band-gap

Accelerated Design of Layered Materials with Bayesian Optimization

Automatic Prediction of Band Gaps of Inorganic Materials using Machine Learning

Automated direct band gap extractor from many measured reflectance samples at a time using recursive segmentation and regression fitting of Tauc plots.

R package to calculate optical band gap of semiconductors from UV-Vis spectra using the Tauc method

A composition-based ML framework for predicting electronic band gaps of inorganic materials. XGBoost & Random Forest on 15,537 Materials Project compounds using Magpie descriptors.

Band Gap ML Project from my ML for Physicists class in Fall 2020.

☀️ Computational SI for the publication 'Photoreactive Tetraperoxoniobate.' doi:

Small database of band gaps and band energies for semiconductors commonly encountered in the PEC field

INFO5000 course project: predicting band gaps of 2D materials with ALIGNN graph neural networks and baseline machine-learning models.

Electronic structure analysis of bulk silicon using DFT — band structure, DOS, PDOS, and charge density (Quantum ESPRESSO, PBE)

Wave propagation and band gap analysis of longitudinally periodic rotors, in Python.

This repository contains notebooks that reproduce figures from my published manuscript

Machine learning model to predict band gap of iron-oxide materials using Materials Project database and matminer chemistry features. Built with Python, scikit-learn and Random Forest achieving R² of 0.665.

Physics-guided self-attention neural network for perovskite band-gap prediction with non-negative, physically valid outputs.

Data-variance capture ability of Composition-descriptors while predicting the band gap (primarily semiconductor family choosen)

A Neuro-symbolic pipeline (LLM +Knowledge graph (KG) integration) for Bandgap of Semiconductor materials