Yibin Xu, Yen-Ju Wu, Huiping Li, Lei Fang, Shigenobu Hayashi, Ayako Oishi, Natsuko Shimizu, Riccarda Caputo, Pierre Villars
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引用次数: 0
Abstract
Data-driven material research for property prediction and material design using machine learning methods requires a large quantity, wide variety, and high-quality materials data. For battery materials, which are commonly polycrystalline, ceramics, and composites, multiscale data on substances, materials, and batteries are required. In this work, we develop a data network composed of three interlinked databases, from which we can obtain comprehensive data on substances such as crystal structures and electronic structures, data on materials such as chemical composition, structure, and properties, and data on batteries such as battery composition, operation conditions, and capacity. The data are extracted from research papers on solid electrolytes and cathode materials, selected by screening more than 330 thousand papers using natural language processing tools. Data extraction and curation are carried out by editors specialized in material science and trained in data standardization.
期刊介绍:
Science and Technology of Advanced Materials (STAM) is a leading open access, international journal for outstanding research articles across all aspects of materials science. Our audience is the international community across the disciplines of materials science, physics, chemistry, biology as well as engineering.
The journal covers a broad spectrum of topics including functional and structural materials, synthesis and processing, theoretical analyses, characterization and properties of materials. Emphasis is placed on the interdisciplinary nature of materials science and issues at the forefront of the field, such as energy and environmental issues, as well as medical and bioengineering applications.
Of particular interest are research papers on the following topics:
Materials informatics and materials genomics
Materials for 3D printing and additive manufacturing
Nanostructured/nanoscale materials and nanodevices
Bio-inspired, biomedical, and biological materials; nanomedicine, and novel technologies for clinical and medical applications
Materials for energy and environment, next-generation photovoltaics, and green technologies
Advanced structural materials, materials for extreme conditions.