3 papers
cond-mat.mtrl-sci2019
Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search
Patrick Avery, Xiaoyu Wang, Davide M. Proserpio +5
Good agreement was found between experimental Vickers hardnesses, , of a wide range of materials and those calculated by three macroscopic hardness models that employ t…
cond-mat.mtrl-sci2017
The AFLOW Fleet for Materials Discovery
Cormac Toher, Corey Oses, David Hicks +48
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the d…
cond-mat.mtrl-sci2017
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
Eric Gossett, Cormac Toher, Corey Oses +8
Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a p…