论文标题
基于遗传算法的钙钛矿太阳能电池设计的材料选择方法
Material selection method for a perovskite solar cell design based on the genetic algorithm
论文作者
论文摘要
在这项工作中，我们提出了一种利用遗传算法的钙钛矿太阳能细胞设计的材料组合的方法。太阳能电池基于甲基铵铅卤化物CH3NH3PBX3，由于其高吸收系数和尖锐的Urbach尾巴，长扩散长度和载体寿命以及高载体迁移率而吸引了研究人员。但是，在暴露于水分的情况下，它们的稳定性较差仍然构成挑战。在我们的工作中，我们根据文献中的可用实验数据为每种材料分配了稳定指数，功率转换效率指数和成本效益指数，并且我们的算法确定了TIO2/CH3NH3PBI2.1BR0.9/sipo-noper-nepero-fortialm在成本，成本，效率和稳定性方面是最均衡的解决方案。可以进一步扩展所提出的方法，以帮助在将来提供有关钙钛矿材料的更多数据，以帮助所有植物套件多期太阳能电池设计。
In this work, we propose a method of selecting the most desirable combinations of material for a perovskite solar cell design utilizing the genetic algorithm. Solar cells based on the methylammonium lead halide, CH3NH3PbX3, attract researchers due to the benefits of their high absorption coefficient and sharp Urbach tail, long diffusion length and carrier lifetime, and high carrier mobility. However, their poor stability under exposure to moisture still poses a challenge. In our work, we assigned stability index, power conversion efficiency index, and cost-effectiveness index for each material based on the available experimental data in the literature, and our algorithm determined the TiO2/CH3NH3PbI2.1Br0.9/Spiro-OMeTAD as the most well balanced solution in terms of cost, efficiency, and stability. The proposed method can be extended further to aid the material selection in all-perovskite multijunction solar cell design as more data on perovskite materials become available in the future.
