Density Functional Theory (DFT) and Time-Dependent DFT (TDDFT) Studies of Porphyrin Adsorption on Graphene: Insights on the Effect of Substituents and Central Metal on Adsorption Energies

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Rayene Gara, Ángel Morales-García, Youssef Arfaoui, Francesc Illas
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Abstract

Combining metalloporphyrins (MPr) and graphene constitutes key composites in the development of photovoltaic devices. Here, we focus on the analysis of the properties of metalloporphyrins/graphene systems by means of the density functional theory (DFT) and its time-dependent (TDDFT) version, focusing on the ground and singlet excited states. Our benchmark analysis concludes that ωB97XD density functional combined with 6-31G(d)/Def2-TZVP basis set is a better-suited method for simulating accurate MPr adsorption on graphene. It is shown that a reduced atomic model where the external organic shell of the structure is removed provides the same resulting optoelectronic properties of the original model, constituting an important speed-up of the calculations when studying porphyrins-derived molecules. We observe that ZnPr provides the highest light harvesting efficiency (LHE) value. In addition, we find out that the adsorption energy increases monotonically with the size of the graphene flake and the highest stability involves the use of graphene comprising above 500 atoms. Besides, CdPr and HgPr keep their properties as photosensitizers when they are bonded to graphene and show promising values in terms of LHE emerging as suitable solar energy harvesters.

Abstract Image

Abstract Image

石墨烯上卟啉吸附的密度泛函理论(DFT)和时变DFT (TDDFT)研究:取代基和中心金属对吸附能影响的见解
结合金属卟啉(MPr)和石墨烯是光伏器件发展的关键复合材料。本文利用密度泛函理论(DFT)及其时间相关理论(TDDFT)分析了金属卟啉/石墨烯体系的性质,重点分析了基态和单线态激发态。我们的基准分析表明,ωB97XD密度函数结合6-31G(d)/Def2-TZVP基集是一种更适合模拟石墨烯上MPr精确吸附的方法。研究表明,去除结构外部有机壳的简化原子模型提供了与原始模型相同的光电特性,这在研究卟啉衍生分子时构成了重要的计算速度加快。我们观察到ZnPr具有最高的光收集效率(LHE)值。此外,我们发现吸附能随着石墨烯薄片的大小单调增加,并且最高的稳定性涉及使用含有500个原子以上的石墨烯。此外,当CdPr和HgPr与石墨烯结合时,它们保持了光敏剂的特性,并且在LHE作为合适的太阳能收集器方面显示出了很好的价值。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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