Charge Control Model Research Articles

Floating gate potential of gate-all-around floating gate memory cell: parameter extraction and compact model

The compact modeling of flash memories is crucial for integrated circuit designers to carry out efficient and precise circuit-level evaluations, particularly in the case of 3D NAND flash where the 3D geometry leads to significant parasitic coupling impacts on performance. In this work, we proposed a charge-based modeling approach for gate-all-around floating gate memory cells. The compact model is based on the derived unified charge control model where the mobile charge is explicitly solved. By solving the charge balance model and taking into account voltage-dependent parasitic capacitances for accurate coupling effects, the floating gate potential is accurately computed. The simulation results are validated with numerical TCAD simulation and showed good agreement with TCAD simulation. By solving the charge balance model and considering voltage-dependent parasitic capacitances for more accurate coupling effects, the floating gate potential is accurately calculated. Additionally, the results indicate that subthreshold degradation is caused by interface trap charge in the experimental device, and the proposed model successfully replicates experimental data.

Compact Spice Models for Terafets

Field effect transistors (FETs) in plasmonic regimes of operation could detect terahertz (THz) radiation and operate as THz interferometers, spectrometers, frequency-to-digital converters and THz modulators and sources. We report on the development of compact models for Si MOS (Metal-Oxide-semiconductor) and heterostructure-based plasmonic FETs (or TeraFETs) suitable for circuit design in the THz range and based on the multi-segment unified charge control model. This model accounts for the electron inertia effect (by incorporating segmented Drude inductances), for the ballistic field effect mobility, which is proportional to the channel length, for parasitic resistances and capacitances and for the leakage current. It is validated by comparison with experimental data and TCAD simulation results. The model can be used for simulation and optimization of sub-THz and THz detectors. Our simulations use up to 200 segments in the device channel. The results are also in good qualitative agreement with the hydrodynamic simulations. Applications of our model could dramatically reduce astronomical design costs of nanoscale VLSI reaching US$1.5 billion for the 3 nm technological node.

An ultra-high-frequency memristor circuit model

In the context of sixth-generation (6G) wireless communications technology, advanced radio-frequency switches are required to accommodate high-frequency terahertz range and complex modulation techniques. This paper proposes a flexible charge-controlled memristor model specifically designed for ultra-high-frequency applications. It describes in detail the derivation of the behavior model of the proposed memristor circuit. The memristor circuit model is built around four inverters, two multipliers, one integrator, one adder, and one differentiator. Through PSPICE simulation, the typical hysteresis loop of the memristor is thoroughly analyzed, demonstrating its suitability for use in wireless communication systems. The model exhibits a good typical hysteresis loop that operates over a wide frequency range from 100 kHz to 20 THz, meeting the specific requirements of terahertz applications. Compared to existing memristor designs, it operates at a much higher frequency. However, the zero crossing of the typical hysteresis loop deviates when the operating frequency exceeds 20 THz. Furthermore, the proposed memristor model can be customized in terms of set/reset voltage, operating frequency and , and has been verified for use in high speed switches with switching speeds of 19.5 ps. Furthermore, this research fills the gap in ultra-high-frequency memristor modeling, offering valuable insights and guidance for the utilization of memristors in the 6G technology and ultra-high frequency fields.

Unified Charge Control Model for Back-Gated 2-D Field Effect Transistors

Unified Charge Control Model for Back-Gated 2-D Field Effect Transistors

Low‐frequency noise model development of MoS2 field effect transistor and its analysis with respect to different traps

