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  • Comment: New sources added are either WP:ROUTINE coverage (profiles), connected to the source via interview or otherwise (fails WP:IS) or just mention Ong (i.e talking about his research or his team). Don't believe the two sources about research meets 1st point of WP:NACADEMIC either. EmeraldRange ( talk/ contribs) 14:52, 4 November 2023 (UTC)
  • Comment: Exclusively reliant on profiles and self-published materials, which are insufficient in demonstrating notability. Make sure to include multiple significant coverage from reliable and independent sources to prove that the subject passes WP:NACADEMIC or WP:NBIO. For the claims that are marked with citation needed, add supporting citations, otherwise they need to be removed. Tutwakhamoe ( talk) 02:58, 7 August 2023 (UTC)
Shyue Ping Ong
翁学平
Professor Ong from UCSD story on use of supercomputers for aided discovery of new LED materials.
Professor Ong from UCSD story on use of supercomputers for aided discovery of new LED materials. [1]
Alma mater MIT
Scientific career
Fields Materials Science, Cheminformatics, Materials Informatics, Machine Learning
Institutions University of California, San Diego
Academic advisors Gerbrand Ceder
Website https://materialsvirtuallab.org/

Shyue Ping Ong is a professor of nanoengineering at the University of California, San Diego and leads the materials virtual lab. [1] [2] [3] He is also the co-founder and co-president of MaterialsQM Consulting and associate editor of ACS Materials letters journal. [4] [5]

Education

Ong received his PhD in Materials Science and Engineering from MIT in 2011 under the guidance of professor Gerbrand Ceder. [6] [7] [8] He also has holds M. Eng. degree in Electrical and Information Science Engineering from University of Cambridge. [ citation needed] He is part of the original team that developed the tooling for the Materials Project which supports the Materials Genome initiative. [9] [10]

Research

Ong's research focuses on Materials informatics and more broadly the intersection between data science, ML/ AI, and the physical sciences. He has used this approach to develop and characterize materials for applications in energy. He helps lead the Materials Project, focused on rapid discovery of advanced materials for sustainable, clean energy to better humanity. [11] [9] [10] As part of the Materials Project he is the lead developer and maintainer of the pymatgen, an open source python platform for materials analysis. [12]

Ong's previous work has indicated that Na-ion batteries are possible competitive alternatives to Li-ion batteries, as they demonstrate lower voltages, structural dependencies, and possibly lower migration barriers for Na+ ions in layered structures. [13] He has also worked on improving Li-ion battery materials.

Ong is the co-developer of the MEGNet and universal M3GNet graph neural network interatomic potentials. [14] [15] [16] Professor Ong and his co-author argue M3GNet enables efficient material discovery across diverse chemistries by leveraging machine learning for structural relaxation, dynamic simulations, and property prediction. [16] More recently, MEGNet and M3GNet have been superseded by a more general and performant framework, MatGL to use graph neural network potentials. [17]

References

  1. ^ "Shyue Ping Ong | Jacobs School of Engineering". jacobsschool.ucsd.edu. Retrieved 2023-03-27.
  2. ^ "People". Materials Virtual Lab. 2016-06-08. Retrieved 2023-03-27.
  3. ^ "Materials Virtual Lab". GitHub. Retrieved 2023-03-27.
  4. ^ "MaterialsQM Consulting". materialsqm.com. Retrieved 2023-03-27.
  5. ^ "ACS Materials Letters editors and editorial board". American Chemical Society Publications. Retrieved 2023-03-26.
  6. ^ Ong, Shyue Ping (2011). First Principles Design and Investigation of Lithium-Ion Battery Cathodes and Electrolytes. Cambridge, MA: MIT.
  7. ^ "Theses" (PDF). Ceder Group, UC Berkeley. Retrieved 2023-03-26.
  8. ^ "Chemistry Tree - Gerbrand Ceder". academictree.org. Retrieved 2023-08-15.
  9. ^ a b "Materials Project - People". Materials Project. Retrieved 2023-03-27.
  10. ^ a b juliechao (2016-11-18). "A New Understanding of Metastability Clears Path for Next-Generation Materials - Berkeley Lab". Berkeley Lab News Center. Retrieved 2023-08-15.
  11. ^ Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy; Chen, Wei; Richards, William Davidson; Dacek, Stephen; Cholia, Shreyas; Gunter, Dan; Skinner, David; Ceder, Gerbrand; Persson, Kristin A. (2013-07-01). "Commentary: The Materials Project: A materials genome approach to accelerating materials innovation". APL Materials. 1 (1): 011002. Bibcode: 2013APLM....1a1002J. doi: 10.1063/1.4812323. S2CID  94929253.
  12. ^ Ong, Shyue Ping; Richards, William Davidson; Jain, Anubhav; Hautier, Geoffroy; Kocher, Michael; Cholia, Shreyas; Gunter, Dan; Chevrier, Vincent L.; Persson, Kristin A.; Ceder, Gerbrand (2013-02-01). "Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis". Computational Materials Science. 68: 314–319. doi: 10.1016/j.commatsci.2012.10.028. ISSN  0927-0256. OSTI  1511345.
  13. ^ Ong, Shyue Ping; Chevrier, Vincent L.; Hautier, Geoffroy; Jain, Anubhav; Moore, Charles; Kim, Sangtae; Ma, Xiaohua; Ceder, Gerbrand (2011-08-26). "Voltage, stability and diffusion barrier differences between sodium-ion and lithium-ion intercalation materials". Energy & Environmental Science. 4 (9): 3680–3688. doi: 10.1039/C1EE01782A. hdl: 1721.1/73998. ISSN  1754-5706. S2CID  18299089.
  14. ^ Chen, Chi; Ong, Shyue Ping (2022-11-01). "A universal graph deep learning interatomic potential for the periodic table". Nature Computational Science. 2 (11): 718–728. arXiv: 2202.02450. doi: 10.1038/s43588-022-00349-3. ISSN  2662-8457. PMID  38177366. S2CID  246634877.
  15. ^ "AI invents millions of materials that don't yet exist". Yahoo News. 2022-11-28. Retrieved 2023-08-15.
  16. ^ a b Singh, Kuldeep (2022-11-28). "New Breakthrough: 'An AlphaFold For Materials' Developed". Revyuh. Retrieved 2023-08-15.
  17. ^ "AI invents millions of materials that don't yet exist". Yahoo News. 2022-11-28. Retrieved 2023-08-15.
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