Torres, E.; Blumenau, A. T.; Biedermann, P. U.: Mechanism for phase transitions and vacancy island formation in alkylthiol/Au(111)self-assembled monolayers based on adatom and vacancy-induced reconstructions. Physical Review B 79 (7), pp. 075440-1 - 075440-6 (2009)
Pengel, S.; Niu, F.; Nayak, S.; Tecklenburg, S.; Chen, Y.-H.; Ebbinghaus, P.; Schulz, R.; Yang, L.; Biedermann, P. U.; Gygi, F.et al.; Schmid, R.; Galli, G.; Wippermann, S. M.; Erbe, A.: Oxygen reduction and water at the semiconductor/solution interface probed by stationary and time-resolved ATR-IR spectroscopy coupled to electrochemical experiments and DFT calculations. In: Program of the 8th International Conference on Advanced Vibrational Spectroscopy (ICAVS) – Oral Abstracts, pp. 130 - 131 (Eds. Lendl, B.; Koch, C.; Kraft, M.; Ofner, J.; Ramer, G.). 8th International Conference on Advanced Vibrational Spectroscopy (ICAVS), Vienna, Austria, July 12, 2015 - July 17, 2015. (2015)
Berezkin, A. V.; Biedermann, P. U.: Multiscale simulation of polyurethane network. World Polymer Congress 2012, Blacksburg, Virginia Tech, USA, June 24, 2012 - June 29, 2012. (2012)
Berezkin, A. V.; Biedermann, P. U.; Auer, A. A.: Mesoscale simulation of network formation and structure, combining molecular dynamics and kinetic Monte Carlo approaches. European Polymer Congress 2011, Granada, Spain, June 26, 2011 - July 01, 2011. (2011)
Kenmoe, S.; Biedermann, P. U.: Water adsorption on non polar ZnO surfaces: from single molecules to multilayers. In APS March Meeting 2015, abstract #G8.011. APS March Meeting 2015 , San Antonio, TX, USA, March 02, 2015 - March 06, 2015. (2015)
Kenmoe, S.; Biedermann, P. U.: Water adsorption on non polar ZnO surfaces: from single molecules to multilayers. In DPG Spring Meeting 2015, Abstract: O14.12. DPG Spring Meeting 2015 , Berlin, Germany, March 16, 2015 - March 20, 2015. (2015)
Kenmoe, S.; Todorova, M.; Biedermann, P. U.; Neugebauer, J.: Impact of the vapour pressure of water on the equilibrium shape of ZnO nanoparticles: An ab-initio study. In APS March Meeting 2014, abstract #Q2.009. APS March Meeting 2014 , Denver, CO, USA, March 03, 2014 - March 07, 2014. (2014)
Kenmoe, S.; Todorova, M.; Biedermann, P. U.; Neugebauer, J.: Impact of the vapour pressure of water on the equilibrium shape of ZnO nanoparticles: An ab-initio study. In DPG Spring Meeting 2014, Abstract: O50.6. DPG Spring Meeting 2014 , Dresden, Germany, March 30, 2014 - April 04, 2015. (2014)
Biedermann, P. U.; Nayak, S.; Erbe, A.: The Mechanism of Electrochemical Oxygen Reduction: A Combined DFT and in-Situ ATR-IR Study on Model Semiconductor Surfaces Ge(100) and ZnO. 227th ECS Meeting, Chicago, IL, USA (2015)
Biedermann, P. U.; Nayak, S.; Erbe, A.: Catching intermediates of the oxygen reduction reaction in situ: Insights from electrochemical ATIR-IR and DFT. 112th Bunsentagung (Annual German Conference on Physical Chemistry), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany (2013)
Biedermann, P. U.; Nayak, S.; Erbe, A.: Towards Understanding the Mechanism of the Electrochemical Oxygen Reduction: DFT Modeling and Spectroelectrochemical Validation. Pacific Rim Meeting on Electrochemical and Solid-State Science PRIME 2012 / ECS 222, Honolulu, HI, USA (2012)
Nayak, S.; Biedermann, P. U.; Stratmann, M.; Erbe, A.: In situ Electrochemical ATR-IR Investigation of the Oxygen Reduction on Germanium. 62nd Annual Meeting of the International Society of Electrochemistry, Niigata, Japan (2011)
Berezkin, A. V.; Biedermann, P. U.; Auer, A. A.: Mesoscale simulation of network formation and structure, combining molecular dynamics and kinetic Monte Carlo approaches. European Polymer Congress 2011, Granada, Spain (2011)
Berezkin, A. V.; Biedermann, P. U.: Simulation of polyurethane and water interac-tions with the ZnO surface: DFT and classical OPLS-AA force field calculation. 4-th World Congress on Adhesion and Related Phenomena, Arcachon, France 2010 (2010)
Biedermann, P. U.: Ab initio approaches to Solvation Free Energies and Single-Ion Chemical Potentials. Minisymposium "Challenges for Theory in Electrochemistry", MPI für Eisenforschung GmbH, Düsseldorf, Germany (2010)
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
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…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
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.