Dr. Szilvási is an Assistant Professor in the Department of Chemical and Biological Engineering within the College of Engineering. His main motivation is to expedite the discovery of new molecules and materials using computational methods and potentially save millions of dollars and years of tedious experimental efforts. He loves the versatility of his projects that can always take a new unexpected turn; for example most recently in the direction of detecting airborne pathogens. Currently, two NSF EFRI awards support Dr. Szilvási’s group (http://che.eng.ua.edu/people/tibor-szilvasi/).

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Representative Publications

1. Demonstrating the Direct Relationship between Hydrogen Evolution Reaction and Catalyst Deactivation in Synthetic Fe Nitrogenases, Z. Benedek, M. Papp, J. Oláh, T. Szilvási. ACS Catalysis, 10: 12555, 2020.
2. A Bis(silylene)-Stabilized Diphosphorus Compound and Its Reactivity as a Monophosphorus Anion Transfer Reagent, Y. Wang, T. Szilvási, S. Yao, M. Driess. Nature Chemistry, 12: 801, 2020.
3. Design of Chemoresponsive Liquid Crystals through Integration of Computational Chemistry and Experimental Studies, T. Szilvási, L. T. Roling, H. Yu, P. Rai, S. Choi, R. J. Twieg, M. Mavrikakis, N. L. Abbott. Chemistry of Materials, 29: 3563, 2017.
4. Direct Time-domain Observation of Attosecond Final-state Lifetimes in Photoemission from Solids, Z. Tao, C. Chen, T. Szilvási, M. Keller, M. Mavrikakis, H. Kapteyn, M. Murnane. Science, 353: 62, 2016.
5. Internal Catalytic Effect of Bulky NHC Groups in Suzuki-Miyaura Cross-coupling Reaction, T. Szilvási, T. Veszprémi. ACS Catalysis, 3: 1984, 2013

Research Interests

Dr. Szilvási’s research group aims to focus on engineering interfaces and molecular materials. Specifically, the group is currently working on (i) optimizing catalytic reactions and catalyst materials, (ii) identifying functional materials for soft matter applications, and (iii) designing complex interfaces for energy and sensor applications. To achieve these goals, the group also develops computational methods and protocols that can provide more accurate predictions for molecule and material design.