Surface Potential Model Research Articles

Comparative studies of different solutes effects on microstructure and comprehensive performance of coherent precipitation-strengthened Cu–Ni–Al alloys

Multi-componentization can further improve the heating resistance of Cu–Ni–Al alloys, enabling them to withstand more demanding situations. Unfortunately, the limited researches have been done on the wear and corrosion resistance of the heat-resistant Cu–Ni–Al alloys, resulting in the lack of relevant evidence in the practical application. In this work, a comparative study of differential types of trace element, Si (the stronger enthalpy interaction element), Sn (the weaker enthalpy interaction element) Cr or Zr (grain boundary strengthening element), effects on microstructure, wear and corrosion resistance will be done, Furthermore, the effect of different trace elements on the surface electron work function and electrochemical behavior of Cu–Ni–Al alloys is reflected by SPM surface potential model. The results indicate that the precipitation of dual nano-phase and accelerated precipitation of γ′ phase can be realized through the addition of Si, Sn, Cr and Zr, in which the value of δγ-γ′ increase sharply after adding Si and it is not conducive to the preservation of cuboidal γ′ phase. The addition of Si, Cr and Zr can improve electron work function distribution and mechanical property, wear, and corrosion resistance of the alloys, in which Si is more conducive to the improvement of wear resistance and mechanical properties of the alloy, while the alloy with Cr and Zr shows the excellent corrosion resistance. The addition of Sn will weaken the enthalpy interaction of the alloy system, reduce the electron work function of the alloy, and have adverse effects on the wear and corrosion resistance of the alloy.

Physics-based modeling of surface potential and leakage current for vertical Ga2O3 FinFET

Gallium oxide (Ga2O3) is a promising ultra-wide bandgap material offering a large bandgap (>4.7 eV) and high critical electric fields. The increasing demand for electronic devices for high-power applications in electric automobiles, high-performance computing, green energy technologies, etc., requires higher voltages and currents with enhanced efficiency. Vertical transistors, such as fin-shaped field-effect transistors (FinFETs) have emerged to meet the growing need with improved current handling capabilities, reduced resistance, and enhanced thermal performance. However, to fully exploit the Ga2O3 power transistors, precise and reliable physics-driven models are crucial. Therefore, a comprehensive surface potential model has been developed in this work for a vertical Ga2O3 FinFET. The electric potential across the channel is explained by analyzing the two-dimensional (2D) Poisson equation employing parabolic approximation. Such a surface potential model is instrumental in determining the performance of the Ga2O3 FinFET as it affects the threshold voltage, the drain current, and fringing capacitance. Exploiting the surface potentials, a fringing capacitance model is derived which is crucial in analyzing the speed of the device in compact integrated circuits. In addition, statistical analysis of the Ga2O3 FinFET using the Monte Carlo simulation technique is performed to determine the leakage current fluctuation due to doping variations. The validation of the analytical model with experimental results confirms the effectiveness and prospects of the developed models in the rapid development and characterization of next-generation high-performance vertical Ga2O3 power transistors.

A Closed-Form Model for 2-DEG Charge and Surface Potential in N-Polar Gallium Nitride Heterostructures

A closed-form model to calculate the 2-D electron gas (2-DEG) charge density and surface potential in an N-polar GaN/AlGaN heterostructure is presented. The proposed model is developed from the solution of Schrödinger’s equation for a finite triangular potential well. Asymptotic expressions of Airy functions are used to compute an initial value of subband energy. A new, unified expression to update the surface potential due to Poisson’s equation is presented. The modified Fang–Howard (M.F.H.) function is then employed to develop a closed-form correction to the subband energy using first-order perturbation theory. No fitting parameters are used. The results from our model are validated with numerical data for a wide range of bias conditions, channel layer thickness, and spacer layer mole fraction. Finally, the gate capacitance of the heterostructure is evaluated using automatic differentiation and validated against experimental data.

