SPARK G45 (Floyd 224 in Tri-Cities)
Monday, 2/24, 4:10 – 5:00 pm

Presented by Dr. Graeme Henkelman, Department of Chemistry and Biochemistry, University of Texas at Austin

Sponsored by Chemical Engineering and Bioengineering, Chemistry, and CIRC

Graeme Henkelman is a professor of chemistry at the University of Texas at Austin. He did his undergraduate
work in physics at Queen’s University in Canada, a PhD in chemistry at the University of Washington, and a
postdoc at Los Alamos National Lab before starting at UT over ten years ago. His research group has focused
on computational methods for modeling reaction dynamics over experimental time scales. These methods are
applied to the challenge of developing new materials for energy applications including catalysts and batteries.

Correlating Structure and Function for Nanoparticle Catalysts

Metal nanoparticles of only 100-200 atoms are synthesized using a dendrimer encapsulation technique to
facilitate a direct comparison with density functional theory (DFT) calculations in terms of both structure and
catalytic function. Structural characterization is done using electron microscopy, x-ray scattering, and
electrochemical methods. Combining these tools with DFT calculations is found to improve the quality of the
structural models. DFT is also successfully used to predict trends between structure and composition of the
nanoparticles and their catalytic function for reactions including the reduction of oxygen and selective
hydrogenation. This investigation demonstrates some remarkable properties of the nanoparticles, including
facile structural rearrangements and nanoscale tuning parameters which can be used to optimize catalytic rates.
In this presentation I will focus on a pair of random alloy bimetallic nanoparticles which have complete
different trends in hydrogenation activity as a function of composition. Pd/Au is found to be tunable as a
function of composition whereas Pt/Au is not. The reason behind these different behaviors will be discussed.