RT Journal Article
T1 MLFoMpy: A post-processing tool for semiconductor TCAD data with machine-learning capabilities
A1 Comesaña Figueroa, Enrique
A1 García Fernández, Julián
A1 Seoane Iglesias, Natalia
A1 García Loureiro, Antonio Jesús
K1 Semiconductor device modeling
K1 Nanoelectronics
K1 Data processing
K1 Machine learning
K1 Python
K1 Pytorch
AB We present MLFoMpy, a Python package for post-processing data from semiconductor device simulations. The software automatically extracts key figures of merit from current–voltage curves of field effect transistor and calculates statistical analyses for these curves. MLFoMpy also includes machine learning tools to predict figures of merit and current–voltage curves for devices with intrinsic variability. Additionally, it offers data visualization tools to plot current–voltage curves and statistical graphs.
PB Elsevier
SN 2352-7110
YR 2025
FD 2025-05
LK https://hdl.handle.net/10347/45320
UL https://hdl.handle.net/10347/45320
LA eng
NO SoftwareX Volume 30, May 2025, 102166
NO The work presented in this paper is funded by the Xunta de Galicia and FEDER funds (ED431F 2020/008, ED431C 2022/16) and by the Agencia Estatal de Investigación (PID2022-141623NB-I00, PID2022-142709OB-C21/PID2022-142709OA-C22).
DS Minerva
RD 24 abr 2026