Five Clemson University researchers co-authored a paper in Scientific Reports that was among the publication’s 100 most downloaded materials science papers of the year.
The paper was May 2021’s “Machine learning-based microstructure prediction during laser sintering of alumina.” Scientific Reports notified the team in an email this month that it made the Top 100 list.
The paper demonstrates the significant progress made towards the future of machine-learning-guided advanced manufacturing, researchers said. It has broad impacts on the research fields of machine learning, additive manufacturing, and materials sciences, they said.
Clemson co-authors included Jianan Tang and Hai Xiao from the Holcombe Department of Electrical and Computer Engineering and Xiao Geng, Jianhua Tong and Fei Peng from the Department of Materials Science and Engineering.
Co-authors from other institutions were Dongsheng Li of Connecticut’s Advanced Manufacturing, LLC and Yunfeng Shi of Rensselaer Polytechnic Institute’s Department of Materials Science and Engineering.
The article received 2,008 downloads in 2021, according to Scientific Reports, which published more than 1,020 materials science papers that year.
Read the full paper here.
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