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首页> 外文会议>IEEE MIT Undergraduate Research Technology Conference >Improvement of Perovskite Solar Cell Efficiency through PLA Additive Induced Boundary Passivation : With Application of Machine Learning in Crystal Image Analysis
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Improvement of Perovskite Solar Cell Efficiency through PLA Additive Induced Boundary Passivation : With Application of Machine Learning in Crystal Image Analysis

机译：通过PLA添加剂诱导的边界钝化提高钙钛矿太阳能电池效率：机器学习在晶体图像分析中的应用

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Perovskite solar cells are an extremely promising photovoltaic technology due to their rapid improvement in power conversion efficiency (PCE) in recent years. Polylactic acid (PLA) is a biodegradable polyester plastic that is used in additive manufacturing. In this study, we used two PLA additives, 30K PLA and 16K PLA, to improve the performance of perovskite solar cells. In particular, we show that these PLA additives unanimously increase the PCE of perovskite solar cells across various concentrations and molecular weights. Additionally, because perovskite crystal size is positively correlated with cell efficiency, we developed a machine learning algorithm to autonomously compute size distributions of PLA-modified perovskite crystals from SEM images. This procedure showed that both the 30K and 16K PLA increased the average size of the crystal grains (p<0.05). The reason for the increased performance and crystal size are that the PLA forms complexes with excess PbI2, with PLA at the core and a PbI2 surrounding. These complexes passivate the boundaries between crystal grains, decreasing the number of trapped or dissoluted excitons and redirecting them in the direction of the current. The complexes likely also decrease the interfacial tension between crystal grains, resulting in crystal sizes which are up to 226% larger. By varying only concentration or only molecular weight, we discovered that there existed an optimal concentration and an optimal molecular weight of around 0.3 mg/mL and 16,000 amu respectively. We identified competing factors that would yield this trend: the aforementioned positive effects of the PLA, and the negative effects of nonideality of the JV curve (and consequences) and poorer conductivity. Given the observed improvement in efficiency of up to 17.5%, these results demonstrate that PLA additives are a novel and promising method of improving the performance of perovskite solar cells.
机译：钙钛矿太阳能电池由于近年来功率转换效率（PCE）的快速提高而成为一种极有前途的光伏技术。聚乳酸（PLA）是一种可生物降解的聚酯塑料，用于增材制造。在这项研究中，我们使用了两种PLA添加剂：30K PLA和16K PLA，以改善钙钛矿太阳能电池的性能。特别是，我们证明了这些PLA添加剂在各种浓度和分子量下均能一致地提高钙钛矿型太阳能电池的PCE。此外，由于钙钛矿晶体尺寸与电池效率呈正相关，因此我们开发了一种机器学习算法，可从SEM图像自动计算PLA改性钙钛矿晶体的尺寸分布。该程序表明30K和16K PLA均增加了晶粒的平均尺寸（p <0.05）。性能和晶体尺寸增加的原因是，PLA与过量的PbI形成复合物 2 ，以PLA为核心，以PbI为核心 2 周围。这些复合物钝化了晶粒之间的边界，从而减少了被俘获或溶解的激子的数量，并使它们在电流方向上重新定向。配合物也可能降低晶粒之间的界面张力，导致晶体尺寸最大增大226％。通过仅改变浓度或仅改变分子量，我们发现存在最佳浓度和最佳分子量分别为约0.3 mg / mL和16,000 amu。我们确定了将导致这种趋势的竞争因素：PLA的上述积极影响，以及合资曲线的非理想性（和后果）的负面影响以及导电性较差。鉴于观察到的效率提高高达17.5％，这些结果表明PLA添加剂是一种改善钙钛矿太阳能电池性能的新颖且有前途的方法。

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