Materials Design and Informatics

2 million formation energies predicted using a machine learning model.
2 million formation energies predicted using a machine learning model F.A. Faber, A. Lindmaa, O.A.v. Lilienfeld, R. Armiento, Physical Review Letters 117(13), 135502 (2016). Reproduced under the Creative Commons Attribution 3.0 License.

The research in the unit of Materials Design and Informatics is aimed at increased understanding of the theory of materials and has applications in the development of new materials, for example, for energy harvesting, conversion, and storage.

Our research spans areas of mathematical physics, quantum mechanics, numerical methods, programming, and the use of informatics and AI methods in materials research.

Ongoing research projects include the development of theoretical methods for the computational prediction of materials properties, execution of high-throughout calculations on supercomputers aimed at design of new materials, development of software for automated computation, analysis, and data curation in large scale databases, and the use of informatics and machine learning/AI-based methods on materials data.

 

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