Weihang Shi - IEEE Xplore Author Profile

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Author details

Weihang Shi

Publications

2

Citations

21

Publications by Year

20222023

Co-Authors:

Wenwu WangKun WuJin WuLei Zhu

Weihang Shi

Affiliation

School of Information Science and Engineering

Wuhan University of Science and Technology

Wuhan, China

Publication Topics

Anomaly Detection,
Defect Region,
Memory Module,
Normal Samples,
Ability Of The Network,
Abnormal Samples,
Anomaly Detection Methods,
Anomaly Score,
Area Under Curve,
Attention Mechanism,
Characteristic Components,
Code Vector

Biography

Weihang Shi received the B.S. degree from the School of Information Science and Engineering, Wuhan University of Science and Technology, where he is currently pursuing the master’s degree. His research interests include computer vision and pattern recognition.(Based on document published on 4 October 2022).

Publications

2

Citations

21

Publications by Year

20222023

Co-Authors:

Wenwu Wang
Kun Wu
Jin Wu
Lei Zhu

Author's Published Works

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Showing 1-25 of 57 results

Conferences (43)

Journals (13)

Early Access Articles (1)

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K P Pradhan(30)
K. P. Pradhan(19)
Rameez Raja Shaik(13)
V Rajakumari(9)
S. Routray(8)
Department of ECE, IIITDM Kancheepuram, Chennai, India(11)
Indian Institute of Information Technology Design and Manufacturing (IIITDM), Kancheepuram, Chennai, India(6)
Department of Electrical Engineering, National Institute of Technology (NIT), Rourkela, Odisha, India(4)
ECE Department, IIITDM Kancheepuram, Chennai, India(3)
Department of ECE, SRM Institute of Science and Technology, Chennai, India(3)
2020 5th IEEE International Conference on Emerging Electronics (ICEE)(5)
IEEE Transactions on Nanotechnology(5)
IEEE Transactions on Electron Devices(4)
2020 4th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)(3)
2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)(3)
IEEE(57)
Media(1)
New Delhi, India(6)
Mumbai, India(5)
Coimbatore, India(4)
Penang, Malaysia(3)
Vancouver, BC, Canada(3)
Drain Current(20)
Transconductance(16)
Field-effect Transistors(12)
Band Gap(11)
Device Simulation(10)

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Evaluation of FONOS FDSOI FET for Synapse Inspired Artificial Neural Network

Rameez Raja Shaik;K P Pradhan

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Year: 2025 | Early Access Article |

In this article, a well calibrated FDSOI ferroelectric (Fe)-FET/FeFET is gate-stacked with a charge trap nitride (CTN) for investigating memory and synaptic applications. The CTN is sandwiched between Fe and silicon channel of FeFET to obtain ferroelectric/ oxide/nitride/oxide/semiconductor (FONOS) FET for improved memory and synaptic applications. This approach of using both Fe and CTN layers to ...Show More

Evaluation of FONOS FDSOI FET for Synapse Inspired Artificial Neural Network

Rameez Raja Shaik;K P Pradhan

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Year: 2025 | Early Access Article |

Comparative Assessment of Charge Sharing and Charge Coupling Circuits: An Approach for Optimal In-Memory Computing

Anshuman Bhasker;Ankit Lodhi;K P Pradhan

2024 7th International Conference on Devices, Circuits and Systems (ICDCS)

Year: 2024 | Conference Paper |

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This study investigates and compares the energy efficiency, signal delay, Energy-Delay Product (EDP), and Power-Delay Product (PDP) characteristics of two widely used charge storage and transfer techniques: charge sharing and charge coupling, within the context of memory computing cells. The aim is to identify the most suitable circuit for facilitating Multiply-Accumulate (MAC) operations crucial ...Show More

Comparative Assessment of Charge Sharing and Charge Coupling Circuits: An Approach for Optimal In-Memory Computing

Anshuman Bhasker;Ankit Lodhi;K P Pradhan

2024 7th International Conference on Devices, Circuits and Systems (ICDCS)

