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优化无机CsCuSbCl/CsTiI双吸收体太阳能电池:SCAPS-1D模拟与机器学习

Optimizing Inorganic CsCuSbCl/CsTiI Dual-Absorber Solar Cells: SCAPS-1D Simulations and Machine Learning.

作者信息

Li Xiangde, Fang Yuming, Zhao Jiang

机构信息

College of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

Nantong Institute, Nanjing University of Posts and Telecommunications, Nantong 226006, China.

出版信息

Nanomaterials (Basel). 2025 Aug 14;15(16):1245. doi: 10.3390/nano15161245.

DOI:10.3390/nano15161245
PMID:40863825
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12388759/
Abstract

Perovskite solar cells (PSCs) have emerged as a promising contender in photovoltaics, owing to their rapidly advancing power conversion efficiencies (PCEs) and compatibility with low-temperature solution processing techniques. Single-junction architectures reveal inherent limitations imposed by the Shockley-Queisser (SQ) limit, motivating adoption of a dual-absorber structure comprising CsCuSbCl (CCSC) and CsTiI (CTI)-lead-free perovskite derivatives valued for environmental benignity and intrinsic stability. Comprehensive theoretical screening of 26 electron/hole transport layer (ETL/HTL) candidates identified SrTiO (STO) and CuSCN as optimal charge transport materials, producing an initial simulated PCE of 16.27%. Subsequent theoretical optimization of key parameters-including bulk and interface defect densities, band gap, layer thickness, and electrode materials-culminated in a simulated PCE of 30.86%. Incorporating quantifiable practical constraints, including radiative recombination, resistance, and FTO reflection, revised simulated efficiency to 26.60%, while qualitative analysis of additional factors follows later. Furthermore, comparing multiple algorithms within this theoretical framework demonstrated eXtreme Gradient Boosting (XGBoost) possesses superior predictive capability, identifying CTI defect density as the dominant impact on PCE-thereby underscoring its critical role in analogous architectures and offering optimization guidance for experimental studies. Collectively, this theoretical research delineates a viable pathway toward developing stable, environmentally sustainable PSCs with high properties.

摘要

钙钛矿太阳能电池(PSCs)凭借其快速提升的功率转换效率(PCEs)以及与低温溶液处理技术的兼容性,已成为光伏领域颇具潜力的竞争者。单结结构显示出受肖克利 - 奎塞尔(SQ)极限所带来的固有局限性,这促使人们采用一种由CsCuSbCl(CCSC)和CsTiI(CTI)组成的双吸收体结构——这两种无铅钙钛矿衍生物因其环境友好性和内在稳定性而受到重视。对26种电子/空穴传输层(ETL/HTL)候选材料进行的全面理论筛选确定了SrTiO(STO)和CuSCN为最佳电荷传输材料,产生了16.27%的初始模拟功率转换效率。随后对包括体相和界面缺陷密度、带隙、层厚度以及电极材料等关键参数进行理论优化,最终模拟功率转换效率达到30.86%。纳入可量化的实际限制因素,包括辐射复合、电阻和FTO反射,将模拟效率修正为26.60%,而对其他因素的定性分析将随后进行。此外,在这个理论框架内比较多种算法表明,极端梯度提升(XGBoost)具有卓越的预测能力,确定CTI缺陷密度是对功率转换效率的主要影响因素——从而突出了其在类似结构中的关键作用,并为实验研究提供了优化指导。总体而言,这项理论研究描绘了一条开发具有高稳定性、环境可持续性的高性能钙钛矿太阳能电池的可行途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/f1b350576424/nanomaterials-15-01245-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/3a594e5bff3c/nanomaterials-15-01245-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/08328cac5a06/nanomaterials-15-01245-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/dccf0845cffc/nanomaterials-15-01245-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/c1dff886fb50/nanomaterials-15-01245-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/5b7823a79a3c/nanomaterials-15-01245-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/1b734ade5bf3/nanomaterials-15-01245-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/4f9b4cd06fdd/nanomaterials-15-01245-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/f1b350576424/nanomaterials-15-01245-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/549a2a3a1833/nanomaterials-15-01245-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/981ac7f2887e/nanomaterials-15-01245-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/d90fa3d9c314/nanomaterials-15-01245-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/21d15a932aa4/nanomaterials-15-01245-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/3a594e5bff3c/nanomaterials-15-01245-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/08328cac5a06/nanomaterials-15-01245-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/dccf0845cffc/nanomaterials-15-01245-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/c1dff886fb50/nanomaterials-15-01245-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/5b7823a79a3c/nanomaterials-15-01245-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/1b734ade5bf3/nanomaterials-15-01245-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/4f9b4cd06fdd/nanomaterials-15-01245-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127c/12388759/f1b350576424/nanomaterials-15-01245-g013.jpg

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Improving Photovoltaic Performance of Hybrid Organic-Inorganic MAGeI Perovskite Solar Cells via Numerical Optimization of Carrier Transport Materials (HTLs/ETLs).
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