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Investigation of Structure-Efficiency Relationship and Performance Prediction of Organic Cathode Interfacial Materials in Organic Solar Cells with Machine Learning

https://doi.org/10.2139/ssrn.4780622
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Quinoxaline-based non-fullerene guest acceptor enables ternary organic solar cells achieving 18.9% efficiency via reducing energy loss and regulating morphology
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A machine learning prediction model for quantitative analyzing the influence of non-radiative voltage loss on non-fullerene organic solar cells
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Ultrathin interlayers of a conjugated polyelectrolyte for low work-function cathodes in efficient inverted organic solar cells
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Recent development of the inverted configuration organic solar cells
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Low temperature based PDINO cathode interlayer for high operational photostable inverted non-fullerene organic solar cells
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Effect of Increasing the Descriptor Set on Machine Learning Prediction of Small Molecule-Based Organic Solar Cells
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Mechanism of the Alcohol-Soluble Ionic Organic Interlayer in Organic Solar Cells
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Glucose and Its Derivatives as Interfacial Materials for Inverted Organic Solar Cells
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Polystyrene-block-Poly(ionic liquid) Copolymers as Work Function Modifiers in Inverted Organic Photovoltaic Cells
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Machine-Learning-Assisted Screening of Interface Passivation Materials for Perovskite Solar Cells
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Photoconductive Cathode Interlayer for Highly Efficient Inverted Polymer Solar Cells
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Non-fullerene acceptors for organic solar cells
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Single-layered organic photovoltaics with double cascading charge transport pathways: 18% efficiencies
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Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors
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Single-junction organic solar cells with over 19% efficiency enabled by a refined double-fibril network morphology
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Inverted organic solar cells with ITO electrodes modified with an ultrathin Al2O3 buffer layer deposited by atomic layer deposition
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A water/alcohol-soluble conjugated porphyrin small molecule as a cathode interfacial layer for efficient organic photovoltaics
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Combining electronic and structural features in machine learning models to predict organic solar cells properties
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Highly efficient inverted organic solar cells using amino acid modified indium tin oxide as cathode
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