A semi-empirical approach to calibrate simulation models for semiconductor devices

• Published in: Scientific reports Vol. 13; no. 1; p. 10436
• Main Authors: Jaiswal, Rahul, Martínez-Ramón, Manel, Busani, Tito
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.06.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/987; 639/4077/909/4101; 639/705/1042; 639/705/1046; Business metrics; Calibration; Datasets; Digital twins; Humanities and Social Sciences; Learning algorithms; Machine learning; multidisciplinary; Photovoltaic cells; Photovoltaics; Prediction models; Science; Science (multidisciplinary); Silicon; Simulation; Solar cells

Semiconductor device optimization using computer-based prototyping techniques like simulation or machine learning digital twins can be time and resource efficient compared to the conventional strategy of iterating over device design variations by fabricating the actual device. Ideally, simulation mo...