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Computational Studies of Catalyzed Chemical Transformations of Biomass


EMSL Project ID
47800

Abstract

There is a critical need to develop new, renewable sources of energy as well as feedstocks for the chemical industry. Biomass is a carbon neutral source of energy and can also address issues related to the sustainability of petroleum-based resources. An issue with biomass is that it is heavily oxygenated (glucose = (C(H2O))6) and catalytic processes are needed to convert the oxygenated biomass into deoxygenated fuels and intermediates. We propose electronic structure theoretical studies of a variety of catalytic processes for the conversion of biomass intermediates to useful fuels and feedstocks. These processes are explicitly controlled by the intrinsic bonds that form between the reactants or intermediates and the active catalytic site as well as by the local nanoscale environment/interface about the site. Catalytic behavior is governed by the size and shape, interaction with the support, composition and atomic configuration for metal alloys and mixed metal oxides, and the influence of solvent. The potential role of an aqueous solvent is important for biomass conversions because of the source of the raw material. We propose to use advanced computational chemistry approaches implemented on EMSL's massively parallel computers to develop a quantitative description of catalytic processes for biomass conversion to develop new design criteria and new understanding of the physical phenomena that occur at different spatial and temporal scales that underlie the catalytic behavior. We will apply computational chemistry at the density functional theory (molecular and plane-wave) and correlated molecular orbital theory levels to study a range of catalytic processes including: acid-base (Bronsted and Lewis) and redox reactions representative of relevant biomass transformations (e.g. deoxygenation, hydrogenolysis, dehydration, and hydroalkylation) on polyoxometalates and (MO3)n (M= Group VIB) clusters of glycerol, levulinic acid, and gamma-valerolactone; polyol and ring-opening hydrogenolysis over bifunctional metal catalysts; formic acid decomposition on Au nanoparticles and bimetallic alloys; selective hydrogenation of lactic acid on Cu-based and Pt-based bimetallic alloys; aldol condensation over metal and metal oxide particles; and hydroalkylation of cyclohexanol in mesoporous zeolites for lignin conversion. A team of researchers from four universities and PNNL with direct ties to experimental efforts will address these problems using appropriate computational methods with the goal of understanding interfacial processes and advancing our ability to understand catalytic processes leading to the design of new catalysts. The proposed computational work is being done in close collaboration with experimental teams, a number of which use EMSL resources or are located in the EMSL.

Project Details

Project type
Large-Scale EMSL Research
Start Date
2013-10-01
End Date
2015-09-30
Status
Closed

Team

Principal Investigator

David Dixon
Institution
University of Alabama

Co-Investigator(s)

Matthew Neurock
Institution
University of Minnesota

Team Members

Benjamin Chen
Institution
University of Wisconsin, Madison

Sean Tacey
Institution
University of Wisconsin, Madison

Peng Bai
Institution
University of Minnesota

Jie Sun
Institution
Xiamen University

Xiuliang Sun
Institution
Beijing University of Chemical Technology

Ahmed Elnabawy
Institution
University of Wisconsin, Madison

Duygu Gerceker
Institution
University of Wisconsin, Madison

Qiuxia Cai
Institution
Zhejiang University of Technology

Srinivas Rangarajan
Institution
University of Wisconsin, Madison

Alyssa Hensley
Institution
Washington State University

Malsoon Lee
Institution
Pacific Northwest National Laboratory

Qiaohua Tan
Institution
University of Virginia

Joseph Marranca
Institution
University of Virginia

Thomas lawlor
Institution
University of Virginia

Mohammad Haider
Institution
Indian Institute of Technology Delhi

Erin Fitzharris
Institution
University of Virginia

Andrew Jones
Institution
University of California, Berkeley

William Knaeble
Institution
University of California, Berkeley

Lang Xu
Institution
University of Wisconsin, Madison

Shengjie Zhang
Institution
University of Alabama

K. Sahan Thanthiriwatte
Institution
University of Alabama

Tanya Mikulas
Institution
University of Alabama

David Hibbitts
Institution
University of California, Berkeley

Luke Roling
Institution
University of Wisconsin, Madison

Anthony Plauck
Institution
University of Wisconsin, Madison

Prashant Deshlahra
Institution
Tufts University

Yanggang Wang
Institution
Pacific Northwest National Laboratory

Michele Stover
Institution
University of Alabama

Yeohoon Yoon
Institution
Pacific Northwest National Laboratory

Zongtang Fang
Institution
Idaho National Laboratory

Sha Li
Institution
University of Wisconsin, Madison

Yunhai Bai
Institution
University of Wisconsin, Madison

Qiang Qian
Institution
University of Virginia

Bing Hao
Institution
University of Virginia

Rado Raharintsalama
Institution
University of Virginia

Suyash Singh
Institution
University of Wisconsin, Madison

Jessica Scaranto
Institution
University of Wisconsin, Madison

Ben Chen
Institution
National Cheng Kung University

Monica Vasiliu
Institution
University of Alabama

Amanda Stott
Institution
University of Alabama

Edward Garner
Institution
University of Alabama

Carrie Farberow
Institution
University of Wisconsin, Madison

Jeffrey Herron
Institution
University of Wisconsin, Madison

Guowen Peng
Institution
University of Wisconsin, Madison

Yu Cai
Institution
University of Virginia

Roger Rousseau
Institution
Pacific Northwest National Laboratory

Craig Plaisance
Institution
University of Virginia

Corneliu Buda
Institution
University of Virginia

Donghai Mei
Institution
Tiangong University

Peter Ferrin
Institution
University of Wisconsin, Madison

Emmanouil Mavrikakis
Institution
University of Wisconsin, Madison

Enrique Iglesia
Institution
University of California, Berkeley

Related Publications

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Chen M, and DA Dixon. 2013. "Tree Growth?Hybrid Genetic Algorithm for Predicting the Structure of Small (TiO2)n, n = 2?13, Nanoclusters." Journal of Chemical Theory and Computation 9(7):3189–3200. doi:10.1021/ct400105c
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