AbstractIn this paper, an analytical drain current model of double gate MoS2 FET Transistor for low‐frequency noise (LFN) power spectral density is developed, and compared its response with the device simulation of the proposed device structure. The developed low‐frequency noise power spectral density (PSD) model is analyzed with respect to different Trap densities, Oxide thicknesses, and high K‐dielectric materials using the TCAD Device simulation tool. Low‐frequency noise is one of the most important noises in any device since it degrades the device's performance. So, in this paper, we used a unique charge‐control model for analyzing the low‐frequency noise by considering the mobility degradation, trapping, and de‐trapping effects caused by trap densities and device lattice structure. Usually, all the previous studies on drain currents with low frequency are based on fluctuations caused by mobility and carrier variations. In our paper, we even considered the charge density fluctuation to analyze the drain current equation. Using a Charge Control Model, we can compute the parameters like gate capacitance (Cgs, Cgd), channel length modulation, and body effect. While other LFN models like the DC model, small signal model, and hybrid model will focus mainly on the static characteristics of the device such as its DC current–voltage (I‐V) relationship, terminal resistances, and input/output conductance of the devices. All the analytical model results were calibrated with the device simulation and it is observed that both are matches each other. Further, it is observed that with an increase in Trap density, the low‐frequency noise increases and low‐frequency noise is dominant at lower frequencies only (1–10 Hz), and after this frequency range the thermal noise will be the dominant noise factor.

Multiple-layer energy management strategy for charging station optimal operation considering peak and valley shaving

Existing vehicle-to-grid (V2G) applications are aimed at the power grid and the government. It is difficult for charging stations (CSs) to execute the schedules in real time. To figure out the multiple-layer energy management from the perspective of CS, the dispatch potential assessment model is constructed based on the EV users’ charging demand and Minkowski summation. And the optimal energy management schedule model of CS with ESS is proposed considering peak shaving and valley filling under the time-in-use tariff. Besides, the real-time charging control model of EVs in CS is designed under the premise of meeting the charging needs. The simulation results show that the proposed strategy can promote CS operation revenues and track the scheduling plan of CS. The arbitrage of tariffs and peak shaving ancillary services are realized while the charging loads of CSs are smoothed by the charging/discharging of ESS. The proposed strategy is applicable for the CS aggregators and can help the grid operators for dispatch schedules.

Distributed demand response charging control of multiple plug‐in electric vehicle clusters

AbstractThis paper is devoted to the distributed demand response (DR) charging control of plug‐in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Specifically, PEVs are divided into different clusters according to their parking place under different energy management systems. Each EV cluster is modelled by a transport‐based load aggregate model with the input being the charging rate, and the output is the aggregate power. Based on the aggregate charging control model, a novel dynamic real‐time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory. The theoretical analysis shows that if the reference power profile is in the trackable area of all PEVs' charging power and the ramping rate is restrained by a predefined bounded constraint, then the demand response charging tracking control is solvable. Finally, simulation results on an EV system with twelve PEV clusters are presented to show the effectiveness of the proposed demand response control algorithm.

Directing-Group-Free Arene C(sp2)-H Amination Using Bulky Aminium Radicals and DFT Analysis of Regioselectivity.

A hydroxylamine-derived electrophilic aminating reagent produces a transient and bulky aminium radical intermediate upon in situ activation by either TMSOTf or TFA and a subsequent electron transfer from an iron(II) catalyst. Density functional theory calculations were used to examine the regioselectivity of arene C-H amination reactions on diversely substituted arenes. The calculations suggest a simple charge-controlled regioselectivity model that enables prediction of the major C(sp2)-H amination product.

Exploring Cuneanes as Potential Benzene Isosteres and Energetic Materials: Scope and Mechanistic Investigations into Regioselective Rearrangements from Cubanes.

Cuneane is a strained hydrocarbon that can be accessed via metal-catalyzed isomerization of cubane. The carbon atoms of cuneane define a polyhedron of the C2v point group with six faces─two triangular, two quadrilateral, and two pentagonal. The rigidity, strain, and unique exit vectors of the cuneane skeleton make it a potential scaffold of interest for the synthesis of functional small molecules and materials. However, the limited previous synthetic efforts toward cuneanes have focused on monosubstituted or redundantly substituted systems such as permethylated, perfluorinated, and bis(hydroxymethylated) cuneanes. Such compounds, particularly rotationally symmetric redundantly substituted cuneanes, have limited potential as building blocks for the synthesis of complex molecules. Reliable, predictable, and selective syntheses of polysubstituted cuneanes bearing more complex substitution patterns would facilitate the study of this ring system in myriad applications. Herein, we report the regioselective, AgI-catalyzed isomerization of asymmetrically 1,4-disubstituted cubanes to cuneanes. In-depth DFT calculations provide a charge-controlled regioselectivity model, and direct dynamics simulations indicate that the nonclassical carbocation invoked is short-lived and dynamic effects augment the charge model.

