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)
Bueno Villoro, R.; Zavanelli, D.; Jung, C.; Mattlat, D. A.; Naderloo, R. H.; Pérez, N. A.; Nielsch, K.; Snyder, G. J.; Scheu, C.; He, R.et al.; Zhang, S.: Grain Boundary Phases in NbFeSb Half-Heusler Alloys: A New Avenue to Tune Transport Properties of Thermoelectric Materials. Advanced Energy Materials 13 (13), 2204321 (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)
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)
Zhang, S.; Yu, Y.; Jung, C.; Mattlat, D. A.; Abdellaoui, L.; Scheu, C.: In situ STEM observation of thermoelectric materials under heating and biasing conditions. The 6th joint Sino-German workshop on advanced & correlative electron microscopy of catalysts, quantum phenomena & soft matter, Bad Honnef, Germany (2024)
Zhang, S.; Yu, Y.; Jung, C.; Wang, Z.; Mattlat, D. A.; Abdellaoui, L.; Scheu, C.: In situ microstructural observation and electrical transport measurements of PbTe thermoelectrics by transmission electron microscopy. International Conference on Thermoelectrics ICT, Krakow, Poland (2024)
Bhat, M. K.; Brink, T.; Ding, H.; Jung, C.; Best, J. P.; Dehm, G.: Influence of the Structure and Chemistry of Σ5 Grain Boundaries on Microscale Strengthening in Cu Bicrystals. TMS Annual Meeting and Exhibition 2024, Orlando, FL, USA (2024)
Jung, C.: Understanding of the property-structure relationship for thermoelectric materials through advanced characterization. Korea Electrotechnology Research Institute, Changwon, South Korea (2023)
Jung, C.: Investigation of interface between CIGS and buffer layer using atom probe tomography. Korea Institute of Energy Research, Daejeon, South Korea (2023)
Jung, C.: NbCoSn based half-Heusler compounds through crystallization of amorphous precursors. Kyungpook National University, Daegu, South Korea (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
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.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…