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Ong’s current research aims to bring about a revolutionary leap in the conduct of materials science through a combination of high-throughput first principles calculations and machine learning. Specifically, his Materials Virtual Lab targets three key bottlenecks in materials science: (1) predicting the properties of materials accurately and efficiently; (2) enabling large-scale, long-time simulations of complex materials and interfaces; and (3) achieving superhuman performance in interpretation of materials characterization. Through the application of AI techniques on large materials datasets, his research has led to the discoveries of novel materials for rechargeable alkali-ion batteries and LED phosphors. Ong is also a firm advocate of open data and software for democratized and reproducible materials science.
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npj Computational Materialsno. 1 (2024): 1-11
Jianbin Zhou,Manas Likhit Holekevi Chandrappa,Sha Tan,Shen Wang,Chaoshan Wu, Howie Nguyen,Canhui Wang,Haodong Liu,Sicen Yu, Quin R. S. Miller,Gayea Hyun,John Holoubek,
Natureno. 8003 (2024): 301-305
Matthew L. Evans, Johan Bergsma,Andrius Merkys,Casper W. Andersen, Oskar B. Andersson,Daniel Beltrán,Evgeny Blokhin, Tara M. Boland,Rubén Castañeda Balderas,Kamal Choudhary,Alberto Díaz Díaz, Rodrigo Domínguez García,
arxiv(2024)
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Ji Qi,Z. H. Aitken,Qingxiang Pei, Anne Marie Z. Tan,Yunxing Zuo, M. H. Jhon, S. S. Quek,T. Wen,Zhaoxuan Wu,Shyue Ping Ong
arXiv (Cornell University) (2023)
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ADVANCED OPTICAL MATERIALSno. 8 (2023)
Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canadano. Supplement_1 (2023): 633-635
Nature communicationsno. 1 (2023): 1940-1940
Journal of Materials Chemistry Ano. 5 (2023): 2273-2290
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