Isotta, E.: Investigating microstructure via thermal conductivity imaging: from grain boundaries, to phase segregations and material anisotropy. 50th International Conference and Expo on Advanced Ceramics and Composites (ICACC 2026), Daytona Beach, FL, USA (2026)
Isotta, E.: Investigating microstructure via thermal conductivity imaging: from grain boundaries, to material anisotropy, and phase segregations. Invited Seminar at RWTH Aachen, Physics Department, Aachen, Germany (2025)
Isotta, E.: Thermal conductivity imaging to advance microstructure engineering in thermoelectric and energy materials. Materials Science and Technology Meeting (MSandT) 2025, Columbus, OH, USA (2025)
Isotta, E.; Zhang, S.; Ghosh, S.; de Boor, J.; Balogun, O.; Snyder, G. J.; Scheu, C.: Thermal conductivity imaging to advance microstructure engineering in thermoelectrics. European Conference on Thermoelectrics 2025, Nancy, France (2025)
Isotta, E.: Thermal conductivity imaging to guide microstructure engineering in energy materials. Invited Seminar at the Karlsruhe Institute of Technology, Karlsruhe, Germany (2025)
Isotta, E.: Thermal conductivity imaging to guide microstructure engineering in energy materials. Invited Seminar at the German Aerospace Center in Cologne, Köln, Germany (2025)
Isotta, E.: Thermal conductivity imaging to guide microstructure engineering in energy materials. Iberian Workshop on Thermoelectrics 2025, Castello de la Plana, Spain (2025)
Isotta, E.: Local thermal conductivity imaging and modelling to guide microstructure engineering in energy materials. TMS 2025 Annual Meeting, Las Vegas, NV, USA (2025)
Isotta, E.: Thermal conductivity imaging to guide microstructure engineering in energy materials. Invited Seminar at the Institute of Science and Technology Austria, Klosterneuburg, Austria (2024)
Busch, F.; Balogun, O.; Snyder, G. J.; Scheu, C.; Isotta, E.: Unravelling grain boundary influences on electronic and lattice thermal conductivity in Mn-doped SnTe thermoelectrics. 21st European Conference on Thermoelectrics (ECT) 2025, Nancy, Frankreich (2025)
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
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.
While Density Functional Theory (DFT) is in principle exact, the exchange functional remains unknown, which limits the accuracy of DFT simulation. Still, in addition to the accuracy of the exchange functional, the quality of material properties calculated with DFT is also restricted by the choice of finite bases sets.