MRS Meetings and Events

 

MD02.07.04 2023 MRS Spring Meeting

Insight into the Reactivity of Electrocatalytic Glycerol Oxidation—The Strength of the Hydroxyl Group Bonding on Surface

When and Where

Apr 13, 2023
5:00pm - 7:00pm

Moscone West, Level 1, Exhibit Hall

Presenter

Co-Author(s)

Minseon Park1,Jeemin Hwang2,Song Jin3,4,Daehee Jang1,Hyung Ju Kim5,Won Bae Kim1,Min Ho Seo6

Postech1,Korea Instutitute of Energy Research2,Gwangju Institute of Science and Technology3,Korea Institute of Materials Science4,Korea institute of Chemical Technology5,Pukyong National University6

Abstract

Minseon Park1,Jeemin Hwang2,Song Jin3,4,Daehee Jang1,Hyung Ju Kim5,Won Bae Kim1,Min Ho Seo6

Postech1,Korea Instutitute of Energy Research2,Gwangju Institute of Science and Technology3,Korea Institute of Materials Science4,Korea institute of Chemical Technology5,Pukyong National University6
Glycerol is a main byproduct originating from the transesterification process of vegetable oils and animal fat into biodiesel. The production of glycerol byproduct has become greater than the demand as the biodiesel production has increased. Its oversupply has significantly lowered the market price. Therefore, research on electrocatalytic glycerol oxidation reaction (EGOR) has been highlighted recently since it can generate both electricity and valuable chemicals. Glycerol can be used not only as fuel in direct alcohol fuel cells but also as reactants to produce valuable chemicals like dihydroxyacetone, glyceric acid, glycolic acid, and formic acid. However, it is not fully unknown for the reaction pathway on various catalysts due to the complexity of reaction intermediates. Most of the research focused on finding the mechanism for which desired target substance is produced. However, this work is done to comprehend a key mechanism that not only determines glycerol oxidation having various pathways but also might relate to the selectivity of each intermediate in oxidizing process. What to find the main descriptor that affects the glycerol electro-oxidation would be worthy for further design of the electrocatalyst. Combination studies of <i>ab-initio</i> computations and experiments to find the represent descriptor that affect the glycerol electro-oxidation was performed. The adsorption energies of OH and hydroxyl group in the glycerol at the catalyst surface were compared with calculating binding energies and a crystal orbital Hamilton population (COHP) analysis. As a result, the binding energy of OH and that between the hydroxyl group in glycerol and the catalyst surface were proposed as key descriptors to control the glycerol oxidation reaction in PtCu surface model. Both OH and hydroxyl group of the glycerol molecule were most strongly bound on the PtCu<sub>3</sub> surface. The alloy catalyst of Pt and Cu supported on porous carbon was used to support this data. (Pt/PC, Pt<sub>3</sub>Cu/PC, PtCu/PC, and PtCu<sub>3</sub>/PC) The mass activity of the glycerol oxidation experiment showed the same tendency as the result of the calculation, that the PtCu<sub>3</sub>/PC sample showed the highest mass activity among other catalysts. Therefore, the stronger OH binds on the surface, the higher the reactivity of the glycerol oxidation. This study identified that the binding energy of OH on the catalyst surface is the key descriptor in the glycerol oxidation reaction. This is expected to be helpful in predicting and analyzing the reactivity of glycerol as well as various alcohol-based molecules. This research will pave the way for the design and development of future catalysts to produce value-added chemicals for electrocatalytic glycerol conversion reactions.

Keywords

alloy

Symposium Organizers

Soumendu Bagchi, Los Alamos National Laboratory
Huck Beng Chew, The University of Illinois at Urbana-Champaign
Haoran Wang, Utah State University
Jiaxin Zhang, Oak Ridge National Laboratory

Symposium Support

Bronze
Patterns and Matter, Cell Press

Session Chairs

Soumendu Bagchi
Haoran Wang

In this Session

MD02.07.01
Automated Defect Analysis of CdSe Nanoparticles through Supervised Learning with Large Simulated Databases

MD02.07.02
STEM Image Analysis Based on Deep Learning—Identification of Vacancy of Defects and Polymorphs of MoS2

MD02.07.03
Beyond Single Molecules: Intermolecular Interference Effects

MD02.07.04
Insight into the Reactivity of Electrocatalytic Glycerol Oxidation—The Strength of the Hydroxyl Group Bonding on Surface

MD02.07.05
Ripplocation Boundaries and Kink Boundaries in Layered Solids

MD02.07.06
Data-Driven Electrode Optimization for Vanadium Redox Flow Battery by Reduced Order Model

MD02.07.07
Application of Baysian Super Resolution to Spectroscopic Data Analysis

MD02.07.08
A Workflow to Track Time-Resolved Dislocation Behavior in High Temperature Aluminum

MD02.07.09
Investigation of Solidification in Supercooled Water Drops using Large Data Sets of Synchronized Optical Images and X-ray Diffraction Patterns

MD02.07.10
Characterizing Dislocations by formulating the Invisibility Criterion for DFXM

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