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Accelerated discovery of perovskite solid solutions through automated materials synthesis and characterization.

Authors :
Omidvar M
Zhang H
Ihalage AA
Saunders TG
Giddens H
Forrester M
Haq S
Hao Y
Source :
Nature communications [Nat Commun] 2024 Aug 02; Vol. 15 (1), pp. 6554. Date of Electronic Publication: 2024 Aug 02.
Publication Year :
2024

Abstract

Accelerating perovskite solid solution discovery and sustainable synthesis is crucial for addressing challenges in wireless communication and biosensors. However, the vast array of chemical compositions and their dependence on factors such as crystal structure, and sintering temperature require time-consuming manual processes. To overcome these constraints, we introduce an automated materials discovery approach encompassing machine learning (ML) assisted material screening, robotic synthesis, and high-throughput characterization. Our proposed platform for rapid sintering and dielectric analysis streamlines the characterization of perovskites and the discovery of disordered materials. The setup has been successfully validated, demonstrating processing materials within minutes, in stark contrast to conventional procedures that can take hours or days. Following setup validation with established samples, we showcase synthesizing single-phase solid solutions within the barium family, such as (Ba <subscript>x</subscript> Sr <subscript>1-x</subscript> )CeO <subscript>3</subscript> , identified through ML-guided chemistry.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
2041-1723
Volume :
15
Issue :
1
Database :
MEDLINE
Journal :
Nature communications
Publication Type :
Academic Journal
Accession number :
39095463
Full Text :
https://doi.org/10.1038/s41467-024-50884-y