Application of Machine Learning in Materials Science
Four kinds of machine learning methods were summarized,including supervised learning,unsupervised learning,deep learning and reinforcement learning.The specific applications of machine learning in material design and discovery,material characterization and computational materials science were discussed,and its potential in accelerating material development and optimization was demonstrated.The database and data mining technology in materials science was introduced,and the development of database and the application of data mining was summarized.The application of emerging large model technologies in material science was summarized,and it was pointed out that the development of large model technologies led material science into a new era of intelligence.However,the current field still faces many challenges,such as data quality,model interpretability and privacy and security concerns.Through in-depth research and international cooperation,the future material science is expected to achieve more intelligent and efficient material design and discovery through machine learning technology.
万方数据
维普