Year: 2024 | Conference Paper |

Novel Ferro-Oxide-Nitride-Oxide-Semiconductor (FONOS) FDSOI FET Towards Memory and Synaptic Applications

Rameez Raja Shaik;K P Pradhan

2023 IEEE 23rd International Conference on Nanotechnology (NANO)

Year: 2023 | Conference Paper |

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In this work, a charge trapping nitride (CTN) assisted memory window (MW) boosting by a novel ferroelectric-oxide-nitride-oxide-semiconductor (FONOS) based memory FET is investigated. The proposed architecture is obtained by a calibrated state-of-art Si: HfO2 FDSOI FeFET TCAD numerical simulations. The calibrated FeFET is further added with charge-trapping-memory and tunnelling models to incorpora...Show More

Novel Ferro-Oxide-Nitride-Oxide-Semiconductor (FONOS) FDSOI FET Towards Memory and Synaptic Applications

Rameez Raja Shaik;K P Pradhan

2023 IEEE 23rd International Conference on Nanotechnology (NANO)

Year: 2023 | Conference Paper |

Prediction of Performance Metrics of Nanosheet Field Effect Transistor with LR and RFR Machine Learning Models

R.B. Naveen Kumar;V Rajakumari;S.R Routray;K.P. Pradhan

2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI)

Year: 2023 | Conference Paper |

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In this article, a distinctive strategy is carried out by the combination of machine learning and TCAD device modeling to predict the important performance metrics of the device. Device expertise is required to extract the features like threshold voltage (Vth), on-state current (Ion), subthreshold swing (SS), off-state current (Ioff), Ion/Ioff ratio, and transconductance (gm) of the vertically sta...Show More

Prediction of Performance Metrics of Nanosheet Field Effect Transistor with LR and RFR Machine Learning Models

R.B. Naveen Kumar;V Rajakumari;S.R Routray;K.P. Pradhan

2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI)

Year: 2023 | Conference Paper |

Development of an Accurate Model for Memristor based Temperature Sensor

Bhargav N C;Akkala Vikas;K P Pradhan;Tejendra Dixit

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Memristors are a unique class of electronic devices and have been considered one of the basic circuit elements along with Resistors, Capacitors, and Inductors. A memristor's built-in nonlinear ability is to remember how much charge has passed through it, and memristance is a charge-dependent resistance. This memristance is a variable value that depends on the change in width of the doped region (s...Show More

Development of an Accurate Model for Memristor based Temperature Sensor

Bhargav N C;Akkala Vikas;K P Pradhan;Tejendra Dixit

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)

Year: 2023 | Conference Paper |

1T FDSOI Based LIF Neuron Without Reset Circuitry: A proposal and Investigation

V Rajakumari;S R Panda;K P Pradhan

2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)

Year: 2023 | Conference Paper |

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In this article, an FDSOI-based neuron is demonstrated to mimic the functionalities of LIF neuron. As the proposed device-based neuron utilizes the single transistor latch (STL) mechanism and it takes the current input and voltage output in the shape of a spike, it does not require any extra circuit for reset. Furthermore, the proposed neuron shows an impressive energy consumption per spike i.e., ...Show More

1T FDSOI Based LIF Neuron Without Reset Circuitry: A proposal and Investigation

V Rajakumari;S R Panda;K P Pradhan

2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)

Year: 2023 | Conference Paper |

A Robust-Compact Model to Emulate Neuro-Mimetic Dynamics With Doped-HfO2 Ferroelectric-FET Based Neurons

Rameez Raja Shaik;L Chandrasekar;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

Cited by: Papers (5)

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A leap towards deriving a robust-compact model for ferroelectric-FET (FeFET) oscillator based spiking neurons has been developed. The compact model can capture and emulate neurons that exhibit both excitatory and inhibitory coupled dynamical behaviour, native to cortical neurons. The proposed model can reliably mimic neuronal dynamics for a broad-spectrum of FeFETs when, factored with appropriate ...Show More

