Pith. sign in

REVIEW 1 cited by

Data-Driven Design-Test-Make-Analyze Paradigm for Inorganic Crystals: Ultrafast Synthesis of Ternary Oxides

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2506.18542 v1 pith:MBSWVIZC submitted 2025-06-23 cond-mat.mtrl-sci

Data-Driven Design-Test-Make-Analyze Paradigm for Inorganic Crystals: Ultrafast Synthesis of Ternary Oxides

classification cond-mat.mtrl-sci
keywords inorganicsynthesisanalysisdata-drivendiscoveryexplorationframeworkmaterials
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original 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 through micro-electron diffraction (microED) analysis. Our framework effectively integrates multi-aspect physics-based filtration with in-depth characterization, demonstrating the feasibility of designing, testing, synthesizing, and analyzing (DTMA) novel material candidates, marking a significant advancement towards inorganic materials by design.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Virp: neural network-accelerated prediction of physical properties in site-disordered materials

    cond-mat.mtrl-sci 2026-05 unverdicted novelty 4.0

    A pipeline samples site-disordered material configurations with 400 virtual cells when the supercell is large enough, improving computational feasibility over quasirandom or cluster expansion methods.