Size‐Distribution Control of Exfoliated Nanosheets Assisted by Machine Learning: Small‐Data‐Driven Materials Science Using Sparse Modeling (Adv. Theory Simul. 10/2021). Issue 10 (4th October 2021)

• Record Type: Journal Article
• Authors: Haraguchi, Yuri; Igarashi, Yasuhiko; Imai, Hiroaki; Oaki, Yuya
• Is Part Of: Advanced theory and simulations. Volume 4:Issue 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-04
• Subjects: Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202170025
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract : Size‐Distribution Control of Exfoliated Nanosheets The downsizing exfoliation process to obtain 2D materials is not easily controlled only by trial and error. In article number 2100158, Yuri Haraguchi, Yuya Oaki, and co‐workers demonstrate that the monodispersed and polydispersed nanosheets are selectively synthesized in a limited number of experiments by machine learning combined with their chemical perspectives on small data.