The DFT Approach to predict 13C NMR chemical shifts of hydrocarbon species adsorbed on Zn-modified zeolites

Abstract

¹³C MAS NMR spectroscopy is a powerful technique to study the mechanisms of hydrocarbon transformations on heterogeneous catalysts. It can reliably identify the surface intermediates and the adsorbed products based on the analysis of their ¹³C chemical shifts, δ(¹³C). However, the unambiguous assignment of the detected signals is always a challenge due to the uncertainty of the nature of the surface intermediates formed and the mechanism of adsorbed species interaction with active sites. The way to solve this problem is the application of DFT calculations to predict chemical shifts for the expected intermediate hydrocarbon species. Herein, the methodology for δ(¹³C) chemical shift calculations for adsorbed species has been proposed. It includes: (i) zeolite framework optimization with periodic DFT (pPBE); (ii) medium-sized cluster geometry optimization with hybrid GGA (PBE0), and (iii) σ(¹³C) values calculation followed by δ(¹³C) estimation using the linear regression method. It is inferred that the TPSS/cc-pVTZ method provides the best computational cost/accuracy ratio for the set of adsorbed hydrocarbon species that was previously detected experimentally on the surface of Zn-containing zeolites. The drawbacks of the computation method have also been revealed and discussed.