Publications of the Theory department

2020 - 2022

Journal Article (42)

2022
Journal Article
Ahsan, M.A., T. He, J.C. Noveron, K. Reuter, A.R. Puente-Santiago and R. Luque: Low-dimensional heterostructures for advanced electrocatalysis: an experimental and computational perspective. Chemical Society Reviews 51 (3), 812–828 (2022).
Journal Article
Bauer, M.N., M.I.J. Probert and C. Panosetti: Systematic Comparison of Genetic Algorithm and Basin Hopping Approaches to the Global Optimization of Si(111) Surface Reconstructions. The Journal of Physical Chemistry A 126 (19), 3043–3056 (2022).
Journal Article
Beinlich, S., N. Hörmann and K. Reuter: Field Effects at Protruding Defect Sites in Electrocatalysis at Metal Electrodes? ACS Catalysis 12 (10), 6143–6148 (2022).
Journal Article
Boix, V., W. Xu, G. D’Acunto, J. Stubbe, T. Gallo, M.D. Strømsheim, S. Zhu, M. Scardamaglia, A. Shavorskiy, K. Reuter, M. Andersen and J. Knudsen: Graphene as an Adsorption Template for Studying Double Bond Activation in Catalysis. The Journal of Physical Chemistry C 126 (33), 14116–14124 (2022).
Journal Article
Brösigke, G., J.-U. Repke, R. Schomäcker and S. Matera: The closer the better? Theoretical assessment of the impact of catalytic site separation for bifunctional core-shell catalyst particles. Chemical Engineering Journal 446 (1), 136891 (2022).
Journal Article
Chakraborty, A., T. Brumme, S. Schmahl, H. Weiske, C. Baldauf and K.R. Asmis: Impact of anion polarizability on ion pairing in microhydrated salt clusters. Chemical Science 13 (44), 13187–13200 (2022).
Journal Article
Chen, K., C. Kunkel, K. Reuter and J. Margraf: Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening. Digital Discovery 1 (2), 147–157 (2022).
Journal Article
Deimel, M., H. Prats, M. Seibt, K. Reuter and M. Andersen: Selectivity Trends and Role of Adsorbate-Adsorbate Interactions in CO Hydrogenation on Rhodium Catalysts. ACS Catalysis 12 (13), 7907–7917 (2022).
Journal Article
Dupuy, R., J. Filser, C. Richter, R. Seidel, F. Trinter, T. Buttersack, C. Nicolas, J. Bozek, U. Hergenhahn, H. Oberhofer, B. Winter, K. Reuter and H. Bluhm: Photoelectron angular distributions as sensitive probes of surfactant layer structure at the liquid-vapor interface. Physical Chemistry Chemical Physics 24 (8), 4796–4808 (2022).
Journal Article
Felsen, F., K. Reuter and C. Scheurer: A model-free sparse approximation approach to robust formal reaction kinetics. Chemical Engineering Journal 433 (1), 134121 (2022).
Journal Article
Filser, J., K. Reuter and H. Oberhofer: Piecewise Multipole-Expansion Implicit Solvation for Arbitrarily Shaped Molecular Solutes. Journal of Chemical Theory and Computation 18 (1), 461–478 (2022).
Journal Article
Gao, H., V. Belova, F. La Porta, J.S. Cingolani, M. Andersen, M. Saedi, O.V. Konovalov, M. Jankowski, H. Heenen, I.M.N. Groot, G. Renaud and K. Reuter: Graphene at Liquid Copper Catalysts: Atomic-Scale Agreement of Experimental and First-Principles Adsorption Height. Advanced Science 9 (36), 2204684 (2022).
Journal Article
Govindarajan, N., G. Kastlunger, H. Heenen and K. Chan: Improving the intrinsic activity of electrocatalysts for sustainable energy conversion: where are we and where can we go? Chemical Science 13 (1), 14–26 (2022).
Journal Article
He, T. and K.S. Exner: Computational electrochemistry focusing on nanostructured catalysts: challenges and opportunities. Materials Today Energy 28, 101083 (2022).
Journal Article
He, T., A.R. Puente-Santiago, S. Xia, M.A. Ahsan, G. Xu and R. Luque: Experimental and Theoretical Advances on Single Atom and Atomic Cluster-Decorated Low-Dimensional Platforms towards Superior Electrocatalysts. Advanced Energy Materials 12 (22), 2200493 (2022).
Journal Article
He, T., A.R.P. Santiago, Y. Kong, M.A. Ahsan, R. Luque, A. Du and H. Pan: Atomically Dispersed Heteronuclear Dual-Atom Catalysts: A New Rising Star in Atomic Catalysis. Small 18 (12), 2106091 (2022).
Journal Article
Heenen, H., H. Shin, G. Kastlunger, S. Overa, J.A. Gauthier, F. Jiao and K. Chan: The mechanism for acetate formation in electrochemical CO(2) reduction on Cu: selectivity with potential, pH, and nanostructuring. Energy & Environmental Science 15 (9), 3978–3990 (2022).
Journal Article
Hu, X., M.-O. Lenz and C. Baldauf: Better force fields start with better data: A data set of cation dipeptide interactions. Scientific Data 9, 327 (2022).
Journal Article
Keller, E., T. Tsatsoulis, K. Reuter and J. Margraf: Regularized second-order correlation methods for extended systems. The Journal of Chemical Physics 156 (2), 024106 (2022).
Journal Article
Kelly, S.R., H. Heenen, N. Govindarajan, K. Chan and J.K. Nørskov: OH Binding Energy as a Universal Descriptor of the Potential of Zero Charge on Transition Metal Surfaces br. The Journal of Physical Chemistry C 126 (12), 5521–5528 (2022).
Journal Article
Khare, R., R. Weindl, A. Jentys, K. Reuter, H. Shi and J.A. Lercher: Di- and Tetrameric Molybdenum Sulfide Clusters Activate and Stabilize Dihydrogen as Hydrides. JACS Au 2 (3), 613–622 (2022).
Journal Article
Kube, P., J. Dong, N. Sánchez Bastardo, H. Ruland, R. Schlögl, J. Margraf, K. Reuter and A. Trunschke: Green synthesis of propylene oxide directly from propane. Nature Communications 13, 7504 (2022).
