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Modeling materials from first principles, i.e., without the need to fit or depend on experimental data, has taken on great importance in the last twenty years. Such methodology allows a deeper understanding of the physico-chemical phenomena dictating how materials behave. Density-functional theory (DFT) has been the tool of choice for computing the properties of materials at the nanoscale for decades. Indeed, ground-state properties such as phase diagrams, magnetism, or band gaps (determining whether a material is an insulator, semiconductor, or metal) and structures as well as more advanced properties such as charge carrier mobilities, ionic conductivity, or light emission/absorption spectra are all reachable within DFT and its extensions.   Because such computations are very demanding, both in terms of CPU power and human efforts, in the last 15 years additional tools have been developed to handle hundreds of thousands of such calculations and store them efficiently in databases. For example, the Materials...

Electrodeposition plays a crucial role in the fabrication of advanced coatings and materials with tailored properties. Research on the electrochemical deposition of nickel-based alloys highlights its catalytic performance. Investigating the nucleation and growth mechanisms in Ni-based alloys deposition bridges the gap between fundamental electrochemistry and practical applications.   Defining New Electrochemical Reactions   One of the key challenges in Ni alloy electrodeposition is understanding the reduction mechanism of alloying element. Unlike nickel, which reduces directly, certain alloying elements undergo a more complex reduction process. Through electrochemical modeling, new reaction pathways were defined by summing multiple electrochemical reactions and optimizing the Butler-Volmer equations. This approach enables a more accurate description of the kinetic parameters governing the process.   AI-Powered Analysis of SEM Images   To quantify the nucleation behavior, the VUB AI tool was utilized for analyzing scanning electron microscopy (SEM) images. This AI-driven approach enables precise detection and measurement of nuclei, providing valuable insights into the effect of...