چكيده به لاتين
Abstract: Today, the use of porphyrin photocatalysts is rapidly increasing, and a large amount of these substances have been appeared in the form of catalysts to simulate the process of natural photosynthesis. One of the main advantages of using porphyrin photocatalysts is their use in the visible region of electromagnetic waves, which allows the use of solar energy. In this study, a fixed and water-soluble porphyrin (TSPP) used as a photocatalyst. This CO2mpound is capable of transferring electrons in its excited state. To increase the efficiency of electron transfer to the biocatalyst part where the final stage of the reaction takes place. The bipyridine CO2mpounds have been used as an alternative for NADH as a natural electron carrier. The proposed model examines the kinetics of electron transfer from an electron carrier that can be replaced by NADH. This study performed through a quantitative structure-activity relationship to predict the best structure for electron transfer. The advantage of using the quenching CO2nstant of fluorescence with electron acceptor CO2mpounds shows their electron acceptability. For this end, the Fluorescence Quenching CO2nstant, a numerical CO2nstant value of the fluorescence quenching measurements, known as the Stern-Volmer CO2nstant Ksv M-, used as an activity for its relation to the extinguishing structure. The multiple linear regression method investigated as a powerful tool for predicting purposes. The models reported in this study include a model for predicting the power of quenching fluorescence, which can be used to predict the reaction efficiency by predicting values. On the other hand, acCO2rding to Eq., which predicts the quantum efficiency of fluorescence, another set of aromatic CO2mpounds, an effective and reliable prediction can be made about the initial part of all photocatalytic reactions, which is the absorption of light. Also, the evaluation and validation of the model by statistical parameters of CO2rrelation CO2efficient (R) and cross-validation (Q) CO2nfirms the model's ability to predict the desired structure.