Journal Article
Lee, Y., C. Scheurer and K. Reuter: Epitaxial Core-Shell Oxide Nanoparticles: First-Principles Evidence for Increased Activity and Stability of Rutile Catalysts for Acidic Oxygen Evolution. ChemSusChem 15 (10), e202200015 (2022).
Journal Article
Levin, N., J. Margraf, J. Lengyel, K. Reuter, M. Tschurl and U. Heiz: CO2-Activation by size-selected tantalum cluster cations (Ta1–16+): thermalization governing reaction selectivity. Physical Chemistry Chemical Physics 24 (4), 2623–2629 (2022).
Journal Article
Li, H. and K. Reuter: Ab Initio Thermodynamic Stability of Carbide Catalysts under Electrochemical Conditions. ACS Catalysis 12 (16), 10506–10513 (2022).
Journal Article
Li, M., M. Tang, H. Dai, T. He and Z. Wang: A binder-free, well-integrated metal–organic frameworks@polypyrrole nanofilm electrocatalyst for highly efficient and selective reduction of carbon dioxide. Materials Today Energy 30, 101140 (2022).
Journal Article
Margraf, J., Z.W. Ulissi, Y. Jung and K. Reuter: Heterogeneous Catalysis in Grammar School. The Journal of Physical Chemistry C 126 (6), 2931–2936 (2022).
Journal Article
Mei, J., J. Shang, T. He, D. Qi, L. Kou, T. Liao, A. Du and Z. Sun: 2D/2D Black Phosphorus/Nickel Hydroxide Heterostructures for Promoting Oxygen Evolution via Electronic Structure Modulation and Surface Reconstruction. Advanced Energy Materials 12 (25), 2201141 (2022).
Journal Article
Peng, J., D. Schwalbe-Koda, K. Akkiraju, T. Xie, L. Giordano, Y. Yu, C.J. Eom, J.R. Lunger, D.J. Zheng, R.R. Rao, S. Muy, J.C. Grossman, K. Reuter, R. Gómez-Bombarelli and Y. Shao-Horn: Human- and machine-centred designs of molecules and materials for sustainability and decarbonization. Nature Reviews Materials 7 (12), 991–1009 (2022).
Journal Article
Ringe, S., N. Hörmann, H. Oberhofer and K. Reuter: Implicit Solvation Methods for Catalysis at Electrified Interfaces. Chemical Reviews 122 (12), 10777–10820 (2022).
Journal Article
Schreck, S., E. Diesen, M. Dell’Angela, C. Liu, M. Weston, F. Capotondi, H. Ogasawara, J. LaRue, R. Costantini, M. Beye, P.S. Miedema, J.H. Stenlid, J. Gladh, B. Liu, H.-Y. Wang, F. Perakis, F. Cavalca, S. Koroidov, P. Amann, E. Pedersoli, D. Naumenko, I. Nikolov, L. Raimondi, F. Abild-Pedersen, T.F. Heinz, J. Voss, A.C. Luntz and A. Nilsson: Atom-Specific Probing of Electron Dynamics in an Atomic Adsorbate by Time-Resolved X-Ray Spectroscopy. Physical Review Letters 129 (27), 276001 (2022).
Journal Article
Shadravan, V., A. Cao, V.J. Bukas, M.K. Grønborg, C.D. Damsgaard, Z. Wang, J. Kibsgaard, J.K. Nørskov and I. Chorkendorff: Enhanced promotion of Ru-based ammonia catalysts by in situ dosing of Cs. Energy & Environmental Science 15 (8), 3310–3320 (2022).
Journal Article
Staacke, C., T. Huss, J. Margraf, K. Reuter and C. Scheurer: Tackling Structural Complexity in Li2 S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials. Nanomaterials 12 (17), 2950 (2022).
Journal Article
Staacke, C., S. Wengert, C. Kunkel, G. Csányi, K. Reuter and J. Margraf: Kernel charge equilibration: efficient and accurate prediction of molecular dipole moments with a machine-learning enhanced electron density model. Machine Learning: Science and Technology 3 (1), 015032 (2022).
Journal Article
Stegmaier, S., K. Reuter and C. Scheurer: Exploiting Nanoscale Complexion in LATP Solid-State Electrolyte via Interfacial Mg2+ Doping. Nanomaterials 12 (17), 2912 (2022).
Journal Article
Stocker, S., J. Gasteiger, F. Becker, S. Günnemann and J. Margraf: How robust are modern graph neural network potentials in long and hot molecular dynamics simulations? Machine Learning: Science and Technology 3 (4), 045010 (2022).
Journal Article
Türk, H., T. Götsch, F. Schmidt, A. Hammud, D. Ivanov, (B.de H. J. L. G., I.C. Vinke, R.-A. Eichel, R. Schlögl, K. Reuter, A. Knop-Gericke, T. Lunkenbein and C. Scheurer: Sr Surface Enrichment in Solid Oxide Cells – Approaching the Limits of EDX Analysis by Multivariate Statistical Analysis and Simulations. ChemCatChem 14 (19), e202200300 (2022).
Journal Article
Türk, H., E. Landini, C. Kunkel, J. Margraf and K. Reuter: Assessing Deep Generative Models in Chemical Composition Space. Chemistry of Materials 34 (21), 9455–9467 (2022).
Journal Article
Wan, H., A. Bagger and J. Rossmeisl: Limitations of Electrochemical Nitrogen Oxidation toward Nitrate. The Journal of Physical Chemistry Letters 13 (38), 8928–8934 (2022).
Journal Article
Wengert, S., G. Csányi, K. Reuter and J. Margraf: A Hybrid Machine Learning Approach for Structure Stability Prediction in Molecular Co-crystal Screenings. Journal of Chemical Theory and Computation 18 (7), 4586–4593 (2022).
Journal Article
Xu, W., K. Reuter and M. Andersen: Predicting binding motifs of complex adsorbates using machine learning with a physics-inspired graph representation. Nature Computational Science 2 (7), 443–450 (2022).
Journal Article
Zhang, D., H. Li, A. Riaz, A. Sharma, W. Liang, Y. Wang, H. Chen, K. Vora, D. Yan, Z. Su, A. Tricoli, C. Zhao, F.J. Beck, K. Reuter, K. Catchpole and S. Karuturi: Unconventional direct synthesis of Ni3N/Ni with N-vacancies for efficient and stable hydrogen evolution. Energy & Environmental Science 15 (1), 185–195 (2022).

