ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data-Reference-Cited by-同舟云学术

ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data

Published:2023-08-25 Issue:35 Volume:127 Page:17545-17555
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Choudhary Kamal¹²³^ORCID,Kelley Mathew L.²⁴

Affiliation:

1. Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States

2. Theiss Research, La Jolla, California 92037, United States

3. DeepMaterials LLC, Maryland, Maryland 20906, United States

4. Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States

Funder

National Institute of Standards and Technology

Microsoft

U.S. Department of Commerce

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.3c03106

Reference57 articles.

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3. Natural Language Processing

4. Phang, J.; Zhao, Y.; Liu, P. J. Investigating Efficiently Extending Transformers for Long Input Summarization. arXiv preprint arXiv:2208.04347, 2022.

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