DOI 10.1007/s00894-025-06567-6
A DFT-elucidated mechanism of red-light-induced desulfurization: the role of excited states in C-S cleavage of dibenzothiophene models.
Аннотация
CONTEXT: SOx emissions from diesel fuel necessitate the development of efficient and environmentally friendly desulfurization technologies. This study investigates the catalyst-free photochemical desulfurization mechanism of a diesel model compound, 2-decyl-7-(10-phenyldecyl)dibenzo[b,d]thiophene (D-PD-DBT), under red light irradiation, providing a theoretical foundation for experimentally observed phenomena. Experimental validation confirmed a desulfurization efficiency of up to 46.2%, which was accompanied by the degradation of aromatic structures as observed by FTIR. The proposed three-step mechanism, elucidated computationally, reveals that population of the triplet state (T1), likely via photosensitization from other chromophores in the diesel matrix, is the critical initiating step. This excited state drastically reduces the HOMO-LUMO gap and chemical hardness, facilitating the initial C-S bond cleavage. The reaction proceeds through the decomposition of intermediates, culminating in the formation of highly stable end products, including benzene, which thermodynamically drives the process to be unidirectional. These findings highlight the fundamental role of excited energy surfaces in enabling C-S bond cleavage without a catalyst.
METHODS
All quantum chemical calculations were performed using density functional theory (DFT) at the B3LYP/6-31G level of theory. Excited state analyses were conducted using time-dependent DFT (TD-DFT) to map the photochemical reaction pathway. Reactant, intermediate, and product structures were geometrically optimized and confirmed as minima through harmonic frequency analysis. A set of conceptual DFT reactivity descriptors was calculated from the frontier molecular orbital energies (HOMO and LUMO). The Gaussian 09 software package was used for all computational modeling, with visualization performed using Gaussview and Avogadro.
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