV and the antenna remains about 10 μm. Defective TSVs cause changes in the operating current and voltage pulses at the detection antenna. Simultaneously, changes in the field distribution around the TSVs are used to explain the changes in current and voltage pulses. Furthermore, the effects of antenna parallel movement were also investigated.

Design and analysis of high-performance double-gate ZnO nano-structured thin-film ISFET for pH sensing applications

This paper reports a high-performance double-gate zinc-oxide thin-film ion-sensitive field-effect transistor (DG-ZnO-ISFET) for pH sensing applications. The sensing mechanism of DG-ZnO-ISFET and a simulation model for pH sensing analysis are demonstrated herein. Various aspects of the device are elucidated through the study of channel conductance, electron density, energy band, and surface-potential profiles. The DG-ZnO-ISFETs enhance minor surface potential variations by capacitive coupling across the dielectrics of the top and bottom gates. Further, it operates by altering the bottom-gate voltage (VBG), obviating the need for a reference electrode system. The device depicts enhanced voltage sensitivity of 205.57 mV/pH, which is substantially 3.48 × greater than the Nernst limit sensitivity. In addition, the DG-ZnO-ISFET renders a maximum current sensitivity of 10.82 mA/mm.pH at VBG=5V. Furthermore, it exhibits high linearity in both voltage and current sensitivity, with the coefficient of determination (R2) values of 0.984 and 0.964, respectively. With their increased sensitivity and linearity, DG-ZnO-ISFETs have the potential device for next-generation biosensors.

Magnetic supercapacitors: Charge storage mechanisms, magnetocapacitance, and magnetoelectric phenomena

Pseudocapacitive (PC) materials are under investigation for energy storage in supercapacitors, which exhibit exceptionally high capacitance, good cyclic stability, and high power density. The ability to combine high electrical capacitance with advanced ferrimagnetic or ferromagnetic properties in a single material at room temperature opens an avenue for the development of advanced magnetically ordered pseudocapacitive (MOPC) materials. This review covers materials science aspects, charge storage mechanisms, magnetocapacitance, and magnetoelectric (ME) phenomena in MOPC materials. Recent studies demonstrate high PC properties of advanced ferrimagnetic materials, such as spinel ferrites and hexagonal ferrites. Of particular importance is the discovery of PC properties of perovskite-type manganites, which exhibit room temperature ferromagnetism and giant negative magnetoresistance. The coupling of high capacitance and magnetization in MOPC provides a platform for strong ME interactions. Various strategies are used for manipulation of electrical capacitance/magnetization of MOPC by a magnetic field/electrode potential. Magnetocapacitance studies show significant increase in capacitance of MOPC under the influence of a magnetic field. Moreover, the application of a magnetic field results in enhanced energy density and power density, reduction of resistance, and improvement of cyclic stability. Such findings offer a potential of a breakthrough in the development of advanced supercapacitors. High magnetocapacitance and ME phenomena are linked to the influence of magnetic fields on electrolyte diffusion, structure of electrical double layer, charge transfer resistance, and variation of conductivity and magnetization of MOPC materials, which facilitate charge/discharge behavior. Various applications of ME effect in MOPC are discussed. Moreover, advantages of magnetocapacitive MOPC are described for applications in electronic and spintronic devices, supercapacitors, and devices for magnetically enhanced capacitive deionization of water.

Design, Characterization, and In Vivo Application of Multi-Conductive Layer Organic Electrocorticography Probes

Biocompatible and plastic neural interface devices allow for minimally invasive recording of brain activity. Increasing electrode density in such devices is essential for high-resolution neural recordings. Superimposing conductive leads in devices can help multiply the number of recording sites while keeping probes width small and suitable for implantation. However, because of leads' vertical proximity, this can create capacitive coupling (CC) between overlapping channels, which leads to crosstalk. Here, we present a thorough investigation of CC phenomenon in multi-gold layer thin-film multi-electrode arrays with a parylene C (PaC) insulation layer between superimposed leads. We also propose a guideline on the design, fabrication, and characterization of such type of neural interface devices for high spatial resolution recording. Our results demonstrate that the capacitance created through CC between superimposed tracks decreases non-linearly and then linearly with the increase of insulation thickness. We identify an optimal PaC insulation thickness that leads to a drastic reduction of CC between superimposed gold channels while not significantly increasing the overall device thickness. Finally, we show that double gold layer electrocorticography probes with the optimal insulation thickness exhibit similar performances in vivo when compared to single-layer devices. This confirms that these probes are adequate for high-quality neural recordings.

