Data-Driven Design-Test-Make-Analyze Paradigm for Inorganic Crystals: Ultrafast Synthesis of Ternary Oxides
Haiwen Dai, Matthew J. McDermott, Andy Paul Chen, Jose Recatala-Gomez, Wei Nong, Ruiming Zhu, Maung Thway, Samuel Morris, Christian Sch\"urmann, Shreyas Dinesh Pethe, Chenguang Zhang, Wuan Geok Saw, Bich Ngoc Tran, Pritish Mishra, Fengxia Wei, Albertus Denny Handoko

TL;DR
This paper introduces a comprehensive data-driven framework for the rapid discovery and synthesis of inorganic ternary oxide materials, successfully synthesizing two previously unsynthesized compounds and validating their structures.
Contribution
The work presents an end-to-end DTMA framework integrating computational predictions with experimental synthesis for inorganic crystals, enabling faster discovery of novel materials.
Findings
Successfully synthesized ZnVO3 with a disordered spinel structure.
Synthesized YMoO3-x close to 1:1:3 composition, identified as Y4Mo4O11.
Validated structures using DFT and microED techniques.
Abstract
Data-driven methodologies hold the promise of revolutionizing inorganic materials discovery, but they often face challenges due to discrepancies between theoretical predictions and experimental validation. In this work, we present an end-to-end discovery framework that leverages synthesizability, oxidation state probability, and reaction pathway calculations to guide the exploration of transition metal oxide spaces. Two previously unsynthesized target compositions, ZnVO3 and YMoO3, passed preliminary computational evaluation and were considered for ultrafast synthesis. Comprehensive structural and compositional analysis confirmed the successful synthesis ZnVO3 in a partially disordered spinel structure, validated via Density Functional Theory (DFT). Exploration of YMoO3 led to YMoO3-x with elemental composition close to 1:1:3; the structure was subsequently identified to be Y4Mo4O11…
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.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
