Benchmark studies on protonated benzene (BZH+) and water (Wn, n = 1–6) clusters: a comparison of hybrid DFT with MP2/CBS and CCSD(T)/CBS methods

Abstract

The selection of a suitable density functional theory (DFT) method is critical to study the interfacial interactions between the protonated species and water clusters at the carbon surface. The interfacial interactions are crucial for the stability of complexes with the support of various kinds of noncovalent interactions. To model this environment, we consider excess proton with benzene [i.e., protonated benzene (BZH+)] and water clusters using high-level electronic structure calculations. These clusters were stabilized by different kinds of noncovalent interactions at the interface. Modeling these clusters is challenging as high-level electronic structure calculations are expensive, whereas less expensive DFT-based methods are inconsistent. Thus, in the present study, we have chosen various hybrid DFT functionals (such as B3LYP, PBE0, M05-2X, M06-2X, and M11) to study the geometries, energetics, and the importance of interfacial interactions. Furthermore, these methods performance is validated by using MP2/CBS and CCSD(T)/CBS approaches. It is found that the selected functionals are reliable to predict the structure, but the energetics of these clusters are varied. Also, each one of these methods has its own advantage in certain aspects. Scrutiny of result reveals that hybrid GGA (PBE0) and hybrid meta-GGA (M11) functionals are more consistent for the structure and stability with the benchmark obtained from MP2/CBS and CCSD(T)/CBS approaches. Besides, our benchmark report states that the selected DFT method can be suitable for the following individual interactions; (1) PBE0 suited for O–H+···O, O–H+···π and C–H+···O interactions, (2) M05-2X more suited for O–H···π, C–H···O, and (3) B3LYP method highly favor for the O–H+···O interactions (i.e., proton transfer). Overall, PBE0/aVTZ method has an excellent correlation with MP2/CBS and CCSD(T)/CBS methods based on our analysis using the mean signed error and correlation coefficient (r) analyses.