Machine Learning in Materials Science

Machine Learning in Materials Science is a research topic within Materials Chemistry. Science Explorer counts 30k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of materials informatics, machine learning, and high-throughput computational techniques to accelerate materials innovation. It encompasses topics such as property predictions, crystal structures, molecular dynamics, and data mining in the context of materials science and engineering.

• Materials Informatics
• Machine Learning
• High-Throughput
• Computational Chemistry
• Materials Discovery
• Quantum Mechanics
• Crystal Structures
• Molecular Dynamics
• Property Predictions
• Data Mining