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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
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.