Abstract
Transition-metal phosphides (TMPs) are promising materials for biomass conversion processes, where their metal-acid bifunctionality provides active sites for the necessary variety of catalytic reactions (e.g., hydrogenation, hydrogenolysis, decarbonylation, and dehydration). Aiming to understand the catalytic performance of ternary TMP catalysts for the hydrodeoxygenation (HDO) reaction of biomass-derived oxygenates, a synthetic protocol was developed herein to prepare a series of ternary Ni2−xRhxP nanoparticles (NPs), incorporating Rh into a parent Ni2P template. This solution synthesis method allowed for a series of NPs to be prepared having precisely controlled compositions with similar morphology and crystalline structure. Detailed characterization of this series of Ni2−xRhxP (x ≤ 1) NPs revealed that Rh substituted into the parent hexagonal crystal lattice of Ni2P with concomitant expansion of the lattice. The influence of composition on the catalytic performance of silica-supported Ni2−xRhxP (x = 0 to 0.8, and cubic Rh2P) NPs was investigated through the HDO reaction of m-cresol. Whereas Rh2P was more selective for direct deoxygenation relative to Ni2P, increasing concentrations of Rh in Ni2−xRhxP resulted in a decreased selectivity to direct deoxygenation products (i.e., toluene, benzene, xylene), and an associated increased selectivity to hydrogenation products (i.e., methylcyclohexene). Through in situ high energy X-ray diffraction and density functional theory modeling, we identified OH* adsorption energy and surface-P sp-band center as effective descriptors for the observed shift in selectivities across this series of TMPs. Furthermore, the calculated electronic-structure changes were found to exert greater influence over the observed product selectivity than the subtle geometric changes associated with lattice expansion. Identification of this structure-function relationship demonstrates that the controlled synthesis of TMPs enables an understanding of composition-dependent selectivity for the HDO reaction of phenolic molecules and this approach could be extended to other ternary TMP compositions for diverse catalytic applications.
| Original language | English |
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| Pages (from-to) | 16788-16802 |
| Number of pages | 15 |
| Journal | Journal of Materials Chemistry A |
| Volume | 11 |
| Issue number | 31 |
| DOIs | |
| State | Published - Jul 26 2023 |
Funding
This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, and in part by Oak Ridge National Laboratory, operated by UT-Battelle, LLC, for the U.S. Department of Energy (DOE) under Contract no. DE-AC36-08GO28308 and DE-AC05-00OR22725, respectively. Funding provided by the U.S. DOE Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office in collaboration with the Chemical Catalysis for Bioenergy (ChemCatBio) Consortium, a member of the Energy Materials Network (EMN). In situ HE-XRD experiments were performed at the 6-ID-D beamline of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated by Argonne National Laboratory under Contract no. DE-AC02-06CH11357. M. Z. acknowledges scholarship support from the UNSW Scientia PhD Scholarship scheme. We would like to thank Doug Robinson for assistance at 6-ID-D and Yang Ren for providing the capillary furnace cell for HE-XRD measurements, as well as Evan C. Wegener for contributions in understanding the initial material structures using X-ray absorption spectroscopy. We would also like to thank Elisa M. Miller for X-ray photoelectron spectroscopy and helpful discussions. The microscopy was performed as part of a user project at the Center for Nanophase Materials Sciences (CNMS), which is a U.S. DOE Office of Science User Facility. The authors thank Kimberley S. Reeves for assistance with TEM sample preparation. A portion of the research was performed using computational resources sponsored by the U.S. DOE Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. This work also used computational resources at the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. The authors thank Vassili Vorotnikov for collaboration on initial computational models.