Theory-Guided Machine Learning in Materials Science Materials scientists are increasingly adopting the use of machine learning tools to discover hidden trends in data and make predictions. Applying concepts from data science without foreknowledge of their limitations and the unique qualit... W Nicholas,...
machine learningmodelingvalidationTraditional methods of discovering new materials,such as the empirical trial and error method and the density functional theory(DFT)-based method,are unable to keep pace with the development of materials science today due to their long development cycles,low efficiency,...
Machine learning is a powerful tool in materials research. Our collection of articles looks in depth at applications of machine learning in various areas of materials science.Editorial Rise of the machines Machine learning holds great potential to accelerate materials research. Many domains in ...
Machine learning has been widely used in various fields of materials science. This review focused on the basic operational procedures of machine learning in analyzing the properties of materials; it summarized the applications of machine learning algorithms in materials science in recent years, which ...
As the fields of artificial intelligence and machine learning are exploding, their universal nature is becoming more apparent. Machine learning is being leveraged in a huge variety of sub-fields, and…
Machine learning is a branch of artificial intelligence that uses data to automatically build inferences and models designed to generalise and make predictions. In this thesis, the use of machine learning in materials science is explored, for two different problems: the optimisation of gallium nitride...
In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywher...
Book Description Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts ...
- 《Applied Surface Science A Journal Devoted to the Properties of Interfaces in Relation to the Synthesis & Behaviour of Materials》 被引量: 0发表: 2024年 Some Approaches for Theoretical Search of Novel Phosphor Materials Based on First-Principles Calculations and Machine Learning For theoretical ...
This review discussed the dilemma of small data faced by materials machine learning. First, we analyzed the limitations brought by small data. Then, the workflow of materials machine learning has been introduced. Next, the methods of dealing with small d