Data-Driven High-Throughput Screening and Experimental Realization of Ag2B(IV)B′(VI)O6 under Negative Chemical-Pressure

Harsh synthetic conditions and high cost seriously hinder the discoveries of metastable materials under extreme conditions. Extending the big-data-driven high-throughput calculation (HTC) to depict the chemically negative pressure (NP) zone enables the creation of efficient and accurate prediction models over the full pressure range. This approach significantly expedites the exploration and discovery of novel multifunctional metastable materials. Here, double perovskites Ag2B(IV)B′(VI)O6 were adopted to illustrate the comprehensive process of big-data-mining, HTC, and experimental realization under chemically NP. High-throughput screening of 32 Ag2BB′O6 compounds, encompassing 9 possible crystal structures and 23 derived magnetic structures, resulting in 1024 potential candidates. Ag2MnTeO6 (AMTO) and Ag2TiTeO6 (ATTO) were selected for the experimental validation. We captured a new polymorph of AMTO (R-3, 3R) at ambient pressure through ion-exchange reaction, a phase theoretically predicted to be stable under NP about −6.6 GPa. Moreover, as predicted by density functional theory calculations, the P-31c (2H) AMTO is an antiferromagnetic semiconductor with magnetic transition at 3 K and direct band gap ∼0.97 eV. This work is expected to guide the exploration of hidden metastable phase by providing a methodological framework and novel conceptual approach for future research.