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At least 235 records · Page 13

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗

Control of Permanent Porosity in Type 3 Porous Liquids via Solvent Clustering

Porous liquids (PLs) are an exciting new class of materials for carbon capture due to their high gas adsorption capacity and ease of industrial implementation. They are composed of sorbent particles suspended in a nonadsorbed solvent, forming a liquid with permanent porosity. While PLs have a vast number of potential compositions based on the number of solvents and sorbent materials available, most of the research has been focused on the selection of the sorbent rather than the solvent. Therefore, PL design criteria on the supramolecular structures of the solvent are explored to create a fundamental understanding of how the solvent enables PL formation for rapid discovery of new PL compositions. Atomistic molecular dynamics simulation of eight solvents with a range of molecular sizes, shapes, and intramolecular bonding was performed, identifying that the shape and size of molecular clusters formed in the solvent are the driving predictor of PL formation rather than the size of the individual solvent molecule. The results demonstrate a significant departure from common approaches to PL formation based on the steric exclusion of solvent molecules from the sorbent via the size of the pore aperture. A modeling and experimental validation study further supports these findings. In conclusion, through this computational material design study, a previously unexplored mechanism in PL formation, solvent–solvent clustering, is identified as a critical factor for the accelerated discovery of liquid phase carbon capture materials.

Carbon capture↗

Dynamics of two fluids under periodic acceleration

The evolution of the interface between two fluids confined in a rectangular cavity is investigated numerically to predict its transient behavior. These computations address mixing characteristics of fluids under microgravity conditions, particularly g-jitter conditions resulting from aircraft vibration or crew motion, and have applications in solution crystal growth. The two-dimensional formulation employs the Boussinesq approximation and treats the mixing of two fluids as an initial value problem with a prescribed concentration field. For fluid mixing of practical applications inside a cavity, it is shown that nonlinear convective transport can dominate over both viscous and molecular diffusion. However, viscous diffusion can become important for low Reynolds number or certain cavity sizes. A stacking phenomenon is shown to occur for aspect ratios (Ar) approximately between 5 to 10. For aspect ratios in the neighborhood of 0.1 to 0.2, inner cells evolve at the interface with increasing time. For a square cavity of Ar = 1, chaotic mixing of the fluid appears to occur for a Stokes-Reynolds number greater than about 5.

Duval, Walter M. B.↗

Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic–inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. Here, to understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31–calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ∼2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31–calcite interactions. While this work provides the first experimental confirmation that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31–calcite interface has advanced our fundamental understanding of the atomic interactions at the organic–inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Close, Emily G. S. [Pacific Northwest National Lab↗

DataSet for Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic-inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. To understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31-calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ~2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31-calcite interactions. These studies provide the first experimental evidence to confirm that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template. However, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31-calcite interface has advanced our fundamental understanding of the atomic interactions at the organic-inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Saccuzzo Close, Emily Grace [Pacific Northwest Nat↗

Gauging the Impact of Cosmic-ray Feedback on the Stellar Initial Mass Function

Cosmic rays (CRs) drive ionization and influence gas dynamics in molecular clouds (MCs), potentially impacting the resulting star formation outcomes. Although previous simulations of individual star formation have included methods for CR transport (CRT), none have been large enough to resolve the stellar initial mass function (IMF). We conduct numerical simulations following the collapse of a 20,000 M ⊙ MC and the subsequent star formation including CRT, both with and without CRs accelerated by winds from the young massive stars, and compare against a non-CRT simulation. We show that after the first massive stars form, the cavity produced by feedback is more pronounced in the CRT simulations because the external CRs are able to propagate inward and compress the gas into higher-density structures. This increases the subsequent star formation in the cloud; by the end of the simulation, the star formation efficiency (SFE) in the CRT simulation including stellar wind CRs is 43% higher than the non-CRT simulation. The IMF is also top-heavy in comparison, with a slope above 1 M ⊙ that is shallower by ∼20%. These effects are also present in the simulation without wind-accelerated CRs, but they are not as pronounced; the SFE is only 16% higher than the non-CRT simulation, and the IMF high-mass slope is shallower by ∼10%. These results may explain some of the observed top-heavy IMFs, which typically occur in high-CR environments such as the Galactic center.

Fitz Axen, Margot [Oak Ridge National Laboratory (↗

Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracy

We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel method and Bayesian linear regression to compute the free energy, atomic forces, and pressure, in conjunction with a linear regression model between the internal and free energies to compute the internal energy, with all training data generated from Kohn–Sham density functional theory (DFT). We verify the accuracy of the formalism by comparing the Hugoniot for carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that Kohn–Sham calculations for the Hugoniot can be accelerated by up to two orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the Hugoniots of 14 materials in the FPEOS database, comprising 9 single elements and 5 compounds, between temperatures of 10 kK and 2 MK. We find good agreement with first principles results in the literature while providing tighter error bars. In addition, we confirm that the inter-element interaction in compounds decreases with temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of differently oriented interlayer phases on the radiation damage of Inconel-$\mathrm{Ni}$ multimetallic layered composite

Multimetallic layered composites (MMLCs) have shown an excellent potential for application under extreme environments, e.g., accident-tolerant fuel cladding, because of their low oxidation tendency and high corrosion resistance. Interfacial phases or complexions in nanocrystalline materials accelerate the annihilation of defects and enhance the radiation resistance of materials, making MMLCs with engineered interlayer phases compelling to deploy in extreme conditions. However, implementation of MMLCs in full capacity remained a challenge due to a lack of fundamental understanding of the underlying mechanisms governing the characteristics of the interface between the metallic layers. The precise role of interlayer phases in MMLCs and their interaction with defects, specifically under extreme conditions, is still unexplored. Pursuing atomistic simulations for various Inconel-Ni MMLCs model materials, we revealed accelerated defect mobility in interlayers with larger crystalline misorientation and the inverse relationship between the interface sink strength to the misorientation angle. Furthermore, we found a linear relation between interlayer misorientation angle with the density of radiation-induced defects and radiation enhanced displacements. So, our results indicate that radiation-induced material degradation is accelerated by the higher defect formation tendency of MMLCs with a high-angle interlayer interface.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Segmental relaxation of sequence defined polymers

For this work, the dynamical behavior of sequence defined polymers, P(C n EG 4 ), was studied using dielectric spectroscopy showing one segmental relaxation in addition to a secondary relaxation. In case of segmental relaxation, the relaxation times strongly depend on the molecular weight at low temperatures, while at higher temperatures, unlike to linear homo polymers, this effect levels out. With increasing length of C-units, the segmental relaxation accelerates. This is also reflected in the glass transition temperature, extracted from dielectric spectroscopy. With increasing length of C-units the glass transition temperature decreases, compatible with the accelerated segmental relaxation.

36 MATERIALS SCIENCE↗

The time-resolved atomic, molecular and optical science instrument at the Linac Coherent Light Source

The newly constructed time-resolved atomic, molecular and optical science instrument (TMO) is configured to take full advantage of both linear accelerators at SLAC National Accelerator Laboratory, the copper accelerator operating at a repetition rate of 120 Hz providing high per-pulse energy as well as the superconducting accelerator operating at a repetition rate of about 1 MHz providing high average intensity. Both accelerators power a soft X-ray free-electron laser with the new variable-gap undulator section. With this flexible light source, TMO supports many experimental techniques not previously available at LCLS and will have two X-ray beam focus spots in line. Thereby, TMO supports atomic, molecular and optical, strong-field and nonlinear science and will also host a designated new dynamic reaction microscope with a sub-micrometer X-ray focus spot. The flexible instrument design is optimized for studying ultrafast electronic and molecular phenomena and can take full advantage of the sub-femtosecond soft X-ray pulse generation program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Microgravity Platforms

The world's space agencies have been conducting microgravity research since the beginning of space flight. Initially driven by the need to understand the impact of less than- earth gravity physics on manned space flight, microgravity research has evolved into a broad class of scientific experimentation that utilizes extreme low acceleration environments. The U.S. NASA microgravity research program supports both basic and applied research in five key areas: biotechnology - focusing on macro-molecular crystal growth as well as the use of the unique space environment to assemble and grow mammalian tissue; combustion science - focusing on the process of ignition, flame propagation, and extinction of gaseous, liquid, and solid fuels; fluid physics - including aspects of fluid dynamics and transport phenomena; fundamental physics - including the study of critical phenomena, low-temperature, atomic, and gravitational physics; and materials science - including electronic and photonic materials, glasses and ceramics, polymers, and metals and alloys. Similar activities prevail within the Chinese, European, Japanese, and Russian agencies with participation from additional international organizations as well. While scientific research remains the principal objective behind these program, all hope to drive toward commercialization to sustain a long range infrastructure which .benefits the national technology and economy. In the 1997 International Space Station Commercialization Study, conducted by the Potomac Institute for Policy Studies, some viable microgravity commercial ventures were identified, however, none appeared sufficiently robust to privately fund space access at that time. Thus, government funded micro gravity research continues on an evolutionary path with revolutionary potential.

Del Basso, Steve↗

Bidentate Lewis bases are preferred for passivation of MAPbI 3 surfaces: A time-domain ab initio analysis

We report chemical passivation is a predominant approach to inhibit intrinsic defects responsible for electron–hole recombination in perovskite solar cells. Using time-domain density functional theory combined with nonadiabatic molecular dynamics, we demonstrate defect passivation by separation of electrons and holes in metal halide perovskites (MHPs), and show that bidentate ligands exhibit the best performance. Defects in traditional semiconductors create deep midgap states, and passivation eliminates these states. In contrast, common defects produce no deep midgap states in MHPs. Instead, defects localize electrons and holes around defect sites, enhancing electron–hole interaction. Defect passivation in MHPs acts to separate charges, decreasing electron–hole and charge–phonon interactions, and increasing charge lifetimes. Bidentate ligands work best, because they can passivate both unsaturated chemical bonds created due to vacancy defects. Bidentate ligands with spatially separated binding sites are preferred, since they provide better match to the sparse inorganic lattice of MHPs. Similar to the Lewis base ligands, water also acts as a ligand and extends charge lifetimes, with the oxygen atom donating its lone electron pair to the defect site. However, water accelerates chemical degradation of MHPs. The binding energy of most ligands is larger than that of water, and therefore, the ligands displace water, increase MHP stability and prolong carrier lifetimes. The established physical mechanism of defect passivation, and the specific principles guiding the choice of passivating molecules advance our understanding of the exceptional properties of MHPs and suggest routes for further improvement of MHP performance in solar energy and optoelectronic applications.

