857 citations · 2.8k across the 19 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…
Automated Structure Discovery in Atomic Force Microscopy
Benjamin Alldritt, Prokop Hapala, Niko Oinonena +7
Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces.…
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…