The intermetallic alloy FeTi is regarded as a promising storage material for solid‑state hydrogen storage: cost‑effective, safe, and operable under near‑ambient conditions. However, a consistent multiscale model capable of describung the various atomic, thermodynamic, and microstructural processes involved in FeTi hydrogenation has so far been elusive. This dissertation presents, for the first time, an integrated computational model based on density functional theory (DFT), CALPHAD, and phase‑field methodology that quantitatively describes the hydrogenation of FeTi. Starting from First-Principles calculations, thermodynamic properties, interfacial energies, and elastic effects are determined with high accuracy and incorporated into mesoscale simulations. The resulting model accuratelyreproduces experimental isotherms, explains the formation and stability of the occurring hydride phases, and enables realistic predictions of microstructural evolution during hydrogen uptake. Thus, this work provides a foundation for the digital design and computational optimization of FeTi‑based hydrogen storage materials.
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Dr. Ebert Alvares is a Brazilian materials engineer whose academic training spans Brazil, France, and Germany, reflecting a strong international research profile. He studied Materials Engineering and Materials Science at the Federal University of São Carlos (Brazil), Université Grenoble Alpes (France), and École des Mines de Saint-Étienne (France), and completed his doctoral degree at Helmut Schmidt University (Germany). His education combines materials engineering, thermodynamics, and computational materials science. He is currently a researcher at the Institute of Hydrogen Technology, Helmholtz-Zentrum Hereon, Hamburg, Germany. His work focuses on computational and multiscale modeling of metallic materials for solid-state hydrogen storage, integrating CALPHAD-based thermodynamics, density functional theory (DFT), and phase-field methods involving thermo-mechanical simulations. Through his experience across diverse academic and industrial research environments, he develops predictive, scale-bridging modeling frameworks that support the predictive design and simulation of material properties for applications in sustainable energy technologies.
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