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IF 3.9 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Materials Science and Engineering: B Pub Date : 2025-03-17 DOI:10.1016/j.mseb.2025.118212

Cihat Güleryüz , Abrar U. Hassan , Hasan Güleryüz , Hussein A.K. Kyhoiesh , Mohamed H.H. Mahmoud

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引用次数: 0

摘要

本研究提出了一种机器学习（ML）方法，用于设计二苯甲酮类有机发色团，使其具有最低的 LUMO 能量（ELUMO）。我们从文献中收集了 1142 个供体的数据集，并使用 RDKit 设计了它们的分子描述符。在各种模型中，随机森林回归模型能准确预测它们的 ELUMO 值。根据这些预测结果，利用它们的合成可及性似然指数（SALI）得分设计出了 5000 个新的供体。其 SHAP 值分析表明，它们的电拓扑状态指数是降低 ELUMO 的最关键描述指标。通过密度泛函理论（DFT），进一步扩展了表现最佳的供体与受体及其光伏（PV）特性。研究结果表明，它们的最大开路电压（Voc）为 2.30 V，短路电流（Jsc）为 47.19 mA/cm2，光收集效率（LHE）为 93%。这项研究证明了 ML 辅助设计在设计新型有机发色团方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A machine learning assisted designing and chemical space generation of benzophenone based organic semiconductors with low lying LUMO energies

Current study presents a machine learning (ML) approach to design benzophenone-based organic chromophore with their lowest possible LUMO energy (E_LUMO). A dataset of their 1142 donors is collected from literature and their molecular descriptors are designed by using RDKit. Among various models, the Random Forest regression model produces accurate results to predict their E_LUMO values. Based on these predictions, their 5000 new donors are designed with their Synthetic Accessibility Likelihood Index (SALI) scores. Their SHAP value analysis reveals that their electro topological state indices are the most critical descriptors to lowering E_LUMOs. The top-performing donor are further extended with acceptors and their photovoltaic (PV) properties by density functional theory (DFT). Their results show their maximum open-circuit voltage (V_oc) of 2.30 V, a short-circuit current (J_sc) of 47.19 mA/cm², and a light-harvesting efficiency (LHE) of 93 %. This study demonstrates the potential of ML assisted design to design new organic chromophores.

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来源期刊

Materials Science and Engineering: B 工程技术-材料科学：综合

CiteScore

5.60

自引率

2.80%

发文量

481

审稿时长

3.5 months

期刊介绍： The journal provides an international medium for the publication of theoretical and experimental studies and reviews related to the electronic, electrochemical, ionic, magnetic, optical, and biosensing properties of solid state materials in bulk, thin film and particulate forms. Papers dealing with synthesis, processing, characterization, structure, physical properties and computational aspects of nano-crystalline, crystalline, amorphous and glassy forms of ceramics, semiconductors, layered insertion compounds, low-dimensional compounds and systems, fast-ion conductors, polymers and dielectrics are viewed as suitable for publication. Articles focused on nano-structured aspects of these advanced solid-state materials will also be considered suitable.