A Surface Potential Model for Metal-Oxide-Semiconductor Transistors Operating near the Threshold Voltage

Device physics and accurate transistor modeling are necessary to reduce the operating voltage near the threshold for power-constrained circuits. Conventional device modeling for metal-oxide-semiconductor (MOS) transistors focuses on operations in either strong or weak inversion regimes, and the electrostatics at gate biases near the threshold voltage is rarely studied. This research proposed an analytical model to describe the distribution of the surface potential along the channel for near-threshold operation. Numerical device simulations were also performed to investigate the electrostatics near the threshold voltage. The numerical simulation with constant carrier mobility showed an overshoot in the transconductance due to decay of the lateral electric field with gate bias. The decay of the lateral electric field was predicted by the proposed analytical surface potential model which considered widening the channel length with flooding of the inversion carriers in the channel and gate overlap regions. The channel length widening effect saturated as the gate bias further increased. Therefore, evident transconductance overshoot was observed near the threshold voltage in short-channel devices.

Comparison of multifidelity machine learning models for potential energy surfaces.

Multifidelity modeling is a technique for fusing the information from two or more datasets into one model. It is particularly advantageous when one dataset contains few accurate results and the other contains many less accurate results. Within the context of modeling potential energy surfaces, the low-fidelity dataset can be made up of a large number of inexpensive energy computations that provide adequate coverage of the N-dimensional space spanned by the molecular internal coordinates. The high-fidelity dataset can provide fewer but more accurate electronic energies for the molecule in question. Here, we compare the performance of several neural network-based approaches to multifidelity modeling. We show that the four methods (dual, Δ-learning, weight transfer, and Meng-Karniadakis neural networks) outperform a traditional implementation of a neural network, given the same amount of training data. We also show that the Δ-learning approach is the most practical and tends to provide the most accurate model.

Methylammonium Tetrel Halide Perovskite Ion Pairs and Their Dimers: The Interplay between the Hydrogen-, Pnictogen- and Tetrel-Bonding Interactions.

The structural stability of the extensively studied organic-inorganic hybrid methylammonium tetrel halide perovskite semiconductors, MATtX3 (MA = CH3NH3+; Tt = Ge, Sn, Pb; X = Cl, Br, I), arises as a result of non-covalent interactions between an organic cation (CH3NH3+) and an inorganic anion (TtX3-). However, the basic understanding of the underlying chemical bonding interactions in these systems that link the ionic moieties together in complex configurations is still limited. In this study, ion pair models constituting the organic and inorganic ions were regarded as the repeating units of periodic crystal systems and density functional theory simulations were performed to elucidate the nature of the non-covalent interactions between them. It is demonstrated that not only the charge-assisted N-H···X and C-H···X hydrogen bonds but also the C-N···X pnictogen bonds interact to stabilize the ion pairs and to define their geometries in the gas phase. Similar interactions are also responsible for the formation of crystalline MATtX3 in the low-temperature phase, some of which have been delineated in previous studies. In contrast, the Tt···X tetrel bonding interactions, which are hidden as coordinate bonds in the crystals, play a vital role in holding the inorganic anionic moieties (TtX3-) together. We have demonstrated that each Tt in each [CH3NH3+•TtX3-] ion pair has the capacity to donate three tetrel (σ-hole) bonds to the halides of three nearest neighbor TtX3- units, thus causing the emergence of an infinite array of 3D TtX64- octahedra in the crystalline phase. The TtX44- octahedra are corner-shared to form cage-like inorganic frameworks that host the organic cation, leading to the formation of functional tetrel halide perovskite materials that have outstanding optoelectronic properties in the solid state. We harnessed the results using the quantum theory of atoms in molecules, natural bond orbital, molecular electrostatic surface potential and independent gradient models to validate these conclusions.