High-Performance FET-Based Dopamine-Sensitive Biosensor Platform Based on SOI Substrate

Dopamine is a catecholamine neurotransmitter that plays a significant role in the human central nervous system, even at extremely low concentrations. Several studies have focused on rapid and accurate detection of dopamine levels using field-effect transistor (FET)-based sensors. However, conventional approaches have poor dopamine sensitivity with values <11 mV/log [DA]. Hence, it is necessary to increase the sensitivity of FET-based dopamine sensors. In the present study, we proposed a high-performance dopamine-sensitive biosensor platform based on dual-gate FET on a silicon-on-insulator substrate. This proposed biosensor overcame the limitations of conventional approaches. The biosensor platform consisted of a dual-gate FET transducer unit and a dopamine-sensitive extended gate sensing unit. The capacitive coupling between the top- and bottom-gate of the transducer unit allowed for self-amplification of the dopamine sensitivity, resulting in an increased sensitivity of 373.98 mV/log[DA] from concentrations 10 fM to 1 μM. Therefore, the proposed FET-based dopamine sensor is expected to be widely applied as a highly sensitive and reliable biosensor platform, enabling fast and accurate detection of dopamine levels in various applications such as medical diagnosis and drug development.

Signal Integrity Analysis of Through-Silicon Via (TSV) With a Silicon Dioxide Well to Reduce Leakage Current for High-Bandwidth Memory Interface

In this paper, we propose and analyze a through silicon via (TSV) with a silicon dioxide well (SDW) to reduce leakage current in the design of a high-speed signaling and low-power consumption high-bandwidth memory (HBM) interface. In the proposed TSV, the SDW is inserted into the silicon substrate area between TSVs. By inserting the SDW, the silicon substrate’s effective conductivity and permittivity are lowered compared to a conventional TSV. The proposed TSV with the SDW improves insertion loss by up to 0.079 dB at 4 GHz by minimizing the leakage current. In addition, by reducing the effective permittivity of the silicon substrate, the difference in ratio between the capacitive coupling and inductive coupling is minimized. It is also possible to obtain a reduction in far-end crosstalk (FEXT) in the range of HBM interface signaling. RLGC modeling of the proposed TSV with the SDW is presented, and is physically analyzed based on the frequency-dependent equivalent capacitance and conductance of the silicon substrate. The proposed TSV with SDW is finally evaluated using an eye diagram, and the eye height and width improved by up to 13.7 % and 4.7 % at 8 Gb/s, respectively, compared to the conventional TSV. The proposed TSV also reduced dynamic power consumption by 48.1 % at 8 Gb/s, verifying the low-power structure.

Dynamic Analysis and Fuzzy Fixed-Time Optimal Synchronization Control of Unidirectionally Coupled FO Permanent Magnet Synchronous Generator System

This paper focuses on dynamic analysis and the fuzzy fixed-time optimal synchronization control problem of unidirectionally coupled fractional-order (FO) permanent magnet synchronous generator (PMSG) system. The synchronization model between FO master and slave PMSGs with capacitive and resistive couplings is built. The dynamic analysis fully reveals its abundant dynamical behaviors including chaotic oscillations and gives stability/instability boundaries with the designed numerical method. In controller design, the hierarchical type-2 fuzzy neural network (HT2FNN) with a transformation is designed to approximate unknown functions, the fixed-time command filter matched up with the compensating signal is proposed to achieve precise estimate and fast convergence, and a fixed-time preconfigured performance function integrated with a smooth and invertible function is built to realize fixed-time convergence and performance constraint. Then a fuzzy fixed-time optimal synchronization control scheme fusing with the HT2FNN, filter, performance function and optimal control is developed under the FO backstepping theory. The stability analysis proves that all signals of the closed-loop system are bounded along with the cost function being minimized. Finally, numerical simulation results verify the feasibility and advantages of our scheme.

E–H transitions in Ar/O2 and Ar/Cl2 inductively coupled plasmas: Antenna geometry and operating conditions

Electronegative inductively coupled plasmas (ICPs) are used for conductor etching in the microelectronics industry for semiconductor fabrication. Pulsing of the antenna power and bias voltages provides additional control for optimizing plasma–surface interactions. However, pulsed ICPs are susceptible to capacitive-to-inductive mode transitions at the onset of the power pulse due to there being low electron densities at the end of the prior afterglow. The capacitive (E) to inductive (H) mode transition is sensitive to the spatial configuration of the plasma at the end of the prior afterglow, circuit (matchbox) settings, operating conditions, and reactor configurations, including antenna geometry. In this paper, we discuss results from a computational investigation of E–H transitions in pulsed ICPs sustained in Ar/Cl2 and Ar/O2 gas mixtures while varying operating conditions, including gas mixture, pulse repetition frequency, duty cycle of the power pulse, and antenna geometry. Pulsed ICPs sustained in Ar/Cl2 mixtures are prone to significant E–H transitions due to thermal dissociative attachment reactions with Cl2 during the afterglow which reduce pre-pulse electron densities. These abrupt E–H transitions launch electrostatic waves from the formation of a sheath at the boundaries of the plasma and under the antenna in particular. The smoother E–H transitions observed for Ar/O2 mixture results from the higher electron density at the start of the power pulse due to the lack of thermal electron attaching reactions to O2. Ion energy and angular distributions (IEADs) incident onto the wafer and the dielectric window under the antenna are discussed. The shape of the antenna influences the severity of the E–H transition and the IEADs, with antennas having larger surface areas facing the plasma producing larger capacitive coupling. Validation of the model is performed by comparison of computed electron densities with experimental measurements.

