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NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
NasGen provides a path for migration of structural models from NASTRAN bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Presto). Many tools at Sandia National Labs (SNL) use the Exodus format. NasGen was written specifically for Salinas and Presto but should be usable with a number of these packages.
NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
NasGen provides a path for migration of structural models from NASTRAN bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Presto). Many tools at Sandia National Labs use the Exodus format. NasGen was written specifically for Salinas and Presto but should be usable with a number of these packages.
Solid-state material at high pressure is prevalent throughout the Universe, and an understanding of the structure of matter under such extreme conditions, gleaned from x-ray diffraction, has been pursued for the best part of a century. The highest pressures that can be reached to date (2 TPa) in combination with x-ray diffraction diagnosis have been achieved by dynamic compression via laser ablation. The past decade has witnessed remarkable advances in x-ray technologies, with novel x-ray Free-Electron-Lasers (FELs) affording the capacity to produce high quality single-shot diffraction data on timescales below 100 fs. We provide a brief history of the field of dynamic compression, spanning from when the x-ray sources were almost always laser-plasma based, to the current state-of-the art diffraction capabilities provided by FELs. We give an overview of the physics of dynamic compression, diagnostic techniques, and the importance of understanding how the rate of compression influences the final temperatures reached. We provide illustrative examples of experiments performed on FEL facilities that are starting to give insight into how materials deform at ultrahigh strain rates, their phase diagrams, and the types of states that can be reached. We emphasize that there often appear to be differences in the crystalline phases observed between the use of static and dynamic compression techniques. We give our perspective on both the current state of this rapidly evolving field and some glimpses of how we see it developing in the near-to-medium term.
Rapid advancements in safe and high-energy-density energy storage are predicated on identifying new solid-state ion conductors with low activation energies and high ionic conductivities for all-solid-state battery technologies. Halide argyrodites are among some of the top candidates for solid-state electrolytes, as they can achieve ionic conductivities that approach liquid electrolytes. Incorporating dynamic pseudohalide species in argyrodite solid electrolytes presents an exciting opportunity to exploit lattice dynamics as a design principle to modulate the ion conduction properties of solid-state ion conductors. In the present study, we have prepared the new argyrodite Li 6 PS 5 CN containing orientationally disordered cyanide ions. The new cyanide argyrodite Li 6 PS 5 CN exhibits an activation barrier to Li-ion transport of 471 ± 25 meV and a room-temperature ionic conductivity of 6(2) × 10 –5 S cm –1 in comparison to the activation barrier of 502 ± 16 meV and an ionic conductivity of 2.3(1) × 10 –4 S cm –1 measured for the bromide analogue Li 6 PS 5 Br. Structural studies of both compounds by high-resolution X-ray diffraction indicate that Li 6 PS 5 CN and Li 6 PS 5 Br adopt nearly identical crystal structures with similar lattice parameters, which indicates that lower activation barriers in Li 6 PS 5 CN arise due to the cyanide ion itself rather than due to changes in the geometry of conduction pathways in the local lithium environment. The orientational disorder of the quadrupolar cyanide ion in Li 6 PS 5 CN points to a complex interplay of lattice polarizability and molecular dynamics that lower the activation barrier for lithium-ion conductivity in the cyanide argyrodite.
HOSS software, developed at LANL, is a powerful, flexible, and parallelized package that enables the user to predict deformation and failure of materials in a variety of situations. LANL’s HOSS software is an R&D 100 finalist that integrates solid mechanics and computational fluid dynamics into a multi-physics platform able to handle millions of interacting and fracturing solids and/or particle systems. This nextgeneration simulation software integrates solid mechanics and computational fluid dynamics into a multi-physics platform able to provide state-of-the-art simulation solutions for a wide field of applications including oil and gas, construction, mining, defense, material sciences, and biomechanics.
Thermodynamics-based models predict the structure of polymer-grafted nanoparticles (PGNs) as well as their assembly behavior based on geometric parameters such as particle size, degree of polymerization, and density of grafted chains. The role of microscopic polymer dynamics, such as the mobility of repeat units in the melt state, in the evolution of the structure and properties remains unknown. Brillouin light spectroscopy (BLS), due to its capability to concurrently discern the local and global elastic properties of PGN assemblies, enables the probing of microscopic processes, such as brush interdigitation, sensitive to the annealing of the assembly. For poly(methyl methacrylate) (PMMA)-grafted silica (SiO 2 ) PGNs in the dry powder state and annealed above the glass transition temperature, BLS revealed fully reversible local elasticity, indicative of limited interdigitation between adjacent PGNs. This contrasts with polystyrene (PS)−SiO 2 analogs that displayed ready (and irreversible) fusion of brush layers during annealing. The retardation of brush interdigitation in PMMA-grafted systems is surprising, given the similar thermomechanical properties of both polymers, and is rationalized as the consequence of higher friction between PMMA repeats compared to PS. Microscopic dynamics thus has a profound impact on the kinetic path of structure (and property) evolution and thus should be considered during the processing of PGNs into functional hybrid materials.
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Abstract Vibrational spectroscopy allows us to understand complex physical and chemical interactions of molecular crystals and liquids such as ammonia, which has recently emerged as a strong hydrogen fuel candidate to support a sustainable society. We report inelastic neutron scattering measurement of vibrational properties of ammonia along the solid-to-liquid phase transition with high enough resolution for direct comparisons to ab-initio simulations. Theoretical analysis reveals the essential role of nuclear quantum effects (NQEs) for correctly describing the intermolecular spectrum as well as high energy intramolecular N-H stretching modes. This is achieved by training neural network models using ab-initio path-integral molecular dynamics (PIMD) simulations, thereby encompassing large spatiotemporal trajectories required to resolve low energy dynamics while retaining NQEs. Our results not only establish the role of NQEs in ammonia but also provide general computational frameworks to study complex molecular systems with NQEs.
The injection of high-speed cryogenic pellets made of frozen hydrogen-isotopes, represents to date the most effective method to fuel magnetically confined thermonuclear fusion plasmas. Additionally, the injection of very large pellets composed of cryogenic solid of some suitable impurity (typically a noble-gas such as H 2 , Ne, or H 2 /Ne, D 2 /Ne mixtures), shattered in relatively small fragments just before entering the plasma, seems to be the most promising method to reduce the damage risks for the plasma-facing components in case of a plasma disruption. This technology, known as "Shattered Pellet Injection" (SPI), allows to spread out the plasma energy and mitigate possible damage to the in-vessel components, as well as to densify the plasma to suppress the formation of runaway electrons, and/or dissipate their energy. Several techniques to produce and launch cryogenic pellets have been investigated in the past decades. "Pipe gun" injectors are reliable and relatively simple devices are still commonly used today. They make use of single- or two-stage pneumatic light-gas guns to accelerate the pellet at high speeds. In these injectors, the cryogenic pellets are formed “ in situ ” (i.e., inside the launching barrel), by de-sublimating them directly from the gas phase, i.e., at temperatures and pressures below those of the triple point. The simplest case is pure deuterium pellets ($\mathcal{T}$ < 18.7 K, $\mathcal{P}$ < 171.3 hPa). The production of good quality solid deuterium, capable of withstanding the mechanical stress during the acceleration of the pellets, is a key issue. To this end the phase transition of deuterium from gas to solid (and vice versa) is modeled with extensive molecular-dynamics (MD) simulations. Furthermore, the solid growth from the gas phase is simulated in an ample range of temperatures and pressures, to find the best compromise between growth velocity and mechanical properties of the resulting solid system.
The vibrational dynamics of molecules and solids play a critical role in defining material properties, particularly their thermal behaviors. However, theoretical calculations of these dynamics are often computationally intensive, while experimental approaches can be technically complex and resource-demanding. Recent advancements in data-driven artificial intelligence (AI) methodologies have substantially enhanced the efficiency of these studies. This review explores the latest progress in AI-driven methods for investigating atomic vibrations, emphasizing their role in accelerating computations and enabling rapid predictions of lattice dynamics, phonon behaviors, molecular dynamics, and vibrational spectra. Key developments are discussed, including advancements in databases, structural representations, machine-learning interatomic potentials, graph neural networks, and other emerging approaches. Compared to traditional techniques, AI methods exhibit transformative potential, dramatically improving the efficiency and scope of research in materials science. The review concludes by highlighting the promising future of AI-driven innovations in the study of atomic vibrations.
In this paper, we report the laser-induced solid-state transformation between a periodic “approximant” and quasicrystal in the Al-Cr system during rapid quenching. Dynamic transmission electron microscopy allows us to capture in situ the dendritic growth of the metastable quasicrystals. The formation of dendrites during solid-state transformation is a rare phenomenon, which we attribute to the structural similarity between the two intermetallics. Through ab initio molecular dynamics simulations, we identify the dominant structural motif to be a 13-atom icosahedral cluster transcending the phases of matter.
An ab initio molecular dynamics study of an electrochemical interface between a solid-state-electrolyte Li 0.29 La 0.57 TiO 3 and Li-metal to analyze interphase formation and evolution when external electric fields are applied.