Comparative Analysis of Machine Learning Approaches on the Prediction of the Electronic Properties of Perovskite: A Case Study of the ABX3 and A2BB’X6

Framework for the Simulation of Temperature Dependent Semiconductor Parameters in Silicon Solar Cells and their Respective Impact on the Current Density-Voltage Characteristic

Automatic Prediction of Band Gaps of Inorganic Materials using Machine Learning

Process UV-Vis absorption spectra, make Tauc transformation for direct/indirect allowed transition, extract band gap values for corresponding transition type, and plot figures

Calculation of the edge potentials of valence and conduction bands. The band edge potentials are in normalized hydrogen scale.

Tuning halide ion concentrations to optimize the performance of flexible perovskite solar cells under bending curvature. Using simulations and experimental data, the research explores how strains affect key properties like bandgap energy, charge mobility, and thermal conductivity with applications in solar cells for curved surfaces.