A Robust-Compact Model to Emulate Neuro-Mimetic Dynamics With Doped-HfO2 Ferroelectric-FET Based Neurons

Rameez Raja Shaik;L Chandrasekar;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

BTBT Based LIF Junctionless FET Neuron With Plausible Mimicking Efficiency

V Rajakumari;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

Cited by: Papers (6)

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Amid the quest for nanoscale devices to mimic the biological neuronal dynamics, this article demonstrates a SOI Junctionless Field Effect Transistor (JLFET) based leaky integrate and fire (LIF) neuron in sub-20 nm technology. The band-to-band-tunneling (BTBT) mechanism is considered to imitate the leaky-integration behavior. As JLFET has strongly doped channel that supports fully depletion in the ...Show More

BTBT Based LIF Junctionless FET Neuron With Plausible Mimicking Efficiency

V Rajakumari;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

Investigation on Impact of Doped HfO$_{2}$ Thin Film Ferro-Dielectrics on FDSOI NCFET Under Back-Gate Bias Influence

Rameez Raja Shaik;K. P. Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

Cited by: Papers (3)

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In this article, negative capacitance effect on metal-ferro-metal-insulator-semiconductor (MFMIS) type FDSOI negative-capacitance-FET (NCFET) has been investigated by considering two well known thin-film ferro-dielectric ($ Fe$) materials HZO (zirconium:HfO$_{2}$) and HSO (silicon:HfO$_{2}$). The investigations are carried out in a well calibrated TCAD environment, where the gate-charge ($ Q_{G}$)...Show More

Investigation on Impact of Doped HfO$_{2}$ Thin Film Ferro-Dielectrics on FDSOI NCFET Under Back-Gate Bias Influence

Rameez Raja Shaik;K. P. Pradhan

IEEE Transactions on Nanotechnology

Year: 2023 | Volume: 22 | Journal Article |

An Analytical Model to Emulate the Biological Synapses Using B or N Substitution Doped Graphene FET With Hysteresis Engineering

L Chandrasekar;Rameez Raja Shaik;V Rajakumari;K P Pradhan

2022 IEEE International Conference on Emerging Electronics (ICEE)

Year: 2022 | Conference Paper |

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An analytical model for boron (B) or nitrogen (N) substitution doped graphene field effect transistor (GFET) with non-zero band gap and interface traps has been proposed to emulate the biological synapses. The synaptic plasticity has been accomplished by utilizing the hysteresis conduction behaviour manifested through channel and gate-insulator interface traps. The proposed metal-insulator-graphen...Show More

An Analytical Model to Emulate the Biological Synapses Using B or N Substitution Doped Graphene FET With Hysteresis Engineering

L Chandrasekar;Rameez Raja Shaik;V Rajakumari;K P Pradhan

2022 IEEE International Conference on Emerging Electronics (ICEE)

Year: 2022 | Conference Paper |

A Robust-Compact Model to Imitate the Neuronal Dynamics with 2T based FeFET-MOSFET Capturing Temperature Effects

Rameez Raja Shaik;L Chandrasekar;V Rajakumari;Kumar Prasannajit Pradhan

2022 IEEE International Conference on Emerging Electronics (ICEE)

Year: 2022 | Conference Paper |

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In this work, a robust-compact model based on 2T-ferroelectric FET (FeFET)-MOSFET oscillator based spiking neurons is developed and investigated for external temperature effects. The compact model is rigorously tuned and validated to existing literature for improving the accuracy of investigations. Emulation of neurons that can exhibit both the excitatory and inhibitory dynamics that are typically...Show More

A Robust-Compact Model to Imitate the Neuronal Dynamics with 2T based FeFET-MOSFET Capturing Temperature Effects

Rameez Raja Shaik;L Chandrasekar;V Rajakumari;Kumar Prasannajit Pradhan

2022 IEEE International Conference on Emerging Electronics (ICEE)

Year: 2022 | Conference Paper |

RF Linearity/Non-Linearity FoMs of FDSOI NCFET in presence of interface trap charges

