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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The design space of E(3)-equivariant atom-centred interatomic potentials

Abstract Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.

Computer Science↗
DOE OSTI2023

Metallization and spin fluctuations in Cu-doped lead apatite

An electronic structure and magnetic properties analysis of the recently proposed Cu-doped lead apatite is performed. Here, we show that electronic structures of differently Cu-substituted structures are characterized by localized molecular Cu-O bands at or near the Fermi level. The Cu substitutions can happen at both Pb1 and Pb2 sites, leading to metallic and semiconducting systems differently. The electronic systems in these bands are highly unstable magnetically and form clusters of rigidly ferromagnetically coupled magnetic moments on Cu and neighboring oxygen atoms with a total moment of about 1µ B . The ground state of uniformly Cu-doped lead apatite appears to be magnetic and semiconducting. The nonuniform distribution of two Cu atoms at the nearest Pb2 sites leads to an antiferromagnetic semiconducting state with formation energy close to uniformly distributed Cu configurations. The inclusion of quantum spin fluctuations confirms the stability of magnetic Cu-O clusters. Our calculations revealed the absence of the long-range magnetic order between uniformly distributed Cu-O clusters, creating the spin glass type of system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Short- and medium-range orders in Al90Tb10 glass and their relation to the structures of competing crystalline phases

Molecular dynamics simulations using an interatomic potential developed by artificial neural network deep machine learning are performed to study the local structural order in Al90Tb10 metallic glass. We show that more than 80% of the Tb-centered clusters in Al90Tb10 glass have short-range order (SRO) with their 17 first coordination shell atoms stacked in a ‘3661’ or ‘15551’ sequence. Medium-range order (MRO) in Bergman-type packing extended out to the second and third coordination shells is also clearly observed. Analysis of the network formed by the ‘3661’ and ‘15551’ clusters show that ~82% of such SRO units share their faces or vertexes, while only ~6% of neighboring SRO pairs are interpenetrating. Such a network topology is consistent with the Bergman-type MRO around the Tb-centers. Moreover, crystal structure searches using genetic algorithm and the neural network interatomic potential reveal several low-energy metastable crystalline structures in the composition range close to Al 90 Tb 10 . Some of these crystalline structures have the ‘3661’ SRO while others have the ‘15551’ SRO. While the crystalline structures with the ‘3661’ SRO also exhibit the MRO very similar to that observed in the glass, the ones with the ‘15551’ SRO have very different atomic packing in the second and third shells around the Tb centers from that of the Bergman-type MRO observed in the glassy phase.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Peculiarities of the formation of photonic nanojets by a matrix of dielectric microtoroids

We report the results of theoretical modelling of photonic nanojets (PNJs) formed by laser radiation scattering on a single-layer ordered assembly of dielectric microtoroids placed on the surface of a transparent matrix (silicone film). Using the method of computational electrodynamics (FDTD), the main PNJ parameters (length, width, peak intensity) are analysed under the conditions of mutual influence of the light fields of neighbouring microparticles. It is shown that the main factor affecting the PNJ characteristics under study is the spatial configuration of the radiation-scattering particle, namely, the internal diameter of its cross section. It is found that for certain configurations of toroid placement in a cluster, a PNJ ensemble is implemented with parameters significantly better than those for a single toroid. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Geometry optimizations with spinor-based relativistic coupled-cluster theory

Development of analytic gradients for relativistic coupled-cluster singles and doubles augmented with a non-iterative triples [CCSD(T)] method using an all-electron exact two-component Hamiltonian with atomic mean-field spin–orbit integrals (X2CAMF) is reported. This enables efficient CC geometry optimizations with spin–orbit coupling included in orbitals. Here, the applicability of the implementation is demonstrated using benchmark X2CAMF-CCSD(T) calculations of equilibrium structures and harmonic vibrational frequencies for methyl halides, CH 3 X (X = Br, I, and At), as well as calculations of rotational constants and infrared spectrum for RaSH+, a radioactive molecular ion of interest to spectroscopic study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

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↗
DOE OSTI2026

The Hidden Path to the Resonance-Stabilized Fulvenallenyl Radical (C 7 H 5 ) via the Bimolecular Reaction of Tricarbon (C 3 , X 1 Σ g + ) with 1,3-Butadiene (C 4 H 6 ; X 1 A g )

Here, we report a novel bimolecular reaction pathway forming the resonance-stabilized fulvenallenyl radical (C 7 H 5 ) via the gas-phase reaction of tricarbon (C 3 , X 1 Σ g + ) with 1,3-butadiene (C 4 H 6 , X 1 A g ). Crossed molecular beam experiments combined with high-level electronic structures and statistical calculations reveal a rich potential energy surface. The reaction proceeds via tricarbon addition to a double bond of 1,3-butadiene, overcoming a 30 kJ mol –1 barrier, followed by ring closure, isomerizations (ring opening/closures, hydrogen shifts), and eventual hydrogen atom loss, yielding the fulvenallenyl radical (p1) almost exclusively via two dominant pathways. Considering the entrance barrier, this reaction may occur in high-temperature environments, like circumstellar envelopes of carbon stars, but is suppressed in colder regions such as molecular clouds and Titan’s atmosphere. These findings highlight the unexpected reactivity of small carbon clusters in shaping the molecular complexity of our universe, from the flicker of a flame to the death of a star.

