Scientific Events

The development and improvement of catalysts for chemical energy conversion, such as (photo-)electrocatalytic water splitting or alcohol oxidation, requires mechanistic understanding at theatomic/molecular level. In my talk I will address several examples for the application of densityfunctional theory calculations to model, understand and tailor the catalytic activity of anodematerials for water splitting. To disentangle the role of structural motifs, crystallographic orientationand dopants, I will focus on iron and cobalt containing transition metal oxides with spinel [1-3],corundum [4] vs. perovskite [5] structure. The aim is to establish a link between the energetic trendsand the underlying structural and electronic properties and to identify potential active sites. Afurther topic is the reduction of iron oxide surfaces and bulk via hydrogen adsorption [6] andincorporation.Funding by the German Research Foundation DFT within SPP 1613 and CRC TRR247 as well ascomputational time at the Leibniz Rechenzentrum and the supercomputer MagnitUDE at UDE isgratefully acknowledged.[1] K. Chakrapani, G. Bendt, H. Hajiyani, I. Schwarzrock, T. Lunkenbein, S. Salamon, J. Landers, H.Wende, R. Schlögl, R. Pentcheva, M. Behrens, S. Schulz, ChemCatChem. 9, 2988-2995, (2017)[2] H. Hajiyani, R. Pentcheva, ACS Catal. 8, 11773-11782 (2018)[3] Y. Peng, H. Hajiyani, R. Pentcheva, ACS Catal. 11, 5601–5613, (2021)[4] A.G. Hufnagel, H. Hajiyani, S. Zhang, T. Li, O. Kasian, B. Gault, B. Breitbach, T. Bein, D. Fattakhova-Rohlfing, C. Scheu, R. Pentcheva, Adv. Funct. Mater., 165, 1804472 (2018)[5] A. Füngerlings, A. Koul, M. Dreyer, A. Rabe, D. M. Morales, W. Schuhmann, M. Behrens, and R.Pentcheva, Chemistry - A European Journal, accepted.[6] G. S. Parkinson, N. Mulakaluri, Y. Losovyj, P. Jacobson, R. Pentcheva, and U. Diebold, Phys. Rev. B82, 125413 (2010).

Engineered systems are an indispensable part of our modern life with far-reaching applications that include aerial and ground transportation, electronics, large-scale structures, and medicine. The ever-evolving societal, environmental, and cultural awareness calls for significantly complex systems with unprecedented properties that reliably meet stakeholders’ demands under extreme conditions. To accelerate the design and deployment of such systems while reducing the reliance on costly and time-consuming experiments, it is necessary to develop advanced computational methods that streamline their design and analysis process. In this talk, I will present some of our recent works for solving challenging problems in engineering design, solid mechanics, and fluid dynamics. In particular, I will demonstrate how we can (1) accelerate multiscale simulations of casting materials ten times via mechanistic reduced order models, (2) surrogate plastic and history dependent deformation of fiber composites with deep learning, (3) optimize material composition with latent map Gaussian processes and Bayesian optimization, and (4) solve partial differential equations with transfer learning. [more]