857 citations · 1.8k across the 8 of their papers we have counts for
3 papers · 1 filter
Data-driven materials science: status, challenges and perspectives
Lauri Himanen, Amber Geurts, Adam S. Foster +1
Data-driven science is heralded as a new paradigm in materials science. In this field, data is the new resource, and knowledge is extracted from materials data sets that are too bi…
DScribe: Library of Descriptors for Machine Learning in Materials Science
Lauri Himanen, Marc O. J. Jäger, Eiaki V. Morooka +5
DScribe is a software package for machine learning that provides popular feature transformations ("descriptors") for atomistic materials simulations. DScribe accelerates the applic…
Database-driven high-throughput study for hybrid perovskite coating materials
Azimatu Seidu, Lauri Himanen, Jingrui Li +1
We developed a high-throughput screening scheme to acquire candidate coating materials for hybrid perovskites. From more than 1.8 million entries of an inorganic compound database,…