Machine learning-based prediction of phases in high-entropy alloys: A data article.

Autor: Machaka R; Advanced Materials Manufacturing, Manufacturing Cluster, Council for Scientific and Industrial Research, P.O. Box 395, Pretoria, 0001, South Africa.; School of Mining, Metallurgy and Chemical Engineering, University of Johannesburg, Johannesburg, South Africa., Motsi GT; Advanced Materials Manufacturing, Manufacturing Cluster, Council for Scientific and Industrial Research, P.O. Box 395, Pretoria, 0001, South Africa., Raganya LM; Advanced Materials Manufacturing, Manufacturing Cluster, Council for Scientific and Industrial Research, P.O. Box 395, Pretoria, 0001, South Africa.; School of Mining, Metallurgy and Chemical Engineering, University of Johannesburg, Johannesburg, South Africa., Radingoana PM; Advanced Materials Manufacturing, Manufacturing Cluster, Council for Scientific and Industrial Research, P.O. Box 395, Pretoria, 0001, South Africa., Chikosha S; Advanced Materials Manufacturing, Manufacturing Cluster, Council for Scientific and Industrial Research, P.O. Box 395, Pretoria, 0001, South Africa.

Publikováno v: Data in brief [Data Brief] 2021 Sep 16; Vol. 38, pp. 107346. Date of Electronic Publication: 2021 Sep 16 (Print Publication: 2021).