This repository has the predictive models of the bandgap energy for III-V semiconductor compounds. The embeded webiste has a proper GUI for predicting the energy bandgap of the compounds of interest.
More information can be found in the bleow article:
Mohammad Alsalman et. al., “Bandgap Energy Prediction of Senary Zincblende III-V Semiconductor Compounds using Machine Learning,” Materials Science in Semiconductor Processing, vol. 161, p. 107461, 2023.