Artificial Data Generation: A Strategy to Improve Efficiency Predictions in Mixed Sn-Pb Perovskite Solar Cells

No abstract is available for this paper.

• Publication year

  2025

• Venue

  Materials Today Communications

• Publication date

  2025-01-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.mtcomm.2025.111625
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Synergistic Effects of Energy Level Alignment and Trap Passivation via 3,4-Dihydroxyphenethylamine Hydrochloride for Efficient and Air-Stable Perovskite Solar Cells

  2024cited by this paper
• Self‐healing polymers in rigid and flexible perovskite photovoltaics

  2024cited by this paper
• Exploring Nanoscale Perovskite Materials for Next-Generation Photodetectors: A Comprehensive Review and Future Directions

  2024cited by this paper
• Band gap tuning of perovskite solar cells for enhancing the efficiency and stability: issues and prospects

  2024cited by this paper
• A novel chain-like conjugated donor-π-acceptor molecular additive for highly efficient and stable perovskite solar cells

  2024cited by this paper
• Significance of Formamidinium Incorporation in Perovskite Composition and Its Impact on Solar Cell Efficiency: A Mini‐Review

  2024cited by this paper
• Enhancing Plant Leaf Disease Prediction Through Advanced Deep Feature Representations: A Transfer Learning Approach

  2024cited by this paper
• Machine learning as a characterization method for analysis and design of perovskite solar cells

  2024cited by this paper
• Surface-Bulk-Passivated Perovskite Films Via 2-Thiophenemethylammonium Bromide and Pbbr2 For Air-Processed Perovskite Solar Cells with High-Stability

  2023cited by this paper
• Prediction of band gap and optimum electrical parameters of a thin homojunction perovskite solar cell based on FA1−xCsxSnyPb1−yI3 through a combination of SCAPS-1D and machine learning based modelling

  2023cited by this paper
• DataAssist: A Machine Learning Approach to Data Cleaning and Preparation

  2023cited by this paper
• Additive Engineering in Spray Enables Efficient Methylammonium-Free Wide-Bandgap Perovskite Solar Cells

  2023cited by this paper
• Green N1 Additive Modified Perovskite Precursor Enables Effective Manufacturing of Large-Area Solar Cell Modules with High Efficiency and Stability

  2023cited by this paper
• On scientific understanding with artificial intelligence

  2022cited by this paper
• A Review of Synthetic Image Data and Its Use in Computer Vision

  2022cited by this paper
• Predicting the device performance of the perovskite solar cells from the experimental parameters through machine learning of existing experimental results

  2022cited by this paper
• Organic Additive Engineering to Grow High‐Quality Inorganic CsPbX3 Perovskite Films for Efficient and Stable Solar Cells

  2022cited by this paper
• Advances and challenges in understanding the microscopic structure–property–performance relationship in perovskite solar cells

  2022cited by this paper
• RETRACTED ARTICLE: The effect of changing the ratios of perovskite triple cations and anions on the optical properties and solar cell performance of perovskite thin films

  2022cited by this paper
• Grain Boundary Chemical Anchoring via Bidirectional Active Site Additive Enables Efficient and Stable Perovskite Solar Cells

  2022cited by this paper
• Enhanced Efficiency and Stability of Perovskite Solar Cells Based on Carbon-Counter-Electrode Via Anti-Solvent Treatment

  2022cited by this paper
• Cation Engineering for Resonant Energy Level Alignment in Two-Dimensional Lead Halide Perovskites.

  2021cited by this paper
• Role of additives and surface passivation on the performance of perovskite solar cells

  2021cited by this paper
• Machine learning-guided search for high-efficiency perovskite solar cells with doped electron transport layers

  2021cited by this paper
• Hybrid Organic–Inorganic Halide Post‐Perovskite 3‐Cyanopyridinium Lead Tribromide for Optoelectronic Applications

  2021cited by this paper
• Optimized Carrier Extraction at Interfaces for 23.6% Efficient Tin–Lead Perovskite Solar Cells

  2021cited by this paper
• Thiamine additive engineering enables improved film formation towards high efficiency and moisture stability in perovskite solar cells

  2021cited by this paper
• Multifunctional liquid additive strategy for highly efficient and stable CsPbI2Br all-inorganic perovskite solar cells

  2021cited by this paper
• Effect of the hole transporting layers on the inverted perovskite solar cells

  2021cited by this paper
• Double-site defect passivation of perovskite film via fullerene additive engineering toward highly efficient and stable bulk heterojunction solar cells

  2021cited by this paper
• Photon management to reduce energy loss in perovskite solar cells.

