Glycerol decomposition via a combination of dehydrogenation, C–C bond scission, and C–O bond scission reactions is examined on Pt(111) with periodic Density Functional Theory (DFT) calculations. Building upon a previous study focused on C–C bond scission in glycerol, the current work presents a first analysis of the competition between C–O and C–C bond cleavage in this reaction network. The thermochemistry of various species produced from C–O bond breaking in glycerol dehydrogenation intermediates is estimated using an extension of a previously introduced empirical correlation scheme, with parameters fit to DFT calculations. Brønsted–Evans–Polanyi (BEP) relationships are then used to estimate the kinetics of C–O bond breaking. When combined with the previous results, the thermochemical and kinetic analyses imply that, while C–O bond scission may be competitive with C–C bond scission during the early stages of glycerol dehydrogenation, the overall rates are likely to be very low. Later in the dehydrogenation process, where rates will be much higher, transition states for C–C bond scission involving decarbonylation are much lower in energy than are the corresponding transition states for C–O bond breaking, implying that the selectivity for C–C scission will be high for glycerol decomposition on smooth platinum surfaces. It is anticipated that the correlation schemes described in this work will provide an efficient strategy for estimating thermochemical and kinetic energetics for a variety of elementary bond breaking processes on Pt(111) and may ultimately facilitate computational catalyst design for these and related catalytic processes.
Density functional theory Scaling relationships Biomass Glycerol Hydrogen production Pt(111) Selectivity Reforming
This study was supported as part of the Institute for Atom-efficient Chemical Transformations (IACT), an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences. Use of the Center for Nanoscale Materials (CNM) is supported by the Office of Science of the US Department of Energy under contract no. DE-AC02-06CH11357. We acknowledge grants of computer time from EMSL, a national scientific user facility located at Pacific Northwest National Laboratory, and the Argonne Laboratory Computing Resource Center (LCRC). This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.