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COMPAS-3:一个关于缩聚二碳化合物的数据集
Alexandra Wahab1, Renana Gershoni-Poranne2
1The Laboratory for Organic Chemistry, Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland.
现在,COMPAS项目数据库中包含了约48k个具有优化结构和特性的周周凝结聚化碳化合物. 这些数据有助于设计用于有机电子和机器学习应用的新芳香分子.
科学领域:
- 计算化学是一种计算化学.
- 材料科学是一种材料科学.
- 有机化学 有机化学
背景情况:
- 多环芳 (PAH) 在有机电子产品中至关重要.
- 对PAHs的数据库对于计算研究和材料设计至关重要.
- 环凝结的PAH具有独特的结构和电子特性.
研究的目的:
- 介绍多环芳香系统 (COMPAS) 计算数据库的第三部分.
- 开发两个具有优化结构和性质的周密凝聚聚化碳化合物 (PBH) 数据集.
- 为化学中的数据驱动机器学习研究提供基础.
主要方法:
- 计数和数据生成的~39k和~9k周密集的PBHs.
- 计算方法:GFN2-xTB和CAM-B3LYP-D3BJ/cc-pvdz//CAM-B3LYP-D3BJ/def2-SVP. 这两种计算方法都是使用的.
- 使用生成的数据集进行结构-属性关系分析.
主要成果:
- 创建了两个周密聚合PBHs的综合数据集.
- 对于稍微扭曲的分子,在计算方法之间发现了最大的几何不一致.
- 突出了分子大小和废除对HOMO-LUMO差距的影响.
结论:
- 康帕斯数据库被扩展为关于周密集型PBHs的有价值数据.
- 计算方法显示不同协议,特别是在扭曲的结构.
- 对结构性质趋势的洞察力有助于合理设计新的功能性芳香分子.
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