Construction and Application of Materials Knowledge Graph Based on Author Disambiguation: Revisiting the Evolution of LiFePO4

Due to the recent innovations in computer technology, the emerging field of materials informatics has now become a catalyst for a revolution of the research paradigm in materials science. Knowledge graphs, which provide support for knowledge management, are able to collectively capture the scientific knowledge from the vast collection of research articles and accomplish the automatic recognition of the relationships between entities. In this work, a materials knowledge graph, named MatKG, is constructed, which establishes a unique correspondence between subjects and objects in the materials science area. An emphasis is placed on the disambiguation of authors, addressed by a deduplication model based on machine learning and matching dependencies algorithms. Specifically, MatKG is applied to perform tracking on research trends in the study of LiFePO4 and to automatically chronicle the milestones achieved so far. It is believed that MatKG can serve as a versatile research platform for amalgamating and refining the scientific knowledge of materials in a variety of subfields and intersectional domains.

Automated summary

The article introduces a materials knowledge graph named MatKG, which addresses issues in materials science research through the construction of the knowledge graph and author disambiguation. It demonstrates the application of MatKG in tracking research trends in LiFePO4 and automatically documenting milestones achieved.