  2021cited by this paper
• A brief review of hole transporting materials commonly used in perovskite solar cells

  2021cited by this paper
• Stability and efficiency improved perovskite solar cells through tuning the hydrophobicity of the hole transport layer with an organic semiconductor

  2021cited by this paper
• Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges

  2021cited by this paper
• Enhanced efficiency and stability in Sn-based perovskite solar cells with secondary crystallization growth

  2021cited by this paper
• Solvent engineering for perovskite solar cells: a review

  2020cited by this paper
• Electron transport material effect on performance of perovskite solar cells based on CH3NH3GeI3

  2020cited by this paper
• Data science applications to string theory

  2020cited by this paper
• A review of aspects of additive engineering in perovskite solar cells

  2020cited by this paper
• A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis

  2020cited by this paper
• Effects of cation size and concentration of cationic chlorides on the properties of formamidinium lead iodide based perovskite solar cells

  2020cited by this paper
• Green solvent for perovskite solar cell production

  2020cited by this paper
• Text Classification Algorithms: A Survey

  2019cited by this paper
• Strategies for Modifying TiO2 Based Electron Transport Layers to Boost Perovskite Solar Cells

  2019cited by this paper
• Impact of Electron Transport Layers (ETLs) and Hole Transport Layer (HTLs) on Perovskite Solar Cells Performance

  2019cited by this paper
• Robust dimensionality reduction via feature space to feature space distance metric learning

  2019cited by this paper
• A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning

  2019cited by this paper
• Optimization of anti-solvent engineering toward high performance perovskite solar cells

  2019cited by this paper
• Performance analysis of perovskite solar cells in 2013–2018 using machine-learning tools

  2019cited by this paper
• Review of Novel Passivation Techniques for Efficient and Stable Perovskite Solar Cells

  2019cited by this paper
• Off-Stoichiometric Methylammonium Iodide Passivated Large Grain Perovskite Film in Ambient Air for Efficient Inverted Solar Cells.

  2019cited by this paper
• Metal Cations in Efficient Perovskite Solar Cells: Progress and Perspective

  2019cited by this paper
• Synergistic effect of anions and cations in additives for highly efficient and stable perovskite solar cells

  2018cited by this paper
• Optimization of TiO 2 /ZnO bilayer electron transport layer to enhance efficiency of perovskite solar cell

  2018cited by this paper
• FA0.88Cs0.12PbI3−x(PF6)x Interlayer Formed by Ion Exchange Reaction between Perovskite and Hole Transporting Layer for Improving Photovoltaic Performance and Stability

  2018cited by this paper
• Grain-boundary effect and post treatment of active layer for efficient inverted planar perovskite solar cells

  2018cited by this paper
• Systematic investigation of the impact of operation conditions on the degradation behaviour of perovskite solar cells

  2018cited by this paper
• Electron-Transport Materials in Perovskite Solar Cells

  2018cited by this paper
• Metaheuristic design of feedforward neural networks: A review of two decades of research

  2017cited by this paper
• Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics

  2017cited by this paper
• Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error.

  2017cited by this paper
• Enhanced Efficiency and Stability of Perovskite Solar Cells via Anti-Solvent Treatment in Two-Step Deposition Method.

  2017cited by this paper
• Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties.

  2017cited by this paper
• High Open‐Circuit Voltages in Tin‐Rich Low‐Bandgap Perovskite‐Based Planar Heterojunction Photovoltaics

  2017cited by this paper
• Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations

  2017cited by this paper
• Current status of electron transport layers in perovskite solar cells: materials and properties

  2017cited by this paper
• Anti-Solvent Crystallization Strategies for Highly Efficient Perovskite Solar Cells

  2017cited by this paper
• Machine-learning the string landscape

  2017cited by this paper
• Quantum-chemical insights from deep tensor neural networks

  2016cited by this paper
• Auto-encoder based dimensionality reduction

  2016cited by this paper
• Deep Learning

  2016cited by this paper
• A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials

  2016cited by this paper
• Interface band structure engineering by ferroelectric polarization in perovskite solar cells

  2015cited by this paper
• Machine learning for quantum mechanics in a nutshell

  2015cited by this paper
• Reversible Anion Exchange Reaction in Solid Halide Perovskites and Its Implication in Photovoltaics

  2015cited by this paper
• Solvent engineering for high-performance inorganic-organic hybrid perovskite solar cells.

  2014cited by this paper
• Deep learning in neural networks: An overview

  2014cited by this paper
• Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

  2012cited by this paper
• ImageNet classification with deep convolutional neural networks

  2012cited by this paper
• Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

  1980cited by this paper

• High-performance perovskite tandem architectures: Materials innovation, device engineering, and industrial prospects

  2026cites this paper
• Density Estimation Based on Mixtures of Gaussians for Perovskite Solar Cells Modeling

  2026cites this paper
• From Data‐Driven to Intelligence‐Driven: Innovating Research Paradigms of Perovskite Solar Cells

  2025cites this paper
• Optimizing Charge Transport and Bandgap Alignment of ETL and HTL in Tin-Based Perovskite Solar Cells via Machine Learning

  2025cites this paper
• Integrated Machine Learning Framework for the Co-Optimization of Efficiency and Stability in Tin-Based Perovskite Solar Cells

  2025cites this paper
• Physics-Informed Temporal Generative Adversarial Networks: A Potent Tool for Lithium Battery Data Generation

  2025cites this paper
• Optimizing the efficiency of perovskite solar cells for improved performance and energy conversion using temporal dynamic graph neural network

  2025cites this paper