Conference Paper (1)

2022
Conference Paper
Seiler, H., D. Zahn, M. Zacharias, P.-N. Hildebrandt, T. Vasileiadis, Y.W. Windsor, Y. Qi, C. Carbogno, D. Claudia, R. Ernstorfer and F. Caruso: Momentum-resolved non-radiative energy flow in photoexcited black phosphorus. In: Optics Infobase Conference Papers.in press

Thesis - PhD (9)

2022
Thesis - PhD
Döpking, S.: Error aware analysis of multi-scale reactivity models for chemical surface reactions. Freie Universität Berlin
Thesis - PhD
Felsen, F.: Optimal experimental designs for the exploration of reaction kinetic phase diagrams. Technische Universität München
Thesis - PhD
Grosu, C.: Capturing ion dynamics in lithium intercalated graphite: bridging the gap between experiment and theory through advanced nuclear magnetic resonance and multiscale modeling. Technische Universität München
Thesis - PhD
Lee, Y.: Discoveries in Ruthenium Oxide-Based Catalysts: From Morphology Control for Water Electrolysis to Surface Structure Determination via Machine-Learning. Technische Universität München
Thesis - PhD
Staacke, C.: The Electrostatic Gap: Combining Electrostatic Models with Machine Learning Potentials. Technische Universität München
Thesis - PhD
Stocker, S.: Transferability in chemical machine learning. Technische Universität München
Thesis - PhD
Timmermann, J.: Iridiumoxid as catalyst in water electrolysis: identification of novel surface structures via machine learning. Technische Universität München
Thesis - PhD
Wengert, S.: Kernel-based machine learning for molecular crystal structure prediction. Technische Universität München
Thesis - PhD
Xu, W.: Tailoring complexity for catalyst discovery using physically motivated machine learning. Technische Universität München

Thesis - Master (2)

2022
Thesis - Master
Huss, T.: Towards a universal machine learning interatomic potential for the xLi2S-(100 - x)P2S5 material class. Technische Universität München
Thesis - Master
König, P.: Generative Adversarial Networks (GANs) for inverse design of RuO2 surfaces. Technische Universität München
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