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)
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)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…