The Value of Device Characterization for the Optimization of Organic Solar Cells DOI Creative Commons
Leonard Christen, Beatriz Urbano, Andreas Krause

et al.

Advanced Energy Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Abstract In addition to achieving record efficiencies of ≈20%, organic photovoltaics (OPV) has overcome several additional challenges. These include researching environmentally friendly solvents, improving stability, yield, and scaling up industrial standards in terms cell size mass production. However, identifying the optimal candidates from countless material combinations determining exact process parameters is like looking for a needle haystack. Process optimization usually comprises phases such as device fabrication, measurement, evaluation, concluding with experimental design next round making. Given extent parameter space, this can be extremely time‐consuming. algorithms mainly based on mathematical models become more prevalent automated laboratories, question arises how physics domain knowledge characterization samples into algorithmic process. To address question, benchmark function created using solar data originating hundreds cells prepared different processing conditions. This used test compare approaches quantify under which conditions physical improve speed an laboratory.

Language: Английский

The Value of Device Characterization for the Optimization of Organic Solar Cells DOI Creative Commons
Leonard Christen, Beatriz Urbano, Andreas Krause

et al.

Advanced Energy Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Abstract In addition to achieving record efficiencies of ≈20%, organic photovoltaics (OPV) has overcome several additional challenges. These include researching environmentally friendly solvents, improving stability, yield, and scaling up industrial standards in terms cell size mass production. However, identifying the optimal candidates from countless material combinations determining exact process parameters is like looking for a needle haystack. Process optimization usually comprises phases such as device fabrication, measurement, evaluation, concluding with experimental design next round making. Given extent parameter space, this can be extremely time‐consuming. algorithms mainly based on mathematical models become more prevalent automated laboratories, question arises how physics domain knowledge characterization samples into algorithmic process. To address question, benchmark function created using solar data originating hundreds cells prepared different processing conditions. This used test compare approaches quantify under which conditions physical improve speed an laboratory.

Language: Английский

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