Enhancing chemical synthesis research with NLP: Word embeddings for chemical reagent identification—A case study on nano-FeCu

Enhancing chemical synthesis research with NLP: Word embeddings for chemical reagent identification—A case study on nano-FeCu

Summary: Nanoparticle synthesis is complex, influenced by multiple variables including reagent selection. This study introduces a specialized corpus focused on “Fe, Cu, synthesis” to train a domain-specific word embedding model using natural language processing (NLP) in an unsupervised environment....

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Bibliographic Details
Main Authors: Dingding Cao, Mieow Kee Chan
Format: Article
Language:English
Published: Elsevier 2024-10-01
Series:iScience
Subjects:
Artificial intelligence
Natural language processing
Engineering
Materials science
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004224020054

Internet

http://www.sciencedirect.com/science/article/pii/S2589004224020054

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