Overcoming language barrier for scientific studies via unsupervised literature learning: case study on solar cell materials prediction
Data‐driven materials and chemical studies have been predominantly confined to English‐
language databases, posing challenges for researchers in non‐English‐speaking regions to …
language databases, posing challenges for researchers in non‐English‐speaking regions to …
Best practices in catalysis: A perspective
A Bhan, WN Delgass - Journal of Catalysis, 2022 - Elsevier
Catalysis, from its roots in petrochemical refining and conversion, has emerged as a
transdisciplinary field that now encompasses synthesis of materials and molecules that …
transdisciplinary field that now encompasses synthesis of materials and molecules that …
Tackling Structured Knowledge Extraction from Polymer Nanocomposite Literature as an NER/RE Task with seq2seq
B Hu, A Lin, LC Brinson - Integrating Materials and Manufacturing …, 2024 - Springer
There is an urgent need for ready access to published data for advances in materials
design, and natural language processing (NLP) techniques offer a promising solution for …
design, and natural language processing (NLP) techniques offer a promising solution for …
Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures
A Su, C Zhang, YB She, YF Yang - Catalysts, 2022 - mdpi.com
Metalloporphyrins have been studied as biomimetic catalysts for more than 120 years and
have accumulated a large amount of data, which provides a solid foundation for deep …
have accumulated a large amount of data, which provides a solid foundation for deep …
[PDF][PDF] Tackling structured knowledge extraction from polymer
B Hu, A Lin, LC Brinson - researchgate.net
There is an urgent need for ready access to published data for advances in materials
design, and natural language processing (NLP) techniques offer a promising solution for …
design, and natural language processing (NLP) techniques offer a promising solution for …