Vullakula Rama Seshu;Rameez Raja Shaik;V Rajakumari;K P Pradhan

2022 IEEE 19th India Council International Conference (INDICON)

Year: 2022 | Conference Paper |

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In this work, linearity of 22 nm FDSOI NCFET in presence of oxide-semiconductor interface trap charges has been systematically examined. To simulate the metal-ferroelectric-metal-insulator-semiconductor (MFMIS) type NCFET, a well calibrated TCAD tool has been used. Firstly, the underlying MIS structure has been constructed and simulated in the TCAD. Subsequently, a 1D - Landau Khalatnikov model (1...Show More

RF Linearity/Non-Linearity FoMs of FDSOI NCFET in presence of interface trap charges

Vullakula Rama Seshu;Rameez Raja Shaik;V Rajakumari;K P Pradhan

2022 IEEE 19th India Council International Conference (INDICON)

Year: 2022 | Conference Paper |

Theoretical Analysis of Dielectric Assisted Tamm Mode Excitation

Amit Kumar Goyal;K. P. Pradhan;Yehia Massoud

2022 IEEE 22nd International Conference on Nanotechnology (NANO)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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In this paper, a dielectric material assisted excitation mechanism is proposed to confine Tamm Modes at the dielectric-air interface. The performance analysis of proposed structure is performed using transfer matrix method (TMM). The design comprises a bilayer one-dimensional photonic crystal structure having a top defect layer. The defect layer thickness, and incident angles are optimized to conf...Show More

Theoretical Analysis of Dielectric Assisted Tamm Mode Excitation

Amit Kumar Goyal;K. P. Pradhan;Yehia Massoud

2022 IEEE 22nd International Conference on Nanotechnology (NANO)

Year: 2022 | Conference Paper |

Contribution of Carrier Quantization Effect towards Performance of Nanostructured CFTS/CFTSe Solar Cells

Shibi Varku;S. Routray;K. P. Pradhan

2022 IEEE Latin American Electron Devices Conference (LAEDC)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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In this work, a detailed analysis is carried out to evaluate the performance enhancement of CFTS solar cell with the inclusion of nano-structures. Multiple quantum well (QW) with CFTSe/CFTS as well constituents are embedded into the cell structure to maximize the power conversion efficiency. Numerical modeling of the cell structure is carried out with optimized parameters and analyzed. The perform...Show More

Contribution of Carrier Quantization Effect towards Performance of Nanostructured CFTS/CFTSe Solar Cells

Shibi Varku;S. Routray;K. P. Pradhan

2022 IEEE Latin American Electron Devices Conference (LAEDC)

Year: 2022 | Conference Paper |

Investigation on Electrical and Optical Properties of Cu2FeSnSe4 (CFTSe) Based Thin Film Solar Cell for Terrestrial Applications

Marikanti Aravind;Shibi Varku;K. P. Pradhan;S. Routray

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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Copper-based quaternery chalcogenides such as Cu2ZnSnS4(CZTS), Cu2ZnSnS4(CZTSe), Cu2ZnSn $(S_{x} Se_{1-x})_{4}$ and Cu2FeSnSe4(CFTSe) have started grabbing attention as a suitable absorber layer. However, Cu2FeSnSe4 is not as much explored material as CZTS. In the work, the study of different physical properties on CFTSe power conversion efficiency is analyzed. Discussed the numerical investigatio...Show More

Investigation on Electrical and Optical Properties of Cu2FeSnSe4 (CFTSe) Based Thin Film Solar Cell for Terrestrial Applications

Marikanti Aravind;Shibi Varku;K. P. Pradhan;S. Routray

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

Understanding the Effect of Interface Trap States on Electrical and Optical Performance of CFTS Thin Film Solar Cell

Shibi Varku;S. Routray;K. P. Pradhan

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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The urge to find new material which can be used for photon absorption in solar cell is never ending. Over the decades, chalcogenides have received attention as potential absorber layer. Copper based chalcogenides such as Cu2ZnSnS4(CZTS), Cu2ZnSnSe4 (CZTSe), Cu2ZnSn $(S_{x}Se_{1-x})_{4}$, Cu2FeSnS4 (CFTS) are being explored. However, the efficiency of CFTS solar cell is not remarkable due to presen...Show More

