About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Late News Poster Session
|
| Presentation Title |
H-38: Prediction of Schottky Barrier Heights From First-Principles Calculations |
| Author(s) |
Viviana Faride Dovale Farelo, Kamal Choudhary |
| On-Site Speaker (Planned) |
Viviana Faride Dovale Farelo |
| Abstract Scope |
Accurate prediction of Schottky barrier heights (SBHs) at metal–semiconductor (M–SC) interfaces is crucial for understanding charge injection processes in electronic and optoelectronic devices. However, conventional density functional theory (DFT) methods often struggle to simultaneously capture the semiconductor bandgap and the metal Fermi level, limiting their predictive accuracy. In this study, we employ a combined DFT and machine learning framework to compute SBHs across diverse M–SC systems. Our approach builds upon the JARVIS-DFT database and integrates interface generation via the Zur algorithm implemented in InterMat, along with pre-relaxation using the ALIGNN-FF force field. This enables automated and realistic modeling of interface structures. We apply the workflow to silicon-based interfaces with Al, Cu, Ag, and Au metals. Multiple exchange-correlation functionals are evaluated to identify the most accurate approach for SBH prediction, with results benchmarked against experimental data. |
| Proceedings Inclusion? |
Undecided |
| Keywords |
Computational Materials Science & Engineering, Machine Learning, Modeling and Simulation |