The purpose of this study is to build machine learning models to predict the band gap of binary compounds, using its known properties like molecular weight, electronegativity, atomic fraction and the group of the constituent elements in the periodic table. Regression techniques like Linear, Ridge regression and Random Forest were used to build the model. This model can be used by students and researchers in experiments involving unknown band gaps or new compounds.
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