Extrapolation performance improvement by quantum chemical calculations for machine-learning-based predictions of flow-synthesized binary copolymers-Reference-Cited by-同舟云学术

Extrapolation performance improvement by quantum chemical calculations for machine-learning-based predictions of flow-synthesized binary copolymers

Published:2023 Issue:3 Volume:2 Page:809-818
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Takasuka Shogo¹^ORCID,Oikawa Shunto¹,Yoshimura Takayoshi²,Ito Sho¹,Harashima Yosuke¹^ORCID,Takayama Tomoaki¹^ORCID,Asano Shigehito³,Kurosawa Akira³,Sugawara Tetsunori³,Hatanaka Miho²^ORCID,Miyao Tomoyuki¹^ORCID,Matsubara Takamitsu¹,Ohnishi Yu-ya³^ORCID,Ajiro Hiroharu¹^ORCID,Fujii Mikiya¹

Affiliation:

1. Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan

2. Keio University, 4-1-1 Hiyoshi, Kohoku-ku, Yokohama-shi, Kanagawa 223-8521, Japan

3. JSR Corporation, Shiodome Sumitomo Bldg., 1-9-2, Higashi-Shimbashi, Minato-ku, Tokyo 105-8640, Japan

Abstract

The study utilized machine learning to predict highly accurate polymer properties, mainly when quantum chemical calculation values were included as variables, thus suggesting a promising tool for accelerating polymer development with new monomers.

Funder

New Energy and Industrial Technology Development Organization

Japan Society for the Promotion of Science

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/DD/D2DD00144F

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