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pro vyhledávání: '"Andy Athawale"'
Autor:
Noushin Omidvar, Shih‐Han Wang, Yang Huang, Hemanth Somarajan Pillai, Andy Athawale, Siwen Wang, Luke E. K. Achenie, Hongliang Xin
Publikováno v:
Electrochemical Science Advances, Vol 4, Iss 6, Pp n/a-n/a (2024)
Abstract As a subfield of artificial intelligence (AI), machine learning (ML) has emerged as a versatile tool in accelerating catalytic materials discovery because of its ability to find complex patterns in high‐dimensional data. While the intricac
Externí odkaz:
https://doaj.org/article/5450aff013d644cb9a304765c438fcfd
Autor:
Hongliang Xin, Siwen Wang, Noushin Omidvar, Luke E. K. Achenie, Shih-Han Wang, Tianyou Mou, Andy Athawale, Hemanth Somarajan Pillai
Understanding the nature of chemical bonding and its variation in strength across physically tunable factors is important for the development of novel catalytic materials. One way to speed up this process is to employ machine learning (ML) algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fe35cda65db7d51ca80b6bc2f33add2
https://hdl.handle.net/10919/108327
https://hdl.handle.net/10919/108327