Results 61 to 70 of about 11,517 (220)

Leveraging Gate and Channel Engineering in Graphene Tunnel FET (GTFET) at Nano-Scale for Better Device Performance

Журнал нано- та електронної фізики
This research work mainly focuses on various gate and channel engineering performed on typical tunnel field effect transistors (TFETs) at nano scale. This step-by-step development of typical nano device TFET model is showcased in this research work, in ...
R. Dutta, D. Das
doaj   +1 more source

Analytics-statistics mixed training and its fitness to semisupervised manufacturing.

PLoS ONE, 2019
While there have been many studies using machine learning (ML) algorithms to predict process outcomes and device performance in semiconductor manufacturing, the extensively developed technology computer-aided design (TCAD) physical models should play a ...
Parag Parashar, Chun Han Chen, Chandni Akbar, Sze Ming Fu, Tejender S Rawat, Sparsh Pratik, Rajat Butola, Shih Han Chen, Albert S Lin   +8 more
doaj   +1 more source

A Generalizable Framework for Building Executable Domain‐Specific Large Language Models Under Data Scarcity: Demonstration on Semiconductor Technology Computer‐Aided Design Simulation

Advanced Intelligent Systems, EarlyView.
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang, Zhenhua Wu, Yu Liu, Kai Chang, Shaohua Wu   +4 more
wiley   +1 more source

Intelligent Manufacturing: TCAD-Assisted Adaptive Weighting Neural Networks

IEEE Access, 2018
Using machine intelligence on device and process performance prediction is an emerging methodology in the IC industry. While semiconductor technology computer-aided design (TCAD) has been researched and developed for over 30 years, it should contribute ...
Chien Y. Huang, Sze M. Fu, Parag Parashar, Chun H. Chen, Chandni Akbar, Albert S. Lin   +5 more
doaj   +1 more source

Bayesian Optimization–Reinforcement Learning Hybrid Framework for a‐IGZO Thin‐Film Transistor Compact Model Parameter Extraction in 2T0C Dynamic Random Access Memory Applications

Advanced Intelligent Systems, EarlyView.
A training‐free two‐stage BO–RL framework extracts compact model parameters for a‐IGZO TFTs, reaching BO‐level fitting quality at a constant per‐simulation optimization cost. Bayesian optimization performs exploration and provides an optimized starting point.
Seunghyun Son, Taejun Ha, Taeyoung Nam, Yoonyoung Chung, Sunmean Kim   +4 more
wiley   +1 more source

Beyond ideal models: non-idealities in TCAD simulations of dielectric-modulated FETs for label-free biosensing

Frontiers in Electronics
Dielectric modulation in field-effect transistors (FETs) for label-free biosensing have been extensively explored to date, mostly due to the availability of semiconductor device technology computer-aided design (TCAD) tools.
Rupam Goswami, Vivek Menon U, Suman Kumar Mitra, Deepjyoti Deb, Prachuryya Subash Das, Hirakjyoti Choudhury, Raja Vipul Gautam   +6 more
doaj   +1 more source

Hardware‐Efficient Locality‐Preserving Graph Processing via Ferroelectric Fowler–Nordheim Tunneling Crossbar Array

Small, EarlyView.
Real‐world graph data are directly mapped onto an mCBA, enabling node similarity to be computed through a single current readout. Strongly nonlinear devices suppress long‐range multi‐hop contributions while preserving local connectivity, whereas weakly nonlinear devices allow excessive signal propagation.
Jae‐Hyun Lee, Jun‐Young Park, Jeong‐Min Lee, Hyun‐Jun Kang, Seon‐Jin Yoo, Ki‐Nam Park, Yoon Ho Jang, Joon‐Kyu Han   +7 more
wiley   +1 more source

Structure and Thermal Properties of 2,2′-Azobis(1H-Imidazole-4,5-Dicarbonitrile)—A Promising Starting Material for a Novel Group of Energetic Compounds

Molecules, 2020
A high-nitrogen compound, 2,2′-azobis(1H-imidazole-4,5-dicarbonitrile) (TCAD), was synthesized from commercially available 2-amino-1H-imidazole-4,5-dicarbonitrile. It was characterized with infrared and nuclear magnetic resonance spectroscopy.
Rafał Lewczuk, Maria Książek, Katarzyna Gańczyk-Specjalska, Katarzyna Cieślak   +3 more
doaj   +1 more source

Microscopic Stress Analysis of Silicon Carbide Devices Under Overcurrent Conditions in DC Solid‐State Circuit Breakers

IET Smart Energy Systems, EarlyView.
A coupled Saber–TCAD–thermo‐mechanical simulation framework is proposed to evaluate microscopic stresses in SiC MOSFETs under overcurrent operation. Ultrahigh gate‐voltage driving reduces thermal and mechanical stress but increases gate oxide electric‐field stress, revealing a reliability tradeoff for DC solid‐state circuit breakers.
Bin Yu, Jiawei Qin, Liang Chen, Zehua Dai   +3 more
wiley   +1 more source

TCAD Modeling of Strain-Engineered MOSFETs

, 2006
The rapid rise of standby power in nanoscale MOSFETs is slowing classical scaling and threatening to derail continued improvements in MOSFET performance.
Lee Smith
core   +1 more source