87‐4: Leveraging Large Language Models for Molecular Generation in OLED Materials Discovery

Molecular generation is a crucial step in the discovery of OLED materials. Generative AI, particularly LLMs has shown remarkable capabilities in text‐based generative applications. We fine‐tuned an LLM to perform two molecular generation tasks. The generated molecules were verified to have the desired properties and closely align with chemical principles. This work demonstrates an effective language modeling for molecular generation in OLED materials discovery.

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Publication Details

Journal
SID Symposium Digest of Technical Papers
Published
2025-06-01
DOI
https://doi.org/10.1002/sdtp.18396
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

87‐4: Leveraging Large Language Models for Molecular Generation in OLED Materials Discovery

SID Symposium Digest of Technical Papers
Geochemistry and Geologic Mapping
article

87‐4: Leveraging Large Language Models for Molecular Generation in OLED Materials Discovery

article en

Abstract

Molecular generation is a crucial step in the discovery of OLED materials. Generative AI, particularly LLMs has shown remarkable capabilities in text‐based generative applications. We fine‐tuned an LLM to perform two molecular generation tasks. The generated molecules were verified to have the desired properties and closely align with chemical principles. This work demonstrates an effective language modeling for molecular generation in OLED materials discovery.

SID Symposium Digest of Technical PapersVol. 56(1)
TCL (China) (CN), San’an Optoelectronics (China) (CN)
Quality Education
Openalex Percentile: Top 71%
Geochemistry and Geologic Mapping
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87‐4: Leveraging Large Language Models for Molecular Generation in OLED Materials Discovery · SID Symposium Digest of Technical Papers (2025) | TGRS Research Map | TGRS