Highly selective hydrogenation of phenol to cyclohexanol over MOF-derived non-noble Co-Ni@NC catalysts

The selective hydrogenation of phenol is an attractive routine to produce cyclohexanol that is an important basic chemical raw in chemical industry, but the design of cost-efficient and highly selective catalysts remains a great challenge. Herein, we report the first example of non-noble bimetallic nanocatalysts for the selective hydrogenation of phenol with cyclohexanol as the sole product. These catalysts consisting of bimetallic Ni-Co alloy nanoparticles (NPs) encapsulated in N-doped carbon matrix were simply synthesized by using our previously developed MOF-templated strategy (Long et al., 2016). The sum of characterization results revealed that the Co and Ni elements were successfully alloyed in every individual NPs that were confined by N-doped carbon layers. Detailed catalytic test results suggested that both the pyrolysis temperature and the composition of these alloy NPs played the key roles in guiding their catalytic performance in the selective hydrogenation of phenol. It has been shown that Co-Ni@NC system was much more effective for hydrogenation of phenol than Cu@NC, Co-Cu@NC and Ni-Cu@NC systems. The optimal 1Co-1Ni@NC could completely catalyze the hydrogenation of phenol to > 99.9% cyclohexanol with a TOF of 0.21 h(-1), which was approximately 2.8- and 4.3-fold higher than that of the Co@NC and Ni@NC respectively, underscoring a strong positive synergistic effect between Ni and Co for this reaction. The mechanism study revealed the cyclohexanol was formed directly by the one-step hydrogenation of phenol in our catalyst system. This one-step pathway could avoid the formation of other hydrogenated intermediate product thereby leading to > 99.9% selectivity of cyclohexanol. Furthermore, this catalyst also showed good recyclability, magnetically reusability and general applicability for a wide range of phenol substrates, which together with the superior activity and selectivity make it a good potential for the industrial applications. (C) 2017 Elsevier Ltd. All rights reserved.