MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art
Jianjun Hu, Stanislav Stefanov, Yuqi Song, Sadman Sadeed Omee,, Steph-Yves Louis, Edirisuriya M. D. Siriwardane, Yong Zhao

TL;DR
MaterialsAtlas.org is a user-friendly web platform that consolidates tools for materials discovery, enabling easier screening, property prediction, and exploration of new materials to accelerate research and development.
Contribution
The paper introduces MaterialsAtlas.org, a comprehensive web app platform that integrates various materials informatics tools for discovery and analysis, filling a gap in accessible online resources.
Findings
Provides a suite of tools for materials property prediction
Enables screening of hypothetical materials
Facilitates materials structure and composition checks
Abstract
The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and generative design of materials. However, lack of user-friendly materials informatics web servers has severely constrained the wide adoption of such tools in the daily practice of materials screening, tinkering, and design space exploration by materials scientists. Herein we first survey current materials informatics web apps and then propose and develop MaterialsAtlas.org, a web based materials informatics toolbox for materials discovery, which includes a variety of routinely needed tools for exploratory materials discovery, including materials composition and structure check (e.g. for neutrality, electronegativity balance, dynamic stability, Pauling…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMachine Learning in Materials Science · Electronic and Structural Properties of Oxides · X-ray Diffraction in Crystallography
