Research Interest 1:
Unravel the key catalytic effects and limitations on material surfaces
Transition metal oxide (TMO) catalysts: TMO catalysts are found generally to be less active than Pt-group metals in oxygen reduction reaction (ORR). Using microkinetic modeling and ab initio calculations, we successfully identified two key reasons why it is difficult to find TMOs with a high ORR activity.1 The first reason is that TMO surfaces consistently bind oxygen atoms weaker than transition metals. This makes O-O bond breaking rate-determining in a number of cases, and limits the catalytic activity relative to metals. The second reason is that electric field effects are stronger at TMO surfaces, further making O-O bond breaking difficult, in particular under acidic conditions. To validate the predictions and ascertain their generalizability for complex TMOs, we report the largest experimental ORR catalyst screening campaign reported to date, yielding activity metrics for 7798 unique TMO compositions that generally exhibit activity well below that of Pt. This work is recently published in Nature Catalysis [1].
Alloy catalysts: Alloying the elements with strong and weak adsorption properties can produce a catalyst with optimally tuned adsorbate binding. A full understanding of alloying effects, however, was not well-established. In our work, we disentangled the ensemble, ligand, and strain effects of close-packed surfaces alloyed by transition metals with a combination of strong and weak adsorption properties, using ab initio calculations. We discovered the tunability of adsorbate binding energies as a function of lattice constant (strain effect), number of alloy-substituted sublayers (ligand effect), and randomly alloyed geometries (ensemble effect) on a large number of bimetallic alloy catalysts. We found that on these alloyed surfaces, the ensemble effect more significantly tunes the adsorbate binding as compared to the ligand and strain effects, with the binding energies predominantly determined by the local adsorption environment provided by the specific triatomic ensemble on the (111) surface. This work provides predictive guidelines for the rational design of alloy catalysts and has been successfully verified by a number of subsequent experiments by our groups and others. We also developed an online alloy database for oxygen reduction and hydrogen evolution catalysts: http://fri.oden.utexas.edu/~fri/fridb/server.py. The most representative publication is shown in Ref. 2, which has been cited > 150 times since 2019.
Representative Publications:
(1) H. Li, S. Kelly, D. Guevarrac, Z. Wang, Y. Wang, J. A. Haber, M. Anand, G. Gunasooriya, C. S. Abraham, S. Vijay, J. M. Gregoire, and J. K. Nørskov. "Analysis of the Limitations in the Oxygen Reduction Activity of Transition Metal Oxide Surfaces", Nature Catalysis, 2021, 4, 463.
(2) H. Li, K. Shin, and G. Henkelman. "Effects of Ensembles, Ligand, and Strain on Adsorbate Binding to Alloy Surfaces", Journal of Chemical Physics, 2018, 149, 174705 (Editor’s Pick; ESI Highly Cited Paper; 2018-2019 The Most Cited Paper in JCP).
Unravel the key catalytic effects and limitations on material surfaces
Transition metal oxide (TMO) catalysts: TMO catalysts are found generally to be less active than Pt-group metals in oxygen reduction reaction (ORR). Using microkinetic modeling and ab initio calculations, we successfully identified two key reasons why it is difficult to find TMOs with a high ORR activity.1 The first reason is that TMO surfaces consistently bind oxygen atoms weaker than transition metals. This makes O-O bond breaking rate-determining in a number of cases, and limits the catalytic activity relative to metals. The second reason is that electric field effects are stronger at TMO surfaces, further making O-O bond breaking difficult, in particular under acidic conditions. To validate the predictions and ascertain their generalizability for complex TMOs, we report the largest experimental ORR catalyst screening campaign reported to date, yielding activity metrics for 7798 unique TMO compositions that generally exhibit activity well below that of Pt. This work is recently published in Nature Catalysis [1].
Alloy catalysts: Alloying the elements with strong and weak adsorption properties can produce a catalyst with optimally tuned adsorbate binding. A full understanding of alloying effects, however, was not well-established. In our work, we disentangled the ensemble, ligand, and strain effects of close-packed surfaces alloyed by transition metals with a combination of strong and weak adsorption properties, using ab initio calculations. We discovered the tunability of adsorbate binding energies as a function of lattice constant (strain effect), number of alloy-substituted sublayers (ligand effect), and randomly alloyed geometries (ensemble effect) on a large number of bimetallic alloy catalysts. We found that on these alloyed surfaces, the ensemble effect more significantly tunes the adsorbate binding as compared to the ligand and strain effects, with the binding energies predominantly determined by the local adsorption environment provided by the specific triatomic ensemble on the (111) surface. This work provides predictive guidelines for the rational design of alloy catalysts and has been successfully verified by a number of subsequent experiments by our groups and others. We also developed an online alloy database for oxygen reduction and hydrogen evolution catalysts: http://fri.oden.utexas.edu/~fri/fridb/server.py. The most representative publication is shown in Ref. 2, which has been cited > 150 times since 2019.
Representative Publications:
(1) H. Li, S. Kelly, D. Guevarrac, Z. Wang, Y. Wang, J. A. Haber, M. Anand, G. Gunasooriya, C. S. Abraham, S. Vijay, J. M. Gregoire, and J. K. Nørskov. "Analysis of the Limitations in the Oxygen Reduction Activity of Transition Metal Oxide Surfaces", Nature Catalysis, 2021, 4, 463.
(2) H. Li, K. Shin, and G. Henkelman. "Effects of Ensembles, Ligand, and Strain on Adsorbate Binding to Alloy Surfaces", Journal of Chemical Physics, 2018, 149, 174705 (Editor’s Pick; ESI Highly Cited Paper; 2018-2019 The Most Cited Paper in JCP).