Understanding the Effect of Interface Trap States on Electrical and Optical Performance of CFTS Thin Film Solar Cell

Shibi Varku;S. Routray;K. P. Pradhan

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

An Energy Efficient LIF Neuron Based on Bulk MOSFET with an n+ Buried Layer

Ametha Sri Sai Dhruthi;V Rajakumari;K P Pradhan

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

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This paper presents a CMOS compatible Bulk MOSFET with an n+ buried layer based leaky integrate and fire (LIF) neuron using properly calibrated 2-D TCAD simulations. The area of the proposed LIF neuron is $0.0507\mu m^{2}$. The device's reduced size allows for the integration of more LIF neurons into the network. The energy per spike of the proposed device is 4.16pJ/spike at a supply voltage of 2....Show More

An Energy Efficient LIF Neuron Based on Bulk MOSFET with an n+ Buried Layer

Ametha Sri Sai Dhruthi;V Rajakumari;K P Pradhan

2022 IEEE Region 10 Symposium (TENSYMP)

Year: 2022 | Conference Paper |

Demonstration of an UltraLow Energy PD-SOI FinFET Based LIF Neuron for SNN

V Rajakumari;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2022 | Volume: 21 | Journal Article |

Cited by: Papers (11)

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In this article, partially depleted silicon on insulator (PD-SOI) FinFET based LIF neuron is demonstrated to mimic biological neuronal behaviour with aid of well-calibrated 3D TCAD simulation. The floating body effect of PD-SOI FinFET is used to store the holes generated by the impact ionisation (‘II’), which exhibits the integration phenomenon and recombination manifests the leaky function. It sh...Show More

Demonstration of an UltraLow Energy PD-SOI FinFET Based LIF Neuron for SNN

V Rajakumari;K P Pradhan

IEEE Transactions on Nanotechnology

Year: 2022 | Volume: 21 | Journal Article |

Computationally Efficient Region-Wise Potential- Based Extremely Closed-Form Analytical Modeling of B/N Substitution Doped GFETs

L. Chandrasekar;K. P. Pradhan

IEEE Transactions on Electron Devices

Year: 2022 | Volume: 69, Issue: 8 | Journal Article |

Cited by: Papers (2)

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A simplified region-wise potential-based analytical model is established for boron (B) or nitrogen (N) substitution doped graphene field-effect transistor (GFET). The closed-form direct analytical relation between graphene channel potential and applied bias condition is developed by imposing the effective approximation for Fermi–Dirac integral function in various regions of operation. The boundary...Show More

Computationally Efficient Region-Wise Potential- Based Extremely Closed-Form Analytical Modeling of B/N Substitution Doped GFETs

L. Chandrasekar;K. P. Pradhan

IEEE Transactions on Electron Devices

Year: 2022 | Volume: 69, Issue: 8 | Journal Article |

Investigation of Temperature Variation on a HSO Ferroelectric FDSOI NCFET

Rameez Raja Shaik;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

Cited by: Papers (4)

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In this work, temperature effect on MFMIS type FDSOI NCFET is investigated considering a well known thin film ferroelectric material HSO (Silicon doped HfO2). The current investigations are performed in a TCAD environment where the underlying gate charge is obtained using TCAD simulation to computing ferro voltage across the HSO ferroelectric capacitor to find the total gate voltage in the gate-st...Show More

Investigation of Temperature Variation on a HSO Ferroelectric FDSOI NCFET

Rameez Raja Shaik;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

Modeling and Investigation of Electronic Transport Properties of Boron or Nitrogen Substitution Doped Single Layer Graphene

L Chandrasekar;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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The key electronic property - interaction parameter $(r_{s})$ for boron (B) or nitrogen (N) substitution doped single layer graphene is analytically modeled. Further, the interaction parameter paves a route to explore the vital transport properties such as scattering time $(\tau)$, conductivity $(\sigma)$, and mobility $(\mu)$, which have been investigated for B/N substitution doped graphene in th...Show More

