Geometrical design of a crystal growth system guided by a machine learning algorithm-Reference-Cited by-同舟云学术

Geometrical design of a crystal growth system guided by a machine learning algorithm

Published:2021 Issue:14 Volume:23 Page:2695-2702
ISSN:1466-8033
Container-title:CrystEngComm
language:en
Short-container-title:CrystEngComm

Author:

Yu Wancheng¹²³⁴^ORCID,Zhu Can¹²³⁴,Tsunooka Yosuke⁵²³⁴^ORCID,Huang Wei⁵²³⁴,Dang Yifan⁵²³⁴^ORCID,Kutsukake Kentaro¹²³⁴⁶,Harada Shunta¹²³⁴⁵,Tagawa Miho¹²³⁴⁵,Ujihara Toru¹²³⁴⁵

Affiliation:

1. Institute of Materials and Systems for Sustainability (IMaSS)

2. Nagoya University

3. Nagoya 464-8603

4. Japan

5. Graduate School of Engineering

6. Center for Advanced Intelligence Project

Abstract

This study proposes a new high-speed method for designing crystal growth systems. It is capable of optimizing large numbers of parameters simultaneously which is difficult for traditional experimental and computational techniques.

Funder

Japan Society for the Promotion of Science

New Energy and Industrial Technology Development Organization

RIKEN

Publisher

Royal Society of Chemistry (RSC)

Subject

Condensed Matter Physics,General Materials Science,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/CE/D1CE00106J

Reference41 articles.

1. H. J. Scheel , in Crystal Growth Technology , ed. H. J. Scheel and T. Fukuda , John Wiley & Sons, Ltd. , 2003 , pp. 3–14