Steady-State Characterization for Capture and Escape Lifetimes of 2-D Electron Gas in Light-Emitting Transistors

Quantum-well-based heterojunction bipolar light-emitting transistors (HBLETs or LETs) could work as candidate devices in optical communication and optoelectronic integrated circuits (OEICs) due to their multiport operation properties. The recombination process and capture-escape dynamics of carriers limit the device modulation bandwidth. The knowledge of capture and escape lifetimes is necessary to improve bandwidths. Here, we present a steady-state procedure rather than dynamic ones such as time-resolved photoluminescence (TRPL) or small-signal response to characterize the two lifetimes of LETs. On the experimental side, we perform dc measurements to investigate the electrical characteristics of the base–emitter (BE) junction of LETs. Theoretically, we formulate the charge-controlled model with continuity equations for electron concentrations in unbound and bound subbands of the quantum well (QW). The related capture and escape lifetimes are extracted with analytical expressions and the current gains of LETs. In the end, we verify our model by comparing the measured bandwidths to the unity gain bandwidths of this study.

Editors’ Choice—Thin Film Transistor Response in the THz Range

Novel metal oxide materials such as InGaZnO (IGZO), ZnO, SnO, and In2O3 and improved fabrication processes dramatically enhanced the achieved and projected thin film transistor (TFT) performance. The record values of the effective field-effect mobility of Metal Oxide TFT (MOTFT) materials have approached 150 cm2/Vs. We report on an improved compact TFT model based on three models: the RPI TFT model, the unified charge control model (UCCM), and the multi-segment TFT compact model. This improved model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-trivial capacitance dependence on the gate bias, and parasitic impedances. The analysis of the TFT response using this model and the analytical calculations showed that TFTs could have a significant response to impinging THz and sub-THz radiation. Using a complementary inverter and the phase-matched THz signal feeding significantly improves the detection sensitivity.

(Invited) Improved Thin Film Transistor Model Predicts TFT Operation in the THz Range

Novel Thin-film-transistor (TFT) TFT materials such as ZnO, InGaZnO, AMO-CNT, and organic materials dramatically improved the achieved and projected TFT performance. The low field mobility of oxide materials has reached values comparable to those for short-channel Si CMOS. The effects related to electron inertia and electron density oscillations in field effect transistors channels (FETs) diminish the role of the low field mobility as a figure of merit in short channel devices making the performance gap between TFTs and Si CMOS smaller enabling high frequency TFT applications even reaching sub-THz and THz frequencies (for the operating regimes using the rectification of the plasma oscillations. We report on an improved compact model based on the RPI TFT model [1] and using the Unified Charge Control Model (UCCM). [2, 3] This model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-trivial capacitance dependence on the gate bias. It also accommodates the inclusion of the parasitics related to the gate impedance. These new features allowed us to obtain an excellent agreement with the measured I-V/C-V characteristics for both long and short n-channel and p-channel TFTs. The application of this new TFT model to the analysis of the TFT response requires accounting for non-local potential distribution in the device channel. This is achieved by using a multi-segment nonlinear transmission line model of the TFT channel reproducing the approach that has been previously used for the THz SPICE/ADS Si CMOS model implementation. As a possible application example, we simulated a TFT complementary inverter. Our simulations showed that using the phase-matched THz signal feeding should yield a very sensitive detection of THz radiation impinging on a short channel TFT. These results show that the TFT RFID and other applications could be extended into the THz range of frequencies.

