Molecular generation targeting desired electronic properties via deep generative models-Reference-Cited by-同舟云学术

Molecular generation targeting desired electronic properties via deep generative models

Published:2020 Issue:12 Volume:12 Page:6744-6758
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Yuan Qi¹²³⁴⁵^ORCID,Santana-Bonilla Alejandro¹²³⁴⁵,Zwijnenburg Martijn A.¹⁶⁷⁸^ORCID,Jelfs Kim E.¹²³⁴⁵^ORCID

Affiliation:

1. Department of Chemistry

2. Molecular Sciences Research Hub

3. White City Campus

4. Imperial College London

5. London

6. University College London

7. London WC1H 0AJ

8. UK

Abstract

A generative recurrent neural network (RNN) model was developed to target and explore the chemical space of electronic donor–acceptor oligomers effectively.

Funder

H2020 European Research Council

Engineering and Physical Sciences Research Council

Royal Society

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2020/NR/C9NR10687A

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1. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

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5. Design Principles and Top Non-Fullerene Acceptor Candidates for Organic Photovoltaics

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