An Analytical Approach to Study the Impact of Traps on Ge-Source Double Gate PNPN TFET

The analytical models for surface potential, electric field, and drain current of a Ge-source double gate hetero-structure PNPN Tunnel FET are developed taking into account the oxide-semiconductor interfacial trap charges. Although other researchers have used similar modeling techniques on various structures, the proposed structure has not yet utilized them when considering the source/drain depletion region and interfacial trap charges that reflect changes in the flat band voltage. The proposed device consists of Ge-source, Si1−xGex pocket (mole fraction 0.3), and Si channel and drain. Moreover, the non-uniform concentration of trap charges is considered at the oxide/semiconductor interfaces: 1013 cm−2 at HfO2/ Si1−xGex interface and 1012 cm−2 at HfO2/Si interface. 2D Poisson’s equation is solved with the help of parabolic potential approximation and different boundary conditions to develop the surface potential model. The developed potential model is subsequently used to construct the electric field model. The drain current model of the proposed TFET is finally developed with the help of the generated electric field and some other parameters. All the developed models are validated using TCAD-simulated data. The studies show that there is good agreement between the simulated and modeled results, ensuring the applicability of the device in charge-trapped memory systems based on tunneling.

An accurate analytical surface potential model of heterojunction tunnel FET

Based on the accurate and efficient thermal injection method, we develop a fully analytical surface potential model for the heterojunction tunnel field-effect transistor (H-TFET). This model accounts for both the effects of source depletion and inversion charge, which are the key factors influencing the charge, capacitance and current in H-TFET. The accuracy of the model is validated against TCAD simulation and is greatly improved in comparison with the conventional model based on Maxwell–Boltzmann approximation. Furthermore, the dependences of the surface potential and electric field on biases are well predicted and thoroughly analyzed.

Impact of temperature on a ferroelectric interfaced negative capacitance double gate junctionless accumulation mode field effect transistor-compact model

Ferroelectric interfaced negative capacitance field effect transistors are gaining popularity for low power applications; however, as temperature is a constant influencing factor, further study is required to comprehend how these devices are influenced. Through a proposed compact model, this paper analytically investigates the influence of temperature on a ferroelectric interfaced negative capacitance double gate junctionless accumulation mode field effect transistor. This device integrates the benefits of negative capacitance with the junctionless accumulation mode structure. An extensive comparison of the proposed device is made with the existing structure to evaluate the benefits offered by the ferroelectric layer at different temperatures. The Landau–Khalatnikov equation and Pao–Sah integral are employed to obtain the surface potential and drain current model with temperature variation. Various key parameters of the device have been analysed extensively by varying the temperature from 200 to 500 K. It has been found that internal voltage amplification declines as temperature rises, but the sub-threshold swing increases from 46 to 72 mV decade −1 with an increase in temperature. Additionally, with a progressive rise in temperature, the loss of gain and degradation of gate capacitance are observed.

An Analytical Surface Potential and Effective Charge Density Approach Based Drain Current Model for Amorphous InGaZnO Thin-Film Transistors

An analytical surface-potential-based drain current model for amorphous indium–gallium–zinc–oxide (a-InGaZnO) thin film transistors (TFTs) is proposed by introducing an effective charge density approach in this paper. This approach gives two initial approximate values of the effective state density and the effective thermal voltage by using the dominant state of the free charge density in total charge density, and then obtains a high-precision one-exponent equivalent transformation for three-exponent total charge density. Based on this approach, we have solved the problem that the physical meaning of the transition area in the regional method is not clear and a one-piece analytical surface potential solution to Poisson’s equation is successfully derived. Furthermore, the drain current is also explicitly derived from the charge sheet model and I-V characteristics of a-InGaZnO TFTs are reproduced from the above obtained model. Finally, accurate and effective surface-potential model and drain current model are obtained and verified by experimental data, respectively. Good verification results prove that the proposed model could become an accurate and suitable tool for being embedded into a circuit simulation.