Aromatic compounds↗
DOE OSTI2020

CephFS experiments on stria.sandia.gov

This report is an institutional record of experiments conducted to explore performance of a vendor installation of CephFS on the SNL stria cluster. Comparisons between CephFS, the Lustre parallel file system, and NFS were done using the IOR and MDTEST benchmarking tools, a test program which uses the SEACAS/Trilinos IOSS library, and the checkpointing activity performed by the LAMMPS molecular dynamics simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Toroidal States of the 12 C Nucleus

Among the states of 12 C, there is an important subset of $K$ = 0 and $K$ = I planar intrinsic states in which the intrinsic motion of the nucleons are confined in the planar region defined by the three-alpha cluster or by their generated toroid. The intrinsic nuclear densities of these states are toroidal in nature. In this work we study these 12 C toroidal states from the generator-coordinate viewpoints in both the alpha cluster model and the toroidal shell model. Numerical solutions in the toroidal mean field approximation are examined to pave the way for future extensions and refinements.

12C Hoyle state↗
DOE OSTI2021

Molecular dynamics simulation of the effect of cooling rate on the structure and properties of lithium disilicate glass

The effects of cooling rate on the structure and properties of lithium disilicate (LS2) glass are investigated using molecular dynamics (MD) computer simulations. The evolution of structural features such as pair distribution function, bond angle distribution, and Li coordination distribution are determined, and correlated with dynamic and static properties to elucidate the effects of cooling rate. The density, elastic moduli, and diffusion coefficient are found to be highly sensitive to cooling rate, whereas the Si pair distribution function and bond angle distribution are weakly affected by the cooling rate. Additionally, the changes of Si-O-Si bond angle and Li coordination number suggest the formation of Li cluster at lower cooling rates. Furthermore, by comparing results from other simulations and reported experiments, we confirm that the increase of cooling rate leads to an increase of conductivity and a decrease of density. Finally, at very high cooling rates, we find that all the atoms in LS2-glass do not relax simultaneously, but do so in two distinct configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Porous Semiconducting K–Sn–Mo–S Aerogel: Synthesis, Local Structure, and Ion-Exchange Properties

Chalcogenide-based aerogels are emerging porous semiconducting nanomaterials that appeal to applications in clean energy and the environment. Here, we report a novel gel, potassium–tin–molybdenum–sulfides (KTMS), that integrates the electrostatically bound K + ions in the covalent network of Sn–Mo–S. Its gelation requires a concurrent reduction of Mo 6+ → Mo 4+/5+ and the oxidation of S 2– → Sn – (n ≈ 1) and Sn 2+ → Sn 4+ . KTMS is an amorphous semiconductor showing quantum confinement effects on band gap energies, 2.1 → 1.4 → 0.9 eV for its wet- → aero- → xerogels. Synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS) revealed a complex local structure of KTMS consisting of molecular Mo 2 (S 2 ) 6 and Mo 3 S(S 2 ) 6 clusters. In addition, the Sn–S coordination is related to crystalline Na4Sn3S8 and SnS2. KTMS also demonstrated the removal of the radionuclides of Cs + , Sr 2+ , and UO 2 2+ from ppm to ppb levels with distribution constants (Kd) up to ≥104 mL/g. Notably, despite the lack of atomic periodicity in the amorphous KTMS, the K+ ion is ion-exchangeable with chemically diverse Sr 2+ , Cs + , and UO 2 2+ in aqueous solutions; especially the ion-exchange properties of Sr 2+ and UO 2 2+ ≡(O=U=O) 2+ is not known to any chalcogels known to date. The sequestration of Cs + and Sr 2+ was achieved by the exchange of K + in the amorphous KTMS, and the removal of [O=U 6+ =O] 2+ synergistically involves surface sorption via -S····U 6+ =O 2 2+ covalent interactions and ion-exchange via the hard–soft Lewis acid–base paradigm. Overall, cooperative roles played by the diverse bonding motifs, surface-exposed Lewis basic frameworks, and polarizability of the (poly)sulfides make it an exceptional adsorbent for chemically diverse radioactive species. This finding will guide the design of superior sorbents for chemically distinct metal ion separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

ReaxFF molecular dynamics simulations of electrolyte–water systems at supercritical temperature

