The high-throughput highway to computational materials design
Source abstract
Abstract
High-throughput computational materials design is an emerging area of materials science. By combining advanced thermodynamic and electronic-structure methods with intelligent data mining and database construction, and exploiting the power of current supercomputer architectures, scientists generate, manage and analyse enormous data repositories for the discovery of novel materials. In this Review we provide a current snapshot of this rapidly evolving field, and highlight the challenges and opportunities that lie ahead.
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Research context
OpenAlex topics: Machine Learning in Materials Science · Electronic and Structural Properties of Oxides · 2D Materials and Applications
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References (100+)
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