Performance Investigation of a Dielectric Stacked Triple Material Cylindrical Gate All Around MOSFET (DSTMCGAA) for Low Power Applications

This paper presents an analysis of gate stacked triple material dual-halo cylindrical MOSFET. The surface potential and electric field have been plotted for the proposed device using TCAD Silvaco at various channel lengths. The analytical model of surface potential, field and subthreshold current is also present. A comparative analysis has been accomplished for the proposed device with Asymmetric gate stack triple metal gate all around (AGSTMGAA), dual dielectric triple metal surrounding gate (DDTMSG) and Triple metal surrounding gate MOSFET. The performance metric of the device has been investigated in terms of Drain Induced Barrier Lowering (DIBL), Subthreshold swing and threshold-voltage roll-off. Furthermore, the analog behaviour of the device has been evaluated by determining transconductance, early voltage and intrinsic gain. The proposed device shows much better performance when compared to its counterpart. The mitigation in DIBL and leakage current indicates the cut back in the SCEs. The proposed device shows 8% improvement in SS, 36.2% improvement in DIBL and 13.5% improvement in threshold voltage roll-off as compared to AGSTMGAA. Hence, it can be used for low power applications.

Surface Potential Modelling Based Performance Analysis of Gate Engineered Trapezoidal Trigate Tunnel FET

In this paper, a three dimensional (3-D) analytical model of surface potential has been derived for gate engineered trapezoidal trigate Tunnel Field Effect Transistor (TFET). The model has been obtained by assuming parabolic approximation of the potential profile and solving 3-D Poisson equation using appropriate boundary conditions. The device considered in this work is silicon based TFET with gate composed of two materials with different work functions. The low work-function material is placed close to source and drain region while high work-function material is placed in between them. This will result in enhancing the tunneling in the source/channel interface region while reducing the electric field in the drain region. Trigate devices have been found to enhance the device performance at nanoscale, however, Trigate device fabricated by Intel have been found to have trapezoidal shape rather than expected rectangular shape. In this work, we have included the effect of different inclination angles of sides on the device performance. The model has been verified by comparing the results with the simulation results obtained in ATLAS software.

Potential model and simulation analysis of dual material gate vertical TFET with impact of interface trap charges

This paper presents modeling and simulation of the dual material gate vertical tunnel FET (VTFET-DMG) by including the interface trap charges. The interface trap charges are considered at the high-k and silicon substrate interface near the source and the channel region. The surface potential model is developed here by utilizing the 1-D and 2-D Poisson equations solved with different boundary conditions after dividing the whole device into eight different regions. The parabolic approximation is assumed to find the numerical solution of the Poisson equations. The same device is also designed and simulated in the Silvaco TCAD simulator with the inclusion of the impact of the interface trap charges and the outcomes of the simulations are compared with the modeled results. The variation of the surface potential with the increase in positive interface charges and negative interface charges is plotted and analyzed. It is seen that the surface potential enhances with the increase in positive interface charges and it reduces with the increase in the negative interface trap charges. We use the dual material gate approach in proposed structure to show an overall increase in the performance of the device. Incorporating the high-K gate oxide in the presence of interface traps improves the device's reliability for low power utilization.

A Neuro-Space Mapping Method for Harmonic Interference Prediction of SOIFET Radio Frequency Switches

With the rapid development of wireless communication, the requirements of high-integration and low-cost radio frequency (RF) front-end modules in mobile phones result in more usage of silicon-on-insulator field effect transistors (SOIFETs) for the manufacturing of RF switches. However, the nonlinear behavior of SOIFET switches in <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> -state always produces unwanted harmonics distortion interference when they are excited by a large signal. In this article, we simplify the well-known physics-based surface potential model to an interelectrode nonlinear capacitance (INC) model since it adequately describes the harmonic effects produced by the transistor. The INC model, referred to as the coarse model, cannot match the behavior of the real switch, since many parameters of the switch cannot be accurately determined. This article proposes a novel dynamic neuro-space mapping network model, referred to as the fine model, to optimize the INC model. The proposed model takes advantage of the high accuracy of the fine model and the fast speed of the coarse model. Ultimately, the proposed method can accurately predict the harmonics interference for SOIFET switches in the complex RF front-end environment and provides an intuitive guideline under the design stage to prevent EMI problems.

