A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing

[https://www.nature.com/articles/s41524-023-01003-w](https://www.nature.com/articles/s41524-023-01003-w)

This paper is an end-to-end demonstration of using a language model (MaterialsBERT) trained as part of this work to extract material property data from published literature. The authors obtained \~300,000 material property records from \~130,000 abstracts in 60 hours using their pipeline. The extracted data was analyzed for various applications such as fuel cells, supercapacitors, and polymer solar cells to recover non-trivial insights. The data extracted through this pipeline is made available at [polymerscholar.org](https://polymerscholar.org/) which can be used to …

data data extraction extraction general language language processing languagetechnology natural natural language natural language processing pipeline processing property