Machine Learning based prediction of noncentrosymmetric crystal materials
| العنوان: | Machine Learning based prediction of noncentrosymmetric crystal materials |
|---|---|
| المؤلفون: | Jie Ling, Steph-Yves M. Louis, Joseph Lindsay, Jianjun Hu, Yuqi Song, Alireza Nasiri, Ming Hu, Yong Zhao |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | FOS: Computer and information sciences, Computer Science - Machine Learning, General Computer Science, Computer science, FOS: Physical sciences, General Physics and Astronomy, Inverse, 02 engineering and technology, 010402 general chemistry, Machine learning, computer.software_genre, Communications system, 01 natural sciences, Machine Learning (cs.LG), Laser technology, General Materials Science, Quantum computer, business.industry, General Chemistry, Computational Physics (physics.comp-ph), 021001 nanoscience & nanotechnology, 0104 chemical sciences, Random forest, Computational Mathematics, Mechanics of Materials, Artificial intelligence, 0210 nano-technology, business, computer, Physics - Computational Physics |
| الوصف: | Noncentrosymmetric materials play a critical role in many important applications such as laser technology, communication systems,quantum computing, cybersecurity, and etc. However, the experimental discovery of new noncentrosymmetric materials is extremely difficult. Here we present a machine learning model that could predict whether the composition of a potential crystalline structure would be centrosymmetric or not. By evaluating a diverse set of composition features calculated using matminer featurizer package coupled with different machine learning algorithms, we find that Random Forest Classifiers give the best performance for noncentrosymmetric material prediction, reaching an accuracy of 84.8% when evaluated with 10 fold cross-validation on the dataset with 82,506 samples extracted from Materials Project. A random forest model trained with materials with only 3 elements gives even higher accuracy of 86.9%. We apply our ML model to screen potential noncentrosymmetric materials from 2,000,000 hypothetical materials generated by our inverse design engine and report the top 20 candidate noncentrosymmetric materials with 2 to 4 elements and top 20 borate candidates 13 pages |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3220fbbae08207f5c00ae9025c53c2f1 http://arxiv.org/abs/2002.11295 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....3220fbbae08207f5c00ae9025c53c2f1 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |