Noël Jakse

Liquid uranium-zirconium (U,Zr) mixtures play a crucial role in the context of nuclear accident scenarios, particularly in the early stages of Pressurized-Water Reactor accidents. In this study, we compare the thermophysical and structural predictions of two interatomic potentials for this system, namely a Modified-Embedded Atom Model (MEAM) semi-empirical interatomic potential and a Spectral Neighbor Analysis Potential (SNAP). These models are employed to investigate the relationship between the viscosity, density, and structural properties of liquid (U,Zr) mixtures, and compare their respective predictions. More specifically, the MEAM potential predicts a significant viscosity anomaly at a molar fraction of approximately 70% of Zr. A thorough structural analysis leveraging radial distribution functions and structure factors, Voronoi tessellation, average degree of five-fold local symmetry, and common neighbor analysis supports these findings and attributes them to the formation of an icosahedral short-range order. In contrast, this structural ordering is not observed with the ab initio and SNAP-based computations. We finally analyze those differences and suggest that the semi-empirical MEAM potential may overestimate ordering effects in the liquid phase. These new results can play a role in the refinement of nuclear fuel models, improving the available recommendations for in-vessel corium retention simulations aimed at mitigating severe accident scenarios.

A computing solution combining the GNU Guix functional package manager with the Apptainer container system is presented. This approach provides fully declarative and reproducible software environments suitable for computational materials science. Its versatility and performance enable the construction of complete frameworks integrating workflow managers such as AiiDA and Ewoks that can be deployed on HPC infrastructures. The efficiency of the solution is illustrated through several examples: (i) AiiDA workflows for automated dataset construction and analysis as well as path‐integral molecular dynamics based on ab initio calculations; (ii) workflows for the training of machine‐learning interatomic potentials; and (iii) an Ewoks workflow for the automated analysis of coherent X‐ray diffraction data in large‐scale synchrotron facilities. These examples demonstrate that the proposed environment provides a reliable and reproducible basis for computational and data‐driven research in materials science.

Dispersion of acoustic and optic collective excitations are comparatively studied in two Al-based liquid metallic alloys, which contain ten atomic percent of Si with four valence electrons or Mg with two ones. Partial density-density and current-current time correlation functions are analyzed by a combination of {\it ab initio} molecular dynamics simulations and theoretical generalized collective modes (GCM) approach. We obtain and analyze the dispersion of acoustic and optic collective excitations and wave number dependence of the slowest relaxation process as eigenmodes of the generalized Langevin equation in matrix form. These findings allow understanding of different factors responsible for features in collective dynamics of these two liquid metallic alloys.

Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describing the interactions between atoms, which is further complicated by chemical order through cross-species interactions. The large scales needed to observe rare nucleation events are far beyond the capabilities of ab initio simulations. Machine learning is used for overcoming these limitations in terms of both accuracy and speed, by building a high-dimensional neural network potential for binary Al–Ni alloys, which serve as a model system relevant to many industrial applications. The potential is validated against experimental diffusion, viscosity, scattering data, and its melting temperature. It is applied to large-scale molecular dynamics simulations of homogeneous nucleation, specifically for Al–Ni at equiatomic composition and for pure Ni. Pure Ni nucleates in a single step into an fcc crystal phase, in contrast to previous results obtained with a classical empirical potential. This highlights the sensitivity of nucleation pathways to the underlying atomic interactions. Our findings suggest that the nucleation pathway for AlNi proceeds in a single step toward a B2 structure, which is discussed in relation to the pure elements counterparts.

First-principles based molecular-dynamics simulations have been performed for binary Cu x Ti 1 − x ( x = 0.31, 0.50, and 0.76) alloys to investigate the relationship between local structure and dynamical properties in the liquid and undercooled melt. The undercooled melts show a pronounced short-range order, majorly a fivefold symmetry (FFS) around the Cu atoms, which competes with bcc ordering. This complex SRO is also reflected in the partial coordination numbers, where mainly a Z12 coordination is present around Cu, which corresponds to an icosahedral ordering. Higher coordination numbers were obtained for Ti compatible with Frank-Kasper polyhedra. The increasing Frank-Kasper polyhedra coordination scenario around Ti impacts the interatomic distances of Ti atoms, which increase with increasing Ti content. The Cu 50 Ti 50 composition exhibits the highest FFS ordering and amount of Frank-Kasper polyhedra, which explains the slowest melt dynamics, found experimentally and in simulations for this composition. Thus, our results suggest that the high undercooling degree originates from the high complexity of the local structure rather than due to the preferred formation of Cu-Ti pairs, as Cu-Ti interactions were found to be weak.

The self-diffusion process in a dense liquid is influenced by collective particle movements. Extensive molecular dynamics simulations for liquid aluminium and rubidium evidence a crossover in the diffusion coefficient at about 1.4 times the melting temperature T m , indicating a profound change in the diffusion mechanism. The corresponding velocity autocorrelation functions demonstrate a decrease of the cage effect with a gradual set in of a power-law decay, they celebrate long time tail. This behavior is caused by a competition of density fluctuations near the melting point with vortex-type particle patterns from transverse currents in the hot fluid. The investigation of the velocity autocorrelation function evidences a gradual transition in dynamics with rising temperature. The competition between these two collective particle movements, one hindering and one enhancing the diffusion process, leads to a non-Arrhenius-type behavior of the diffusion coefficient around 1.4 T m , which signals the transition from a dense to a fluidlike liquid dynamics in the potential energy landscape picture.

Classical (MD) and ab initio (AIMD) molecular dynamics simulations were conducted to investigate the fundamental properties of solid and liquid MgO. AIMD was performed by DFT using the Strongly Conditioned and Appropriately Normed (SCAN) exchange correlation functional. The obtained pair-correlation functions of liquid MgO were used as reference data for the optimization of parameters of classical MD. For the latter, a Born–Mayer–Huggins (BMH) potential was applied, and parameters were adjusted until a best fit of both structural properties was obtained by AIMD and physical properties by experimental data. Different structural, dynamic and thermodynamic properties of solid and liquid MgO were then calculated by classical MD and compared with the literature data. Good agreement was found for the Mg-O bond length, self-diffusion coefficients, density of liquid MgO and for heat content and density of crystalline MgO. Using a void-melting approach, the melting temperature of MgO was found as 3295 ± 30 K, which is in good agreement with the recent experimental work by Ronchi et al. (3250 ± 20 K). The optimized parameters of BMH potential describe well the structural, dynamic and thermodynamic properties of solid and liquid MgO and may be combined with our previous results of a CaO-Al₂O₃-TiO₂ system to calculate the properties of a quaternary CaO-MgO-Al₂O₃-TiO₂ system.