MLFoMpy: A post-processing tool for semiconductor TCAD data with machine-learning capabilities
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.
Authors
- Antonio J. García‐Loureiro (ORCID: https://orcid.org/0000-0003-0574-1513)
- Julián G. Fernández (ORCID: https://orcid.org/0000-0002-1347-4577)
- Enrique Comesaña (ORCID: https://orcid.org/0000-0001-8422-5394)
- Natalia Seoane (ORCID: https://orcid.org/0000-0003-0973-461X)
Institutions
- Universidade de Santiago de Compostela (ES)
- Center for Research in Molecular Medicine and Chronic Diseases (ES)
Publication Details
- Journal
- SoftwareX
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1016/j.softx.2025.102166
- Citations
- 1
- Primary Topic
- Advancements in Semiconductor Devices and Circuit Design
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- Xunta de Galicia
- European Regional Development Fund
- Agencia Estatal de Investigación