Cojocaru-Mirédin, O.; Schwarz, T.; Choi, P.; Würz, R.; Raabe, D.: Exploring the internal interfaces at the atomic-scale in thin-film solar cells. Seminar Talk at Helmholtz Zentrum Berlin (HZB), Berlin, Germany (2012)
Li, Y. J.; Choi, P.; Goto, S.; Borchers, C.; Raabe, D.; Kirchheim, R.: Evolution of strength and microstructure during annealing of heavily cold-drawn 6.3 GPa hypereutectoid pearlitic steel wire. 53rd International Field Emission Symposium (IFES), Tascaloosa, AL, USA (2012)
Choi, P.: Characterization of advanced functional and structural materials using Atom Probe Tomography. Inauguration symposium for the Atom Probe facilities ETH Zürich, Zürich, Switzerland (2011)
Cojocaru-Mirédin, O.; Choi, P.; Würz, R.; Abou-Ras, D.; Raabe, D.: Explorer les interfaces à l’échelle atomique dans les cellules photovoltaïques CIGSe. Commissariat à l’Energie Atomique et aux Energies Alternatives, Grenoble, France (2011)
Herbig, M.; Li, Y.; Choi, P.: Atomic Analysis of Concentration Changes at Interfaces by Atom Probe Tomography. SFB 761 Doktorandenseminar, RWTH Aachen, Germany (2011)
Cojocaru-Mirédin, O.; Choi, P.; Abou-Ras, D.; Wuerz, R.; Liu, T.; Schmidt, S. S.; Caballero, R.; Raabe, D.: Characterization of internal interfaces in Cu(In,Ga)Se2 thin-film solar cells using Atom Probe Tomography. Euromat 2011, Montpellier, France (2011)
Choi, P.: Study of local chemical gradients in advanced precipitation hardened steel using atom probe tomography. THERMEC 2011, Québec City, QC, Canada (2011)
Choi, P.: Characterization of CuInSe2 and CuInGaSe2 thin-film solar cells using Atom Probe Tomography. International Conference on Electronic Materials and Nanotechnology for Green Environemnt, Jeju Island, South Korea (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
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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…
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…