Our guest on this episode is Dr. Turab Lookman from Los Alamos National Laboratory. The interview took place at the 2018 MRS Fall meeting.
Relevant papers:
- Gubernatis, J. E.; Lookman, T., Machine Learning in Materials Design and Discovery: Examples from the Present and Suggestions for the Future. Phys. Rev. Materials 2018, 2 (12), 120301. https://doi.org/10.1103/PhysRevMaterials.2.120301.
- Rickman, J. M.; Lookman, T.; Kalinin, S. V., Materials Informatics: From the Atomic-Level to the Continuum. Acta Materialia 2019, 168, 473–510. https://doi.org/10.1016/j.actamat.2019.01.051.
- Lookman, T.; Balachandran, P. V.; Xue, D.; Yuan, R. Active Learning in Materials Science with Emphasis on Adaptive Sampling Using Uncertainties for Targeted Design. npj Computational Materials 2019, 5 (1), 21. https://doi.org/10.1038/s41524-019-0153-8.
- Xue, D.; Balachandran, P. V.; Hogden, J.; Theiler, J.; Xue, D.; Lookman, T., Accelerated Search for Materials with Targeted Properties by Adaptive Design. Nature Communications 2016, 7, 11241. https://doi.org/10.1038/ncomms11241.
