Amino Acid/Dopamine-based Binary Catalyst For The Efficient Synthesis Of Cyclic Carbonates

Development of efficient, green and inexpensive way for the conversion of carbon dioxide (CO2) intouseful chemicals has attracted widespread attention in recent years. One of the most effective methods onchemical fixation of CO2is the synthesis of cyclic carbonates via coupling reaction of epoxides and CO2.Up till now, efforts are still being made in order to further overcome the problems in the correspondingprocess, such as unsatisfactory catalytic activities, critical reaction conditions and the requirement ofco-solvents. As our continuous work, herein, the synthesis of cyclic carbonates by using biocompatible,environmentally benign, and efficient catalysts has been systematically investigated. And the preliminaryinnovative results for this dissertation are summarized as follows.1. Biocompatible and recyclable amino acid based binary catalysts were proved to be efficient for thechemical fixation of CO2under the mild conditions. Effects of parameters such as catalyst molar ratio,catalyst amount, temperature, pressure, and reaction time were studied systematically. Under the optimizedreaction conditions,99%propylene oxide (PO) conversion and more than99%propylene carbonate (PC)selectivity could be achieved at the optimal conditions (molar ratio of KI to L-tryptophan was1:1,120oC,2MPa and1h). Moreover, the catalyst could be reused for six times without loss of its activity andselectivity, and was proved to be applicable to other terminal epoxides.2. Nano-sized polydopamine (PDA) sphere was prepared and combined with alkali metal halide as thecatalyst for the synthesis of cyclic carbonates. It was found that a99.0%conversion of PO with more than99.0%PC selectivity could be achieved by using KI/PDA as catalyst without any co-solvents under mildconditions. The catalyst showed good reusability and applicability to a series of epoxides. The highcatalytic efficiency related to the reaction mechanism was discussed based on density functional theory(DFT) and NMR techniques.