Materials Databases: Foundations of Modern Digital Materials
North China Electric Power University · Energy Storage Systems (United States) · +5 more institutions
Abstract
Materials databases are increasingly the backbone of data-driven discovery for energy materials. In this Perspective, we map the ecosystem of computational and experimental databases, and argue that database architecture, which covers ingestion, curation, metadata, provenance, and access interfaces, strongly influences the performance and trustworthiness of modern AI models. We classify computational repositories into bulk-property and surface/interface resources, and summarize representative experimental databases spanning crystal structures, catalysis, energy storage, and characterization. Beyond single-modality repositories, we highlight integrated platforms that connect computed descriptors with…
Citation impact
- FWCI
- 23.69
- Percentile
- 99%
- References
- 102
Authors
11- YZYutian Zhuang
North China Electric Power University, Energy Storage Systems (United States), Institute of Power Engineering
- XYXiaojin Yang
North China Electric Power University, Energy Storage Systems (United States), Institute of Power Engineering
- CZChenyi Zhang
North China Electric Power University, Energy Storage Systems (United States), Institute of Power Engineering
- XJXue Jia
Tohoku University, Institute for Materials Research, Tohoku University
- DZDi Zhang
Tohoku University, Institute for Materials Research, Tohoku University
Topics & keywords
- Trustworthiness
- Key (lock)
- Graph
- Energy (signal processing)
- Artificial neural network
- Deep learning