Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery-Reference-Cited by-同舟云学术

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Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery

Published:2024-01-25 Issue:3 Volume:64 Page:677-689
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Kim Hyeonsu¹,Lee Kyunghoon¹,Kim Jun Hyeong¹,Kim Woo Youn¹²^ORCID

Affiliation:

1. Department of Chemistry, Korea Advanced Institute of Science & Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

2. AI Institute, Korea Advanced Institute of Science & Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Funder

Ministry of Trade, Industry and Energy

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c01747

Reference139 articles.

1. Materials discovery and design using machine learning

2. Computational functionality‐driven design of semiconductors for optoelectronic applications

3. Computer-aided discovery of connected metal-organic frameworks

4. Deep learning for development of organic optoelectronic devices: efficient prescreening of hosts and emitters in deep-blue fluorescent OLEDs

5. Computer-aided materials design: bridging the gaps between physics, chemistry and engineering

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