TY - GEN
T1 - Machine learning approach to predicting tunnel field-effect transistors
AU - Akbar, Chandni
AU - Thoti, Narasimhulu
AU - Li, Yi-Ming
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/19
Y1 - 2021/4/19
N2 - We for the first time investigate the possibility to replace the device simulation for tunnel field-effect transistors (TFETs) with a machine learning (ML) algorithm. By incorporating the experimentally validated device simulation, a keyML technique named random forest regression (RFR) model is advanced and applied to predict characteristics of TFETs. The results of this work may benefit the design and fabrication of TFETs based on the well-trained RFR model. Very fast and accurate drain current (ID) prediction in terms of the engineering acceptable root-mean-square (RMSE) error inaugurates TFET technology with ML with a potential application to significantly reduce the computational cost.
AB - We for the first time investigate the possibility to replace the device simulation for tunnel field-effect transistors (TFETs) with a machine learning (ML) algorithm. By incorporating the experimentally validated device simulation, a keyML technique named random forest regression (RFR) model is advanced and applied to predict characteristics of TFETs. The results of this work may benefit the design and fabrication of TFETs based on the well-trained RFR model. Very fast and accurate drain current (ID) prediction in terms of the engineering acceptable root-mean-square (RMSE) error inaugurates TFET technology with ML with a potential application to significantly reduce the computational cost.
UR - http://www.scopus.com/inward/record.url?scp=85108160609&partnerID=8YFLogxK
U2 - 10.1109/VLSI-TSA51926.2021.9440136
DO - 10.1109/VLSI-TSA51926.2021.9440136
M3 - Conference contribution
AN - SCOPUS:85108160609
T3 - VLSI-TSA 2021 - 2021 International Symposium on VLSI Technology, Systems and Applications, Proceedings
BT - VLSI-TSA 2021 - 2021 International Symposium on VLSI Technology, Systems and Applications, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2021
Y2 - 19 April 2021 through 22 April 2021
ER -