Aota, L. S.; Jung, C.; Zhang, S.; Kim, S.-H.; Gault, B.: Revealing Compositional Evolution of PdAu Electrocatalyst by Atom Probe Tomography. ACS Energy Letters 8 (6), pp. 2824 - 2830 (2023)
Kim, S.-H.; Jun, H.; Jang, K.; Choi, P.-P.; Gault, B.; Jung, C.: Exploring the Surface Segregation of Rh Dopants in PtNi Nanoparticles through Atom Probe Tomography Analysis. The Journal of Physical Chemistry C 127 (46), pp. 22721 - 22725 (2023)
Singh, M. P.; Woods, E.; Kim, S.-H.; Jung, C.; Aota, L. S.; Gault, B.: Facilitating the Systematic Nanoscale Study of Battery Materials by Atom Probe Tomography through in-situ Metal Coating. Batteries & Supercaps 7 (2), e202300403 (2023)
Kim, S.-H.; El-Zoka, A.; Gault, B.: A Liquid Metal Encapsulation for Analyzing Porous Nanomaterials by Atom Probe Tomography. Microscopy and Microanalysis 28 (4), pp. 1198 - 1206 (2022)
Jung, C.; Jun, H.; Jang, K.; Kim, S.-H.; Choi, P.-P.: Tracking the Mn Diffusion in the Carbon-Supported Nanoparticles Through the Collaborative Analysis of Atom Probe and Evaporation Simulation. Microscopy and Microanalysis 28 (6), pp. 1841 - 1850 (2022)
Kim, S.-H.; Dong, K.; Zhao, H.; El-Zoka, A.; Zhou, X.; Woods, E.; Giuliani, F.; Manke, I.; Raabe, D.; Gault, B.: Understanding the Degradation of a Model Si Anode in a Li-Ion Battery at the Atomic Scale. The Journal of Physical Chemistry Letters 13 (36), pp. 8416 - 8421 (2022)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO2-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into…
It is very challenging to simulate electron-transfer reactions under potential control within high-level electronic structure theory, e. g. to study electrochemical and electrocatalytic reaction mechanisms. We develop a novel method to sample the canonical NVTΦ or NpTΦ ensemble at constant electrode potential in ab initio molecular dynamics…
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…
The field of micromechanics has seen a large progress in the past two decades, enabled by the development of instrumented nanoindentation. Consequently, diverse methodologies have been tested to extract fundamental properties of materials related to their plastic and elastic behaviour and fracture toughness. Established experimental protocols are…
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…