Suchergebnisse

Lee, Y.: Discoveries in Ruthenium Oxide-Based Catalysts: From Morphology Control for Water Electrolysis to Surface Structure Determination via Machine-Learning. Dissertation, Technische Universität, München (2022)

Xu, W.: Tailoring complexity for catalyst discovery using physically motivated machine learning. Dissertation, Technische Universität, München (2022)

Dragoumi, M.: Quasiparticle energies from second-order perturbation theory. Dissertation, Freie Universität, Berlin (2022)

Staacke, C.: The Electrostatic Gap: Combining Electrostatic Models with Machine Learning Potentials. Dissertation, Technische Universität, München (2022)

Malerz, S.: Advances in Liquid-Jet Photoelectron Spectroscopy: Determination of Absolute Energetics and Probing Chirality in Solution. Dissertation, Freie Universität, Berlin (2022)

Bellini, G.: Towards the implementation of fundamental knowledge in oxidation catalysis: perovskites as dataset for artificial intelligence analysis. Dissertation, Technische Universität, Berlin (2022)

Stegmaier, S.: Working Interfaces in Solid-State Electrolytes: A Theoretical Approach towards Realistic Models. Dissertation, Technische Universität, München (2022)

Felsen, F.: Optimal experimental designs for the exploration of reaction kinetic phase diagrams. Dissertation, Technische Universität, München (2022)

Stocker, S.: Transferability in chemical machine learning. Dissertation, Technische Universität, München (2022)

Wengert, S.: Kernel-based machine learning for molecular crystal structure prediction. Dissertation, Technische Universität, München (2022)

Regler, B.: Systematic identification of relevant features for the statistical modeling of materials properties of crystalline solids. Dissertation, Freie Universität, Berlin (2022)

Erdem, E.: The impact of alkali-vanadate(s) in supported vanadia catalysts on the propane oxidation reaction. Dissertation, Technische Universität, Berlin (2022)

Leitherer, A.: Robust recognition and exploratory analysis of crystal structures using machine learning. Dissertation, Humboldt Universität, Berlin (2022)

Zahn, D.: Ultrafast lattice dynamics and microscopic energy flow in ferromagnetic metals and in an anisotropic layered semiconductor. Dissertation, Freie Universität, Berlin (2022)

Timmermann, J.: Iridiumoxid as catalyst in water electrolysis: identification of novel surface structures via machine learning. Dissertation, Technische Universität, München (2022)

Ahmetcik, E.: Artificial intelligence for crystal structure prediction. Dissertation, Technische Universität, Berlin (2022)

Grabarics, M.: Glycan analysis using mass spectrometry-based techniques. Dissertation, Freie Universität, Berlin (2022)

Grosu, C.: Capturing ion dynamics in lithium intercalated graphite: bridging the gap between experiment and theory through advanced nuclear magnetic resonance and multiscale modeling. Dissertation, Technische Universität, München (2022)

Knoop, F.: Heat transport in strongly anharmonic solids from first principles. Dissertation, Humboldt-Universität zu, Berlin (2022)

Yuan, Z.: Electrical conductivity from first principles. Dissertation, Humboldt-Universität zu, Berlin (2022)