Design of Polymer-Based Trigate Nanoscale FinFET for the Implementation of Two-Stage Operational Amplifier

The major motivation behind transistor scaling is the requirement for high-speed transistors with lower fabrication costs. When the fin thickness or breadth is smaller than 10 nm in a trigate FET, charges travel in a nonconfined fashion, resulting in the creation of energy subbands and causing volume inversion. In comparison to the carrier near a surface inversion layer, volume inversion experiences less interface scattering. In large-scale integrations, we have focused on developing a 3D model for surface potential by establishing the three-dimensional Poison’s equation and building a unique fin field-effect transistor (FinFET) structure. In this context, there is a growing interest in developing a low-cost, simple solution that combines plastic (polymer) as a substrate and organic materials to create electronics such as monitors and sensors. The research examines characteristics such as silicon width, oxide thickness, doping concentration, metal work-function about gate, and various surface potentials. For different circuit configurations, it also examines the DC and AC characteristics of the FinFET structure. A differential amplifier is built for RF application based on the device specifications. This work is aimed at improving the semiconductor design structure by adjusting device parameters, analyzing the results, establishing the best FinFET device preferences, and selecting an application for the optimized device. The 3D Poisson’s equation may be used to create an analytical model of a trigate nanosize FinFET, which can then be tested using a TCAD simulator. By constructing such a FinFET, we can structure and analyze various electrostatic parameters. To facilitate the creation of FinFET-based circuits, including product development, a novel transistor needs a creative device basis. The infrastructure’s support denotes a computationally advantageous numerical model that accurately depicts a FinFET. The work presents a compact model for semiconductor manufacturing that permits separate IC productions while achieving higher levels of excellence and using less power. The design outperforms the CMOS by 22.7% in gain, 31.48% in power consumption, and 12.72% in CMRR, while operating at a 5 GHz unity gain frequency.

Quasi-analytical model of surface potential and drain current for trigate negative capacitance FinFET: a superposition approach

Negative capacitance (NC) obtained from the ferroelectric polarization switching is a widely adopted approach for the realization of low power, high-performance devices. In this paper, for the first time, we have developed a 3D quasi-analytical model for the surface potential and drain current of the trigate NC-FinFET using the superposition approach. Till date, only double gate (DG) uniformly doped NC-FinFET structures have been explored, which does not reveal the practicality of the device. Therefore, we perform an extensive device evaluation: (a) by solving the Poisson’s equation separately for the side gates (DG) and the top gate to acquire a complete model for trigate FinFET using the superposition principle; (b) to mimic the actual source/drain (S/D) doping, we included Gaussian doping in our proposed model; (c) with the incorporation of the laterally extended gate and S/D underlap. The model data are found in good agreement with the well-calibrated simulation data. We have taken the parabolic approximation method and appropriate boundary conditions to solve the Poisson’s equation.

A Physics-Based Model of Vertical TFET—Part II: Drain Current Model

A physics-based model for the tunneling current of vertical tunneling field transistors (TFET) is proposed. In part I, the expression of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varphi _{\text {1D}}{(}\textit {x}{)}$ </tex-math></inline-formula> is derived from the multi-branch general solutions of Poisson’s equation. The model’s results are verified with TCAD simulation for transistors with different materials, device geometries, and biases. In this article, a surface potential model is validated at different device regions which include channel and drain. Based on the above two electric potential models, Kane’s tunneling formula is utilized for the calculation of band-to-band tunneling current. The proposed current model is valid for all transistors’ operating regions. The quantum effect on the band-structure parameters is taken into account in the modeling of InAs vertical TFET. It is shown that the channel thickness needs to be optimized to achieve the highest drive current.

