A knowledge graph of Cu-based electrocatalysts for electrocatalytic CO2 reduction is constructed based on a linguistically enriched SciBERT-based framework. This framework retrieves multiple types of entities including material, regulation method, product, Faradaic efficiency, etc. from 757 scientific literature, generates representations with abundant domain-specific semantic information, and exhibits the capability to deal with electrocatalysts for CO2 reduction. The obtained graph shows the development history of related catalysts, builds relationships between the factors associated with catalysis, and provides intuitive charts for researchers to gain useful information. 

 Revisiting electrocatalyst design by a knowledge graph of Cu-based catalysts for CO2 reduction. ACS Catalysis 2023, 13 (13), 8525-8534.