A density functional theory study at the B3LYP/6-31++G** + RECP(Sb) level of the HF/SbF(5) superacid system was carried out. The geometries of possible electrophilic species, such as H(2)F(+).Sb(2)F(11)(-) and H(3)F(2)(+).Sb(2)F(11)(-), were calculated and correspond with available experimental results. Calculations of different equilibrium reactions involving HF and SbF(5) allowed the relative concentration of the most energetically favorable species present in 1:1 HF/SbF(5) solutions to be estimated. These species are H(+).Sb(2)F(11)(-), H(2)F(+).Sb(2)F(11)(-), H(3)F(2)(+).Sb(2)F(11)(-), and H(4)F(3)(+).Sb(2)F(11)(-), which correspond to 36.9, 16.8, 36.9, and 9.4%, respectively. Calculations of the acid strength of the electrophilic species were also performed and indicated that, for the same anion, the acid strength increases with the solvation degree. The entropic term also plays a significant role in proton-transfer reactions in superacid systems.
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Food Res Int
January 2025
College of Food Science and Nutritional Engineering, National Engineering Research Centre for Fruits and Vegetables Processing, Key Laboratory of Storage and Processing of Fruits and Vegetables, Ministry of Agriculture, Engineering Research Centre for Fruits and Vegetables Processing, Ministry of Education, China Agricultural University, Beijing 100083, China. Electronic address:
Reactive carbonyl species (RCS) are a class of compounds with one or more C = O structures with highly reactive electrophilic properties. This comprehensive review delves into the multifaceted role of RCS in thermally processed foods, where they serve as both crucial intermediates in the development of food color and flavor, as well as precursors of potentially harmful compounds. By exploring the carbonyl pool concept, the impact of RCS equilibrium on the formation and reduction of hazardous substances such as acrylamide, hydroxymethylfurfural, advanced glycation end-products, and heterocyclic amines was elucidated.
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Chemistry & Chemical Engineering Data Center, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China.
Machine learning (ML) is expected to bring new insights into the impact of organic structures on the reaction mechanisms in reactive oxygen species oxidation. However, understanding the underlying chemical mechanisms still faces challenges due to the limited interpretability of the ML models. In this study, interpretable ML models were established to predict the second-order rate constants between hydroxyl radicals (OH) and organics ().
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View Article and Find Full Text PDFBioorg Med Chem
January 2025
Department of Pharmaceutical Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China; Ningbo Institute of Dalian University of Technology, Ningbo 315016, China. Electronic address:
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View Article and Find Full Text PDFJ Am Chem Soc
January 2025
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