424087 Fast Estimation Methods of Catalytic Cycles of Lignin Molecules on Pt(111)

Tuesday, November 10, 2015: 9:30 AM
355B (Salt Palace Convention Center)
Geun Ho Gu, Chemical Engineering, University of Delaware, Newark, DE and Dionisios G. Vlachos, Catalysis Center for Energy Innovation, Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE

AICHE National Meeting 2015

Fast Estimation Methods of Catalytic Cycles of Lignin Molecules on Pt(111)

Geun Ho Gu and Dionisios G. Vlachos


Biomass utilization could play an important role in a green energy future as a renewable source of carbon. Fast pyrolysis converts biomass into a “bio-oil” that cannot be used due to instability caused by its high oxygen content. Oxygen can be removed as water using heterogeneously catalyzed hydrodeoxygenation (HDO). However, understanding the underlying mechanism of HDO is a challenge. The bio-oil mixture involves a large number of intermediates, and density functional theory (DFT) is too expensive to compute surface thermochemical properties for all intermediates. To more efficiently compute these properties, we develop a group additivity scheme for intermediates involved in HDO of lignin molecules on Pt(111). Pt has shown to be the very active for HDO of lignin model compounds.1-4 Understanding Pt’s activation mechanism may give us insights into more efficient and cheaper catalysts.

To build the group additivity scheme that encompasses all the relevant groups for HDO of the complex lignin reaction network, we use the RING software5 to enumerate the reaction intermediates and account for all the important unique groups. Then, the thermochemical properties of a regression set are computed using DFT. The group additivity scheme has been improved in several ways from the previous schemes for enhanced predictability6,7, including: (1) regression of gas groups; (2) accounting of a C(=M) type group; and (3) differentiation between the groups close and far from the surface to account for dispersion. Each of these improvements reduced the mean and max absolute error of DGf,298 from 6.9 and 26.8 kcal/mol to (1) 4.2 and 20.8 kcal/mol, (2) 3.4 and 14.6 kcal/mol, and (3) 3.3 and 13.5 kcal/mol, respectively. The improved group additivity scheme is used in combination with Brønsted-Evans-Polyani (BEP) relationsand the energy span model to calculate the turnover frequency (TOF) of major products and identify the rate limiting steps of various lignin compounds, such as guaiacol, on Pt(111). Comparison to experimental data is also made.

(1)        Wan, H. J. et al. Top Catal 2012, 55, 129.

(2)        Foster, A. et al. Top Catal 2012, 55, 118.

(3)        Nie, L. et al. Journal of Catalysis 2014, 317, 22.

(4)        Runnebaum, R. C. et al. Catalysis Science & Technology 2012, 2, 113.

(5)        Rangarajan, S. et al. Computers & Chemical Engineering 2012, 46, 141.

(6)        Vorotnikov, V. et al. Ind. Eng. Chem. Res. 2014.

(7)        Salciccioli, M. et al. The Journal of Physical Chemistry C 2012, 116, 1873.

(8)        Lee, K. et al. ChemSusChem 2015, 8, 315.

Extended Abstract: File Not Uploaded
See more of this Session: Computational Catalysis I
See more of this Group/Topical: Catalysis and Reaction Engineering Division