Catalytic hydrogenolysis over Cu-based oxide derived from hydrotalcite-like structured materials: Reaction condition optimization and artificial neural network modelling

Abstract

In this study, the catalytic activity of Cu-derived oxide catalysts in glycerol hydrogenolysis was investigated and the effect on the selectivity of 1,2-propanediol (1,2-PDO) with the different Cu/Al molar ratios was observed. The glycerol conversion/1,2-PDO selectivity was found to be dependent on the metallic sites and surface acidity of the Cu-based catalyst. The surface acidity and metallic sites of Cu nanoparticles were significantly improved with the increase of Cu/Al mole fraction in the catalyst. The efficiency of the Cu-derived oxide catalyst was attributed to the well-dispersed Cu and the presence of acidic sites. As expected, the Cu-based oxide catalyst (3CuAl) showed remarkable catalytic performance for 1,2-PDO synthesis with the highest turnover frequency (TOF) from the hydrogenolysis reaction. It is observed that the Cu-derived oxide catalyst is stable and efficient under strident reaction conditions in the presence of water and high temperature (aqueous glycerol solution (20 wt%), 210 °C, 40 bar). Moreover, the reaction conditions for glycerol hydrogenolysis in the presence of active 3CuAl were optimized to maximize the selectivity of 1,2-PDO with TOF. In addition, overcoming the limitation due to the external mass transfer resistance was investigated. The rate of glycerol consumption was subjected to kinetic analysis, which revealed a zero-order relationship on glycerol concentration, indicating that adsorbed glycerol was the most tightly bonded organic adsorbate. Further, the experimental reaction data was validated through the developed artificial neural network (ANN) model.