Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models

These are data used for the submitted paper "Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models" at Advanced Energy Materials.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-21
DOI
https://doi.org/10.5281/zenodo.15480770
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models

Zenodo (CERN European Organization for Nuclear Research)
Photovoltaic System Optimization Techniques
article

Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models

article en

Abstract

These are data used for the submitted paper "Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models" at Advanced Energy Materials.

Zenodo (CERN European Organization for Nuclear Research)
Forschungszentrum Jülich (DE)
Affordable and clean energy
Openalex Percentile: Top 66%
Photovoltaic System Optimization Techniques
DOIOpen Access PDFOpenAlex
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Inferring Material Parameters from Current-Voltage Curves in Organic Solar Cells via Neural-Network-Based Surrogate Models · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS