Design and Performance Optimization of Small Molecule Organic Photovoltaic Materials
DOI:
https://doi.org/10.62051/yr4cbz73Keywords:
Machine Learning; Approximate Bayesian Computing; Molecular Structure Design.Abstract
In this article, researchers have investigated the design and capability optimisation of SMPS with a particular emphasis on increasing the efficiency of power transfer and developing new manufacturing techniques. Nowadays, the PV industry mostly depends on silicon base technique, but it has many advantages such as high cost, low flexibility and great environment impact. By comparison, the structure of small molecular materials is easily duplicated and has a promising future in the field of PV devices. In this paper, this paper present a discussion on how to increase energy conversion efficiency by using SMPS, as well as the high efficiency of all SMPS systems. In addition, this paper also proposes methods and theoretical frameworks for optimizing material structures using experimental design and machine learning. Not only do they contribute to the improvement of material properties, but they also provide significant theory and practice support for developing highly efficient PV devices.
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