Kraemer, M.; Favelukis, B.; Sokol, M.; Rosen, B. A.; Eliaz, N.; Kim, S.-H.; Gault, B.: Facilitating Atom Probe Tomography of 2D MXene Films by In Situ Sputtering. Microscopy and Microanalysis 30 (6), pp. 1057 - 1065 (2024)
Sharma, V. M.; Svetlizky, D.; Das, M.; Tevet, O.; Krämer, M.; Kim, S.-H.; Gault, B.; Eliaz, N.: Microstructure and mechanical properties of bulk NiTi shape memory alloy fabricated using directed energy deposition. Additive Manufacturing 86, 104224 (2024)
Krämer, M.; Favelukis, B.; El-Zoka, A.; Sokol, M.; Rosen, B. A.; Eliaz, N.; Kim, S.-H.; Gault, B.: Near-Atomic Scale Perspective on the Oxidation of Ti3C2Tx MXenes: Insights from Atom Probe Tomography. Advanced Materials 23 (3), 2305183 (2024)
Woods, E.; Singh, M. P.; Kim, S.-H.; Schwarz, T.; Douglas, J. O.; El-Zoka, A.; Giulani, F.; Gault, B.: A versatile and reproducible cryo-sample preparation methodology for atom probe studies. Microscopy and Microanalysis, ozad120 29 (6), pp. 1992 - 2003 (2023)
Yoo, S.-H.; Aota, L. S.; Shin, S.; El-Zoka, A. A.; Kang, P. W.; Lee, Y.; Lee, H.; Kim, S.-H.; Gault, B.: Dopant Evolution in Electrocatalysts after Hydrogen Oxidation Reaction in an Alkaline Environment. ACS Energy Letters 8 (8), pp. 3381 - 3386 (2023)
Kim, S.-H.; Stephenson, L.; Schwarz, T.; Gault, B.: Chemical Analysis for Alkali Ion–exchanged Glass Using Atom Probe Tomography. Microscopy and Microanalysis 29 (3), pp. 890 - 899 (2023)
Kim, S.-H.; Shin, K.; Zhou, X.; Jung, C.; Kim, H. Y.; Pedrazzini, S.; Conroy, M.; Henkelman, G.; Gault, B.: Atom probe analysis of BaTiO3 enabled by metallic shielding. Scripta Materialia 229, 115370 (2023)
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)
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…