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
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…