AURORA - An Automatic Robotic Platform for Materials Discovery

The urgent need for renewable energy solutions requires rapid advancements in materials discovery. In response, we present AURORA, an innovative robotic platform that enhances this process by integrating automated synthesis, characterization, and evaluation into a single unit, thereby improving efficiency and reducing errors. Its modular design allows for adaptable screening of diverse materials, including metal halide perovskites, and their application in solar cell devices. Our study demonstrates the ability of AURORA to autonomously synthesize and evaluate polycrystalline, mixed halide perovskites, including a novel mesoscopic solar cell array with improved data reliability and throughput. AURORA also conducts postsynthesis treatments and dynamic analyses under stress, setting it apart from traditional methods. These features make AURORA a transformative tool for the discovery of novel materials, with potential machine learning integration for optimization. Our results highlight the application of AURORA as a robust and adaptable platform for future developments in automated materials research.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-04-23
DOI
https://doi.org/10.1021/acsami.5c02605
Citations
3
Primary Topic
Perovskite Materials and Applications
Type
article
Field-Weighted Citation Impact
2.19

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article

AURORA - An Automatic Robotic Platform for Materials Discovery

Per H. Svensson, Pavel V. Yushmanov, Lars A. Kloo, Bingyu Lei
3 citations
ACS Applied Materials & Interfaces
Perovskite Materials and Applications
2.19
article

AURORA - An Automatic Robotic Platform for Materials Discovery

Per H. Svensson, Pavel V. Yushmanov, Lars A. Kloo, Bingyu Lei
article en
3 citations

Abstract

The urgent need for renewable energy solutions requires rapid advancements in materials discovery. In response, we present AURORA, an innovative robotic platform that enhances this process by integrating automated synthesis, characterization, and evaluation into a single unit, thereby improving efficiency and reducing errors. Its modular design allows for adaptable screening of diverse materials, including metal halide perovskites, and their application in solar cell devices. Our study demonstrates the ability of AURORA to autonomously synthesize and evaluate polycrystalline, mixed halide perovskites, including a novel mesoscopic solar cell array with improved data reliability and throughput. AURORA also conducts postsynthesis treatments and dynamic analyses under stress, setting it apart from traditional methods. These features make AURORA a transformative tool for the discovery of novel materials, with potential machine learning integration for optimization. Our results highlight the application of AURORA as a robust and adaptable platform for future developments in automated materials research.

ACS Applied Materials & InterfacesVol. 17(18)
AstraZeneca (Brazil) (BR), Pharmaceutical Product Development (India) (IN), Applied Physical Sciences (United States) (US), KTH Royal Institute of Technology (SE)
Carl Tryggers Stiftelse för Vetenskaplig Forskning, Stiftelsen Olle Engkvist Byggmästare, Vetenskapsrådet
Openalex Percentile: Top 13%
Perovskite Materials and Applications
2.19
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AURORA - An Automatic Robotic Platform for Materials Discovery — Per H. Svensson, Pavel V. Yushmanov, et al. · ACS Applied Materials & Interfaces (2025) | TGRS Research Map | TGRS