Predictions of High-Order Electric Properties of Molecules: Can We Benefit from Machine Learning?-Reference-Cited by-同舟云学术

Predictions of High-Order Electric Properties of Molecules: Can We Benefit from Machine Learning?

Published:2020-03-09 Issue:10 Volume:5 Page:5318-5325
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Tuan-Anh Tran¹,Zaleśny Robert²^ORCID

Affiliation:

1. Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme Viet Nam, 764 Vo Van Kiet, Quan 5, Ho Chi Minh City, Vietnam

2. Department of Physical and Quantum Chemistry, Faculty of Chemistry, Wrocław University of Science and Technology, Wyb. Wyspiańskiego 27, PL-50370 Wrocław, Poland

Funder

Ministerstwo Nauki i Szkolnictwa Wyzszego

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acsomega.9b04339

Reference74 articles.

1. Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17

2. Theory-Inspired Development of Organic Electro-optic Materials

3. Design and Characterization of Molecular Nonlinear Optical Switches

4. Strategies for Designing Diarylethenes as Efficient Nonlinear Optical Switches

5. Designing Efficient Azobenzene and Azothiophene Nonlinear Optical Photochromes

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