Airy Function-Based Model for 2-DEG Charge and Surface Potential in N-Polar Gallium Nitride Heterostructures

A systematic, analytical method to obtain the charge density and surface potential in an N-polar GaN/AlGaN heterostructure is presented. This method also provides the wave functions, subband energies, and band diagram. The model accounts for the greater leakage of the wave functions into the spacer and barrier layers in the N-polar structure as compared to the Ga-polar structure. The framework is based on the solution of Schrödinger–Poisson equations for an approximately triangular well potential with finite confinement, achieved using first-order perturbation theory. No fitting parameters are used. Results obtained using our model are in good agreement with numerical results (obtained using the finite difference method) for a wide range of bias conditions (from OFF- to ON-states) and Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>x</i></sub> Ga <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{{1}-{x}}\text{N}$ </tex-math></inline-formula> spacer mole fractions.

Classification SINGLE-LEAD ECG by using conventional neural network algorithm

Cardiac disease, including atrial fibrillation (AF), is one of the biggest causes of morbidity and mortality in the world, accounting for one third of all deaths. Cardiac modelling is now a well-established field. The Convolutional Neural Network (CNN) algorithm offer a valuable way of gaining insight into the dynamic behaviors of the heart, in normal and pathological conditions. Great efforts have been put into modelling the ventricles, whilst the atria have received less focus. This research therefore concentrates on developing models of the heart ECG atria using deep learning. The research developed an experimental result on MIT-BIH dataset for modelling myocyte electrophysiology and excitation waves in 1D & 2D tissues. It includes optimizations such as adaptive stimulus protocols. As examples of application, it is used to investigate effects of a novel anion bearing current on heart atrial excitation and the effect of remodeling on atrial myocyte electrical heterogeneity. A computationally efficient CNN anatomically based model of the heart atria is constructed. The 3D-CNN model includes heterogeneous, biophysically detailed electrophysiology and conduction anisotropy. The full model activates in 121 ms in heart rhythm, in close agreement with clinical ECG data. The model is used, with the toolkit, to investigate the function effects of S140G mutation in MIT-BIH dataset which is associated with familial. The 3D-CNN model forms the core of a boundary element model of the P-wave Body Surface Potential (BSP). The CNN model incorporates representations of the heart blood masses. Generated ECGs show qualitative agreement with clinical data. Their morphology is as expected for a healthy person, with a lead duration of 103 ms. The CNN model is used to verify an existing algorithm for focal atrial tachycardia location and in providing explanation for a novel clinical phenomenon, using CNN with 99.27% accuracy. Models of the human atria and body surface potential are constructed. The models are validated against both experimental and clinical data. These models are suitable to use as the platform for further research.

A comprehensive physics based surface potential and drain current model for SiGe channel dual programmable FETs

In the present work, a comprehensive analytical model for surface potential and drain current has been developed for double gate silicon-germanium channel dual programmable FETs (SiGe-DP-FET) which is capable to conduct both in n- as well as p-modes. The developed model accurately predicts the impact of mole fraction (m) variation in Si(1 − m)Ge m channel on various device characteristics such as energy band, surface potential, electric field, drain current, and transconductance. While deriving the surface potential expression, the active SiGe channel is bifurcated in three regions such that regions I and III denote the two gated regions while region II denotes the ungated region. Further, in order to compute the expression for surface potential, 2D Poisson’s equation has been solved in gated regions while linear approximation has been applied in ungated region and subsequently, the drain current expression has been obtained by integrating the band-to-band generation rate of charge carriers across the source side Schottky junctions. Moreover, in order to validate the proposed model, the analytical results are compared and verified with 2D TCAD ATLAS simulated results and it has been observed that the results obtained using proposed model match well with the simulated results.