Ostertag, L. M.; Utzig, T.; Klinger, C.; Valtiner, M.: Tether-Length Dependence of Bias in Equilibrium Free-Energy Estimates for Surface-to-Molecule Unbinding Experiments. Langmuir 34 (3), pp. 766 - 772 (2018)
Stock, P.; Utzig, T.; Valtiner, M.: Soft matter interactions at the molecular scale: interaction forces and energies between single hydrophobic model peptides. Physical Chemistry Chemical Physics 19 (6), pp. 4216 - 4221 (2017)
Utzig, T.; Stock, P.; Valtiner, M.: Resolving Non-Specific and Specific Adhesive Interactions of Catechols at Solid/Liquid Interfaces at the Molecular Scale. Angewandte Chemie International Edition in English 55, pp. 9524 - 9528 (2016)
Utzig, T.; Stock, P.; Valtiner, M.: Resolving Non-Specific and Specific Adhesive Interactions of Catechols at Solid/Liquid Interfaces at the Molecular Scale. Angewandte Chemie 128, pp. 9676 - 9680 (2016)
Utzig, T.; Stock, P.; Raman, S.; Valtiner, M.: Targeted Tuning of Interactive Forces by Engineering of Molecular Bonds in Series and Parallel Using Peptide-Based Adhesives. Langmuir 31 (40), pp. 11051 - 11057 (2015)
Stock, P.; Utzig, T.; Valtiner, M.: Direct and quantitative AFM measurements of the concentration and temperature dependence of the hydrophobic force law at nanoscopic contacts. Journal of Colloid and Interface Science 446, pp. 244 - 251 (2015)
Utzig, T.; Raman, S.; Valtiner, M.: Scaling from Single Molecule to Macroscopic Adhesion at Polymer/Metal Interfaces. Langmuir 31 (9), pp. 2722 - 2729 (2015)
Hu, Q.; Cheng, H.-W.; Stock, P.; Utzig, T.; Shrestha, B. R.; Valtiner, M.: Elucidating the structure of solid/electrolyte interfaces - Force probe experiments at hydrophilic, hydrophobic and electrified aqueous as well as ionic liquid|electrode interfaces. Bunsenmagazin 2, pp. 49 - 55 (2015)
Cheng, H.-W.; Utzig, T.; Valtiner, M.: Using a Surface-Forces-Apparatus to measure force distance profiles across confined ionic liquids. Application Note – Spectrographs (Andor) (2014)
Utzig, T.: A contribution to understanding interfacial adhesion based on molecular level knowledge. Dissertation, Fakultät für Maschinenbau, Ruhr-Universität Bochum, Bochum, Germany (2016)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…