Publication Type : Conference Proceedings
Publisher : AIP Publishing
Source : AIP Conference Proceedings
Url : https://doi.org/10.1063/5.0224899
Campus : Bengaluru
School : School of Engineering
Year : 2024
Abstract : The combined application of informatics and material science is explored. The data containing 83989 compositions are extracted from Materials database and after cleansing the extracted data, the linkage between composition and the bulk modulus property are predicted with the technique of Composition Based Feature Vector (CBFV) by using suitable Classical Machine Learning Algorithms and further with a Deep neural network.
Cite this Research Publication : M. Dharani, M. Praveen, Predicting composition and bulk modulus property linkage using materials informatics, AIP Conference Proceedings, AIP Publishing, 2024, https://doi.org/10.1063/5.0224899