(Invited) Improved Thin Film Transistor Model Predicts TFT Operation in the THz Range

Novel materials such as ZnO, InGaZnO, AMO-CNT, and organic materials and improved fabrication processes dramatically enhanced the achieved and projected thin film transistor (TFT) performance. The effective field-effect mobility of metal oxide TFT materials has reached values comparable to those for short-channel Si CMOS. We report on an improved compact model based on the RPI TFT model, the unified charge control model (UCCM), and the multi-segment TFT compact model. This improved model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-trivial capacitance dependence on the gate bias. The application of this new TFT model to the analysis of the TFT response showed that a TFT complementary inverter using the phase-matched THz signal feeding should yield a very sensitive detection of THz radiation impinging on a short channel TFT.

Physics based model of an AlGaN/GaN vacuum field effect transistor

A vacuum field effect transistor (VacFET) is proposed that consists of a modification of a conventional AlGaN/GaN high electron mobility transistor to include a nanogap near the gate on either the source (cathode) or drain (anode) side of the device. The current flowing through the two-dimensional electron gas (2DEG) under the gate is obtained using a charge-control model, which is forced to be equal to the tunneling current across the nanogap. The latter is modeled using a modified version of Simmons tunneling theory of a metal–insulator–metal junction to include the effect of barrier lowering across the nanogap. When compared to other recently fabricated VacFETs, the proposed device has potential for much higher emission current densities and transconductance levels, of the order of several hundreds of mA/mm and tens of mS/mm, respectively. For similar material parameters and physical dimensions, the proposed VacFET has a turn-on voltage that depends on the location of the nanogap on either the source or drain side of the gate. It is shown that the current–voltage characteristics of VacFETs with a nanogap either on the drain or source side of the gate are highly sensitive to their physical parameters and biasing conditions, making them a very strong candidate for chemical or gas sensing applications. This is due to the sensitivity of the tunneling current to the effective barrier height and field enhancement factor of the nanogap.

Analytical Modeling of Tunnel-Junction Transistor Lasers

Compared with transistor lasers (TLs), tunnel-junction transistor lasers (TJTLs) are more easily modulated with the voltage across base-collector (BC) junction. In this work, the charge-control model and modified rate equation of TJTLs which includes the Franz-Keldysh effect and direct tunneling is developed. We conduct DC and AC analysis with our model and show that the doping concentration in the BC junction plays a key role in the capability to voltage modulate TJTLs since it affects the junction field. A trade-off between the optical power and capability of the voltage modulation emerges as a concern for designing the doping concentration. We also study the effect of the quantum well (QW) position. The result shows that the QW closer to the BC junction can obtain a higher confinement factor to achieve better output power and modulation bandwidth.

Frequency to digital conversion using Si TeraFETs

Our simulations using the validated multisegment simulation program with integrated circuit emphasis (SPICE) model show that the terahertz (THz) spectrometers using plasmonic field effect transistors could be used for the frequency to digital conversion. The THz SPICE unified charge control model that uses the distributed channel resistances, capacitances, and Drude inductances is validated by technology computer-aided design simulations. The THz spectrometers using Si plasmonic field effect transistors (or TeraFETs) determine the frequency of the impinging radiation by measuring the gate bias where the responsivity changes sign. This crossover frequency is sensitive to the channel length and nearly insensitive to the gate bias in the weak and moderate inversion regions. This unique feature allows the use of multiple THz spectrometers with different channel lengths to implement the frequency-to-digital converters in the sub-THz and THz frequency range. The simulations predict the operation frequency from 110 GHz up to 4 THz for the frequency-to-digital converters using Si TeraFETs with feature sizes from 20 to 130 nm.

AlGaN/AlN/GaN SG-HEMT as pH detector: A simulation study

Unlike other FETs where a sub-threshold regime is preferred for pH detection where power is a constraint, here both subthreshold and saturation region of operation can be used for sensing. In the saturation region, a large change in drain current shift is obtained compared to the sub-threshold region which leads to enhanced sensitivity. Similarly, sub-threshold parameters like transconductance (gm), current ratio gm/IDS, threshold voltage (Vth) also can be applied as effective sensing metrics for biochemical sensing. The HEMT sensor design with AlN interlayer’s in the epitaxial design and thin Al2O3 gate oxide layer enhances the overall performance of the device and gm sensitivity. Using TCAD simulation an investigation is done on the applicability of different sensing metrics through the development of a charge-controlled model for the sensitivity analysis of solution gated HEMT (SGHEMT) for pH-sensing. The simulation results indicate the high potential of the device for pH detection.

