DataVXACS Energy LettersPaper
journal article·2024-04-12Open access

Artificial Intelligence-Based, Wavelet-Aided Prediction of Long-Term Outdoor Performance of Perovskite Solar Cells

Ioannis Kouroudis, Kenedy Tabah Tanko, Masoud Karimipour, Aziz Ben Ali, D. Kishore Kumar, Vediappan Sudhakar, Ritesh Kant Gupta, Iris Visoly-Fisher, Monica Lira-Cantu, Alessio Gagliardi

ACS Energy Letters· Volume 9· Issue 4
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Source abstract

Abstract

The commercial development of perovskite solar cells (PSCs) has been significantly delayed by the constraint of performing time-consuming degradation studies under real outdoor conditions. These are necessary steps to determine the device lifetime, an area where PSCs traditionally suffer. In this work, we demonstrate that the outdoor degradation behavior of PSCs can be predicted by employing accelerated indoor stability analyses. The prediction was possible using a swift and accurate pipeline of machine learning algorithms and mathematical decompositions. By training the algorithms with different indoor stability data sets, we can determine the most relevant stress factors, thereby shedding light on the outdoor degradation pathways. Our methodology is not specific to PSCs and can be extended to other PV technologies where degradation and its mechanisms are crucial elements of their widespread adoption.
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Research context

Electronic materials

OpenAlex topics: Perovskite Materials and Applications · Machine Learning and ELM · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering, School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty Strasse 1, 85748 Garching bei Munich,Germany

Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and The Barcelona Institute of Science and Technology, 08193 Bellaterra, Barcelona, Spain

Ben-Gurion Solar Energy Center, Swiss Inst. for Dryland Environmental and Energy Research, The Jacob Blaustein Institutes for Desert Research (BIDR), Ben-Gurion University of the Negev, Sede Boker Campus, Midereshet Ben-Gurion 84990, Israel

Munich Data Science Institute, TUM, 85748 Garching, Walther-von-Dyck-Straße 10, Germany

Funding

Agencia Estatal de Investigaci?n · Deutsche Forschungsgemeinschaft · Bundesministerium f?r Wirtschaft und Energie · Ministry of Energy, Israel · Horizon 2020 Framework Programme · Generalitat de Catalunya · Ben-Gurion University of the Negev · CERCA Programme · Severo Ochoa Centres of Excellence programme · TUM Innovation Network for Artificial Intelligence powered Multifunctional Material Design · Spanish Ministry of Science and Education

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