Accurate Prediction of HOMO-LUMO Gap Using DFT Functional and Application to Next-Generation Organic Telluro[n]Helicenes Materials

利用DFT泛函精确预测HOMO-LUMO能隙及其在下一代有机碲[n]螺烯材料中的应用

阅读:1

Abstract

The present work purposes and establishes an accurate prediction of HOMO-LUMO energies of thiophene-, selenophene-, and tellurophene-based helicenes using 15 different DFT methodologies. DFT functionals used in this work are PBE, PBE0, B3LYP, B3LYP-D, B3LYP-D3, M06, MN15, HSE06, LC-BLYP, CAM-B3LYP, LC-ωPBE, ωΒ97XD and B2PLYP. DFT HOMO-LUMO gaps are compared with the fundamental gaps calculated at the CCSD(T) level of theory. The LANL2DZ basis set is used for tellurium atoms, and the 6-311++G(d,p) basis set is used for other elements. Statistical error analysis suggests that the HOMO-LUMO energy gaps can be accurately obtained using ωB97XD functional, with geometry optimization performed at the same theoretical level. However, geometry optimization using the B3LYP functional, followed by single-point energy calculation with the ωB97XD functional, provides a more cost-effective method with similar accuracy for energy gap prediction. HOMO-LUMO gaps of telluro[n]helicenes ([n]TeH) are redshifted compared with their S- and Se-analogs. Tellurophene-based helicenes ([n]TeH) systems are easy to oxidize in contrast to their S- and Se-analogs. Dimerization studies have found that substituted [7]TeH(•+) is more stable in dichloromethane than its S- and Se-analogs. The CAM-B3LYP and ωΒ97XD functionals are used in conjunction with the TDDFT procedure to explore the excited states of [n]TeH radical cations. These radical cation systems showed better absorption in the infrared range than S- and Se-systems. Overall, our benchmarking studies lead to an accurate prediction of HOMO-LUMO gaps of [n]TeH. Further, this study demonstrates the potential of Te-based helical structures to create versatile next-generation organic materials.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。