36 MATERIALS SCIENCE↗

Computational simulation of asymmetric phase transformation in cracked Li₇La₃Zr₂O₁₂: Variant selection and chemo-mechanical implications

Coupling between microcracks and phase transformation in ion-conducting ceramics can jointly affect mechanical responses and ion transport. In this work we investigate the cubic-to-tetragonal phase transformation in Li₇La₃Zr₂O₁₂ in the presence of a microcrack under hydrostatic loading and quantify its implications for crack-tip stress concentration and Li-ion transport using phase-field and molecular dynamics simulations. The phase transformation exhibits a strong asymmetry between hydrostatic tension and compression. Under tension, the crack edge nucleates one tetragonal variant that amplifies the crack-tip stress intensity and promotes crack opening. Under compression, the crack tip nucleates a different tetragonal variant that enhances the stress-induced crack-closure tendency. Effective Li diffusivity analysis shows faster transport degradation under compression due to accelerated transformation kinetics, exposing a trade-off between mechanical stability and ionic conductivity. These results highlight the intertwined nature of cracking, phase transformation, and ionic transport in ion-conducting oxides and provide mechanistic insights into chemo-mechanical degradation of solid electrolytes.

36 MATERIALS SCIENCE↗

State of the Art Assessment of Simulation in Advanced Materials Development

Advances in both the underlying theory and in the practical implementation of molecular modeling techniques have increased their value in the advanced materials development process. The objective is to accelerate the maturation of emerging materials by tightly integrating modeling with the other critical processes: synthesis, processing, and characterization. The aims of this report are to summarize the state of the art of existing modeling tools and to highlight a number of areas in which additional development is required. In an effort to maintain focus and limit length, this survey is restricted to classical simulation techniques including molecular dynamics and Monte Carlo simulations.

Wise, Kristopher E.↗

Structure and Flow-Viscosity of Filled-Polymer-Based 3D Printing Ink: Exploration through Coarse-Grained Molecular Dynamics

The addition of nanofiller particles to a polymer matrix has long been known to enhance or modify the composite’s mechanical and rheological properties. However, quantitatively capturing such changes with molecular level simulations remains computationally challenging. Toward that goal, we performed coarse-grained molecular dynamics of a nanocomposite system at a fixed (25 vol %) filler loading under nonspecific, weak polymer–filler interactions representative of a broad class of technologically important materials. We report several interesting results, including: (1) the equilibrium chain-configuration remains Gaussian-like as in an unfilled melt; (2) smaller filler particles display a stronger tendency to cluster; (3) larger fillers act as plasticizers by reducing the entanglement density and accelerating the chain mobility; and (4) fillers enhance the tensile response modulus, with the effect being stronger for larger particles. We also simulate cluster breakup, yielding, and elongational flow under an applied time-linear tensile strain and study the flow viscosity as a function of filler-size and chain-length.

Materials science↗

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗

Theoretical considerations of shock wave behavior

Interstellar shock waves have a significant influence on the structure and dynamics of interstellar matter and probably trigger star formation in suitably dense regions. The overall structure of regions near shock waves is reviewed; in addition, the main observational effects of shocks on interstellar molecules are discussed including: (1) acceleration to velocities in the 1 km/s to 100 km/s range relative to the ambient gas, (2) excitation of infrared lines in the heated postshock gas, and (3) production of high abundances of certain molecular species such as H, OH, H2O, CH(+), OCS, and SiO through high temperature chemical reactions in the postshock gas at temperatures above 1000 K. The molecular region around the BN infrared source in Orion and the high velocity molecules in IC443 are discussed as possible examples of shocked molecular gas.

Hollenbach, D.↗

Temperature-induced structural evolution in liquid Ag-Ga alloys

Temperature-dependent atomic structural evolutions of liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys have been studied by in situ high-energy x-ray-diffraction (HEXRD) experiments combined with ab initio molecular-dynamics simulations. The experimental data show a reversible structural crossover at about 1050 ~ 1100 (± 50) K in both liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys. Obvious changes of the electrical resistivity, absolute thermoelectric power, and atomic diffusivity around the similar temperature range for both Ag-Ga liquids strongly support the HEXRD results. The origin of the liquid-to-liquid crossover in both Ag-Ga liquids was suggested to link with the rearrangements of Ag and Ga atoms, i.e., Ag and Ga atoms prefer to associate with themselves in the higher temperature range above 1100 K, consistent with the accelerated increase of the strong covalently bonded Ga–Ga dimers in both Ag-Ga liquids. In addition, more studies from the energy aspect are still desirable to understand the rearrangements of Ag and Ga atoms in the higher temperature range in both Ag-Ga liquids.

36 MATERIALS SCIENCE↗