Performance Enhancement of AlGaN/GaN HEMT by Optimization of Device Parameters Considering Nanometer Barrier Layer Thickness

The two-dimensional electron gas (2DEG) at the heterointerface of AlGaN and GaN is a complicated transcendental function of gate voltage, so an analytical charge control model for AlGaN/GaN high electron mobility transistor (HEMT) is presented accounting for all the three regions of operation (i.e., sub-threshold, moderate, and strong-inversion region). In addition to it, the performance of AlGaN/GaN HEMT is highly dependent on the device geometry. Therefore, to get the optimum performance of the device it is advisable to optimize the parameters governing the device geometry. Accordingly, the output and transfer characteristics, threshold voltage, ON current, OFF current, and transconductance are calculated using numerical computations. The present design is tested to calculate the voltage transfer characteristics (VTC) and transient characteristics of the invertor circuit, after the optimization of the device parameters.

CDDPG: A Deep-Reinforcement-Learning-Based Approach for Electric Vehicle Charging Control

Electric vehicle (EV) has become one of the most critical components in the smart grid with the applications of the Internet-of-Things (IoT) technologies. Real-time charging control is pivotal to ensure the efficient operation of EVs. However, the charging control performance is limited by the uncertainty of the environment. On the other hand, it is challenging to determine a charging control strategy that is able to optimize multiple objectives simultaneously. In this article, we formulate the EV charging control model as a Markov decision process (MDP) by constructing state, action, transition function, and reward. Then, we propose a deep-reinforcement-learning-based approach: charging control deep deterministic policy gradient (CDDPG) to learn the optimal charging control strategy for satisfying the user’s requirement of battery energy while minimizing the user’s charging expense. We utilize the long short-term memory (LSTM) network that extracts the information of previous energy price to determine the current charging control strategy. Moreover, Gaussian noise is added to the output of the actor network to prevent the agent from sticking into the nonoptimal strategy. In addition, we address the limitation of sparse rewards by using two replay buffers, of which one is used to store the rewards during the charging phase and another is used to store the rewards after charging is completed. The simulation results prove that the CDDPG-based approach outperforms the deep- $Q$ -learning-based approach (DQL) and the deep-deterministic-policy-gradient-based approach (DDPG) in satisfying the user’s requirement for the battery energy and reducing the charging cost.

Ordered charge control considering the uncertainty of charging load of electric vehicles based on Markov chain

Abstracts In order to improve the consumption capacity of renewable energy, an ordered charging control method of electric vehicles based on Markov chain prediction is proposed considering the uncertainty of the electric vehicle charging load. The quantity of electric vehicles in different parking lots and different time periods is predicted by the Markov chain to calculate the electric vehicle charging load of the photovoltaic charging station. Taking the minimum power sum of a photovoltaic charging station, the minimum cost of users and the maximum consumption of the renewable energy as the objective functions, an ordered charging control model with the interest and willingness of electric vehicle users is established. The peak-to-valley time period is divided by the particle swarm optimization algorithm, and the genetic algorithm is used to solve the model. The simulation tests of the electric vehicle driving data provided by the Unite State Travel Survey website verify the correctness and effectiveness of the proposed method, the effects of different peak and valley periods and the responsiveness of electric vehicle users on the ordered charging control of electric vehicles are compared and analyzed. The simulation results show that the prediction accuracy of the charging load obtained by the Markov chain is significantly higher than that of Monte Carlo, and when the responsiveness of electric vehicle users reaches 90%, the total charging cost can be reduced by up to 16.89%. The ordered charging strategy of electric vehicles proposed in this paper can effectively reduce the peak-to-valley difference, increase the consumption of renewable energy, and reduce the charging cost of electric vehicle users.