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Machine Learning for High Entropy Alloys by Krishnakant Tiwari is a document available to read on EtoBox.
This study presents a systematic framework utilizing genetic algorithms to optimize the selection of machine learning models and materials descriptors for predicting phase formation in high entropy alloys (HEAs). The proposed method achieved classification accuracies of up to 91.3% for identifying different HEA phases and demonstrated the effectiveness of active learning in improving model performance. This approach can be generalized for various materials problems, enhancing the efficiency of materials dis
- Author
- Krishnakant Tiwari
- Language
- EN