Modeling and Investigation of Electronic Transport Properties of Boron or Nitrogen Substitution Doped Single Layer Graphene

L Chandrasekar;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

A Proposal of Energy Efficient Ferroelectric PDSOI LIF Neuron for Spiking Neural Network Applications

P Sowparna;V Rajakumari;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

Cited by: Papers (4)

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The proposed device is a partially depleted silicon on insulator (PD-SOI) with a ferroelectric material as a part of gate stack structure demonstrating the functions of leaky integrate and fire (LIF) neurons with a minimum energy of 9.375 pJ/spike and area of $0.25\ \mu \mathrm{m}^{2}$. A high-k ferroelectric (FE) dielectric in the gate stack improves the energy performance by reducing the subthre...Show More

A Proposal of Energy Efficient Ferroelectric PDSOI LIF Neuron for Spiking Neural Network Applications

P Sowparna;V Rajakumari;K P Pradhan

2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)

Year: 2021 | Conference Paper |

Effect of Temperature on Performance of HZO-Based FD-SOI NCFET

Vullakula Rama Seshu;Rameez Raja Shaik;K P Pradhan

2021 Joint International EUROSOI Workshop and International Conference on Ultimate Integration on Silicon (EuroSOI-ULIS)

Year: 2021 | Conference Paper |

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In this study, the temperature effect on Zirconium doped HfO2 (HZO) based Metal-Ferroelectric-Metal-Insulator-Semiconductor (MFMIS) type Fully depleted Silicon on Insulator (FDSOI) negative capacitance field effect transistor (NCFET) has been investigated in ATLAS TCAD. The MIS device simulation has been performed in TCAD and its gate charge (QG) has been extracted. The extracted charge is further...Show More

Effect of Temperature on Performance of HZO-Based FD-SOI NCFET

Vullakula Rama Seshu;Rameez Raja Shaik;K P Pradhan

2021 Joint International EUROSOI Workshop and International Conference on Ultimate Integration on Silicon (EuroSOI-ULIS)

Year: 2021 | Conference Paper |

Impact of HZO and HSO thin film ferroelectric on FDSOI NCFET

Rameez Raja Shaik;K P Pradhan

2021 IEEE 21st International Conference on Nanotechnology (NANO)

Year: 2021 | Conference Paper |

Cited by: Papers (3)

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In this work, negative capacitance effect of MFMIS type FDSOI NCFET is investigated considering two well known thin film ferroelectric materials HZO (Zirconium doped HfO2) and HSO (Silicon doped HfO2). The investigations are carried out in a TCAD environment where the gate charge is extracted from the TCAD simulation and subsequently computed ferro voltage across the ferroelectric capacitor to fin...Show More

Impact of HZO and HSO thin film ferroelectric on FDSOI NCFET

Rameez Raja Shaik;K P Pradhan

2021 IEEE 21st International Conference on Nanotechnology (NANO)

Year: 2021 | Conference Paper |

Self-Consistent Modeling of B or N Substitution Doped Bottom Gated Graphene FET With Nonzero Bandgap

L. Chandrasekar;K. P. Pradhan

IEEE Transactions on Electron Devices

Year: 2021 | Volume: 68, Issue: 7 | Journal Article |

Cited by: Papers (6)

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A phenomenological all region drain current model for boron (B) or nitrogen (N) substitution-doped bottom gated graphene field effect transistor (GFET) is developed. In this work, a self-consistent approach is utilized to obtain appropriate potential-charge relation. The effects of substitution doping such as shift in Dirac point with significant nonzero bandgap, change in carrier sheet density an...Show More

Self-Consistent Modeling of B or N Substitution Doped Bottom Gated Graphene FET With Nonzero Bandgap

L. Chandrasekar;K. P. Pradhan

IEEE Transactions on Electron Devices

Year: 2021 | Volume: 68, Issue: 7 | Journal Article |

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