Correction: Accelerating materials discovery using integrated deep machine learning approaches
Source abstract
Abstract
Correction for ‘Accelerating materials discovery using integrated deep machine learning approaches’ by Weiyi Xia et al. , J. Mater. Chem. A , 2023, 11 , 25973–25982, https://doi.org/10.1039/d3ta03771a.
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Machine Learning in Materials Science · Computational Drug Discovery Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Ames National Laboratory, U.S. Department of Energy, Ames, IA 50011, USA
Department of Applied Physics, College of Science, Zhejiang University of Technology, Hangzhou, 310023, China
Jiyang College of Zhejiang Agriculture, Forestry University, Zhuji 311800, China
Department of Physics, Yantai University, Yantai 264005, China
Department of Physics and Astronomy, Iowa State University, Ames, IA 50011, USA
Department of Chemistry, Iowa State University, Ames, IA 50011, USA
Funding
U.S. Department of Energy
References
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