Seyed Mahdi Mastoor

collaborators

3 papers

cond-mat.mtrl-sci2026

Multilayer Screening of Double and Conventional Perovskite Solar Cells Using SCAPS-1D and Machine Learning: Optimization of ETL, HTL, and Absorber for High-Efficiency Architectures

Neda Nasiri, Seyed Mahdi Mastoor, Amirhosein Ahmadkhan Kordbacheh

The combinatorial design space of multilayer perovskite solar cells is vast, yet exhaustive experimental or computational screening of all possible material combinations remains im…

cond-mat.mes-hall2025

Geometry-Driven Charge and Spin Transport in $β 12$ Borophene Quantum Dots

Seyed Mahdi Mastoor, Amirhossein Ahmadkhan Kordbacheh

Theoretical research has been conducted to study how geometry affects charge and spin transport in $β 12$ borophene quantum dots, which are confined systems. The study exam…

cond-mat.mes-hall2025

Scalable Machine Learning Models for Predicting Quantum Transport in Disordered 2D Hexagonal Materials

Seyed Mahdi Mastoor, Amirhossein Ahmadkhan Kordbacheh

We introduce scalable machine learning models to accurately predict two key quantum transport properties, the transmission coefficient T(E) and average local density of states (Ave…

Multilayer Screening of Double and Conventional Perovskite Solar Cells Using SCAPS-1D and Machine Learning: Optimization of ETL, HTL, and Absorber for High-Efficiency Architectures

Geometry-Driven Charge and Spin Transport in β12 Borophene Quantum Dots

Scalable Machine Learning Models for Predicting Quantum Transport in Disordered 2D Hexagonal Materials

Geometry-Driven Charge and Spin Transport in $β 12$ Borophene Quantum Dots