How to predict band gap of other compounds ?
How will I predict the band gap of any compound other than Si, SiO2, NaCl, Sn and Diamond ? What is the code for doing so? Also if i want to predict the bandgap of the polymer can I do so? and how?
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Benjamin Afflerbach @ on
To predict the bandgaps of other compounds we would need to generate the input features for those new materials. To do so I'd probably recommend jumping outside of the specific notebook used here and use directly one of the materials focused ML packages that include similar featurizers to what we did in this specific example. For example the MAST-ML code referenced here, or the similar matminer package I know has analogous featurizers where we could feed in the compositions to generate the feature sets.
For a few examples that run through google colab you could check out the MAST-ML tutorial sections here:https://mastmldocs.readthedocs.io/en/latest/0_5_tutorials.html
I'd probably warn against using this dataset to predict complex polymers because the dataset only contains binary compounds. Generally we'd expect machine learning models to break down when used significantly outside of the domain of training. In this case the model is only trained on binary compounds so trying to predict a complex polymer would likely give very incorrect predictions.
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