Electrical Capacitance Tomography-Based Flow Measurement in a Closed Container Using 16-Electrode Sensor in Contrast with 8-Pair-16-Electrodes Topology

Electrical Capacitance Tomography (ECT) is a commonly used technique to investigate the interior of a pipe by evaluating the coupling capacitances of a multi-electrode assembly. In this article, to improve the performance of the ECT sensor, sesitivity matrix, and hence the image quality, a typical customized 16-to-8 electrode ECT sensor is proposed, designed, simulated, and implemented in parallel with a standard 16-electrode ECT sensor. The results of both types of sensors are noted and compared to each other. It is evident from the results obtained during this experiment that the performance of the customized 16-8 electrode ECT sensor is comparatively better and exhibits better quality in its image reconstruction. The percentage of accuracy for the image quality could also be appreciated as compared with the standard 16-electrode ECT sensor. Further, a test was conducted for both the sensors under similar specifications and conditions to measure the flow of water, and it was found from the images that, for the same flow speed, image clarity is better for the customized 16-8 electrode ECT sensor in comparison with the standard 16-electrode ECT sensor. These findings may be useful for real time applications in the process industry.

Grid-Tied Single-Phase Integrated Zeta Inverter for Photovoltaic Applications

Recently, the development of integrated inverters for photovoltaic systems has been widely performed to reduce overall system size, costs, and losses. Thus, integrated inverters have emerged as a prominent solution for replacing two-stage power conversion composed of a step-up converter and a voltage source inverter. Thereby, this paper proposes an integrated inverter topology for single-phase grid-tied photovoltaic systems. The proposed power converter, called a Single-Phase Integrated Zeta Inverter (SP-IZI), can boost the input voltage and inject a sinusoidal and regulated current into the mains with low harmonic distortion. The SP-IZI is based on integrating modified DC-DC Zeta converters, designed and controlled to operate in a discontinuous conduction mode, and presents similarities with the Modified Zeta Inverter (MZI). In this way, this paper compares the main parameters of both topologies and provides a complete study of the SP-IZI, involving both quantitative and qualitative studies as well as a small signals analysis. The feasibility and functionality of the proposed SP-IZI inverter are presented and evaluated through experimental results, which demonstrate that the SP-IZI presents the following advantages compared to the MZI: (i) the voltage in coupling capacitors is 13% lower; (ii) voltage stresses in switches and diodes are 40% lower; and (iii) static gain is similar to the traditional Zeta converter.

A programmable analog front-end with independent biasing technique for ECG signal acquisition

This paper presents a programmable low power and low noise analog front-end (AFE) for electrocardiogram (ECG) signal acquisition. A novel capacitor-coupled instrumentation amplifier (CCIA) features independent biasing technique and AC coupling to signal source is proposed. Independent biasing technique is capable of obtaining better noise performance and more stable static working point reducing the glitch of chopping. An AC coupling style helps suppress electrode DC offset and enhance input impedance with metal-oxide-metal capacitor array, which is symmetrical to the center to alleviate the mismatch of input capacitor enhancing system common mode rejection ratio (CMRR). The current steering technology (CST) and programmable feedback capacitors are utilized to achieve an area-efficient programmable low pass filter (PLPF) under PVT variations. Also, a charge buck after PLPF is introduced to strengthen the driving ability of AFE. To verify the proposed AFE structure, a prototype is designed in 0.13 μm standard CMOS process with a 1.2 V supply. Post-simulation results show that the input impedance reaches 1.4 GΩ under 50 Hz. The in-band white noise density and integrating noise are 48 nV/sqrt (Hz) and 0.6 μV, respectively. The obtained low pass corner of PLPF are 380 Hz, 451 Hz and 1 kHz. The CMRR and PSRR under montecarlo simulation are 93 dB and 77 dB, respectively. The power of whole AFE is 48 μW.

Quantum Dots-Sensitized High Electron Mobility Transistor (HEMT) for Sensitive NO2 Detection

Colloidal quantum dots (CQDs) are gaining increasing attention for gas sensing applications due to their large surface area and abundant active sites. However, traditional resistor-type gas sensors using CQDs to realize molecule recognition and signal transduction at the same time are associated with the trade-off between sensitivity and conductivity. This limitation has restricted their range of practical applications. In this study, we propose and demonstrate a monolithically integrated field-effect transistor (FET) gas sensor. This novel FET-type gas sensor utilizes the capacitance coupling effect of the CQD sensing film based on a floating gate, and the quantum capacitance plays a role in the capacitance response of the CQD sensing film. By effectively separating the gate sensing film from the two-dimensional electron gas (2DEG) conduction channel, the lead sulfide (PbS) CQD gate-sensitized FET gas sensor offers high sensitivity, a high signal-to-noise ratio, and a wide range, with a real-time response of sub-ppb NO2. This work highlights the potential of quantum dot-sensitized FET gas sensors as a practical solution for integrated gas sensor chip applications using CQDs.