{"id":"doi:10.1103/physrevb.89.094104","kind":"article","title":"Combinatorial screening for new materials in unconstrained composition space with machine learning","authors":["Bryce Meredig","Ankit Agrawal","Scott J. Kirklin","James E. Saal","Jeff W. Doak","Alexander E. Thompson","K. Zhang","Alok Choudhary","Chris M. Wolverton"],"author_count":9,"year":2014,"published":"2014-03-14","venue":"Physical Review B","cited_by":735,"doi":"10.1103/physrevb.89.094104","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1103/physrevb.89.094104","archive_url":"https://space-kitty.com/papers/doi:10.1103/physrevb.89.094104","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2313966941","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Machine Learning in Materials Science"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-for-science","name":"AI for Science","domain_slug":"ai"}],"cited_in_dossiers":[]}