Directing nitrogen-doped carbon support chemistry for improved aqueous phase hydrogenation catalysis

Autor: Lina Rustam, Anna Fischer, Robin J. White, Ralf Thomann, Monika Bosilj, Julia Melke
Rok vydání: 2020
Předmět:
Zdroj: Catalysis Science & Technology. 10:4794-4808
ISSN: 2044-4761
2044-4753
Popis: Selective hydrogenations in the aqueous phase are an important transformation in the context of developing biorefinery concepts. In this report the application and optimisation of nitrogen-doped carbon (NDC) supported Pd nanoparticles as hydrogenation catalysts is discussed in the context of directing support (e.g. N) chemistry for improved catalytic performance in the aqueous phase. As a demonstrative example, the aqueous phase hydrogenation of phenol to cyclohexanone (e.g. a platform for polyamide production) is utilised. Catalyst supports were prepared based on an initial hydrothermal synthesis to yield NDC xerogels (from biomass precursors), the chemistry of which (e.g. functionality) was directed using a secondary thermal carbonisation (Tc) step at different temperatures (i.e. 350, 550, 750, 900 and 1000 °C). After Pd introduction, it was found that size, dispersion and electronic structure of the formed nanoparticles is affected by the surface chemistry of the NDC. This consequently led to higher turn-over frequency (TOF) and stability of the prepared catalysts compared to a “nitrogen-free” carbon supported Pd and a commercial, carbon supported Pd (Pd/AC) catalyst. Pd/NDC 900 (featuring predominantly quaternary and pyridinic N) catalysed the complete conversion of phenol at 99% selectivity to cyclohexanone, with excellent stability over 11 recycles and no discernible catalyst sintering or leaching (in contrast to the commercial catalyst). High catalytic stability, activity and selectivity make the Pd/NDC 900 catalyst highly applicable for aqueous phase hydrogenation reactions, whilst the general principle opens scope for support tailoring for application (e.g. biorefinery hydrogenations) and the development of structure/activity relationships.
Databáze: OpenAIRE