We have performed ReaxFF molecular dynamics simulations of alkali metal–chlorine pairs in different water densities at supercritical temperature (700 K) to elucidate the structural and dynamical properties of the system. The radial distribution function and the angular distribution function explain the inter-ionic structural and orientational arrangements of atoms during the simulation. The coordination number of water molecules in the solvation shell of ions increases with an increase in the radius of ions. We find that the self-diffusion coefficient of metal ions increases with a decrease in density under supercritical conditions due to the formation of voids within the system. The hydrogen bond dynamics has been interpreted by the residence time distribution of various ions, which shows Li+ having the highest water retaining capability. The void distribution within the system has been analyzed by using the Voronoi polyhedra algorithm providing an estimation of void formation within the system at high temperatures. We observe the formation of salt clusters of Na+ and K+ at low densities due to the loss of dielectric constants of ions. The diffusion of ions gets altered dramatically due to the formation of voids and nucleation of ions in the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts

In this work, we present NENCI-2021, a benchmark database of ~8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation–π and anion–π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.7× to 1.1× the equilibrium separation) and nine intermolecular angles per distance (five for each ion–π complex), yielding an extensive database of 7763 benchmark intermolecular interaction energies (E int ) obtained at the coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory. The E int values in NENCI-2021 span a total of 225.3 kcal/mol, ranging from -38.5 to +186.8 kcal/mol, with a mean (median) E int value of -1.06 kcal/mol (-2.39 kcal/mol). In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent—these interactions, in particular, pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed symmetry-adapted perturbation theory (SAPT)- based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021, which now includes a significant number of primarily induction-bound dimers (e.g., cation–π complexes). NENCI-2021 thus spans all regions of the SAPT ternary diagram, thereby warranting a new four-category classification scheme that includes complexes primarily bound by electrostatics (3499), induction (700), dispersion (1372), or mixtures thereof (2192). A critical error analysis performed on a representative set of intermolecular complexes in NENCI-2021 demonstrates that the E int values provided herein have an average error of ±0.1 kcal/mol, even for complexes with strongly repulsive E int values, and maximum errors of ±0.2–0.3 kcal/mol (i.e., ~±1.0 kJ/mol) for the most challenging cases. For these reasons, we expect that NENCI-2021 will play an important role in the testing, training, and development of next-generation classical and polarizable force fields, density functional theory approximations, wavefunction theory methods, and machine learning based intra- and inter-molecular potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Proton Dissociation and Delocalization under Stepwise Hydration of Zeolite HZSM-5

The protonation behavior of zeolite Brønsted acid sites (BAS) in the presence of water is important for the performance of these widely used catalysts. Despite extensive study, the number of water molecules necessary for deprotonation is not well understood, in large part because experiments have been unable to access this information. In this work, we report experimental evidence for full deprotonation of the BAS in the presence of two or more water molecules, with a deprotonation energy of 1.6 kcal/mol. Linear IR absorption and 2D IR spectra were measured over a wide range of controlled hydration levels from 0.5 to 8.0 equivalents of H 2 O/Al at a constant temperature. Distinct spectral signatures of the protonated BAS and excess proton are identified, and their hydration dependence is analyzed quantitatively. Using the experiment as a benchmark, ab initio molecular dynamics simulations are reported that reproduce the experimental trends in the protonation state and IR spectra. The proton charge position and delocalization are quantified in clusters of 1–8 H 2 O molecules using the recently developed rCEC method. This analysis provides insight into the proton structure in confined water clusters, showing that the excess charge remains relatively localized between two oxygen atoms across the hydration range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Nuclear short-range correlations and the zero-energy eigenstates of the Schrödinger equation

Here, we present a systematic analysis of the nuclear two- and three-body short-range correlations and their relations to the zero-energy eigenstates of the Schrödinger equation. To this end we analyze the doublet and triplet coupled-cluster amplitudes in the high momentum limit, and show that they obey universal equations independent of the number of nucleons and their state. Furthermore, we find that these coupled-cluster amplitudes coincide with the zero-energy Bloch-Horowitz operator. These results illuminate the relations between the nuclear many-body theory and the generalized contact formalism, introduced to describe the nuclear two-body short range correlations, and they might also be helpful for general coupled-cluster computations as the asymptotic part of the amplitudes is given and shown to be universal.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Molecular dynamics studies of lattice defect effects on tritium diffusion in zirconium

Tritium diffusion in α-Zr containing point defects such as vacancies or self-interstitial atoms (SIAs) is simulated using molecular dynamics. Point defects rapidly aggregate to form extended defects, such as 3D nanoclusters and Frank loops. The geometry of extended defects is affected by the presence of tritium. At low temperature and in the absence of tritium, vacancies aggregate to form stacking fault pyramids. Addition of tritium at these temperatures promotes aggregation of vacancies to form 3D nanoclusters, within which the tritium concentration can be sufficiently high to suggest that these defects may serve as nucleation sites for hydride precipitation. Trapping of tritium in vacancy nanocluster reduces the calculated bulk diffusivity by an amount proportional to the vacancy concentration. At high temperature, vacancy clusters change shape to form planar basal dislocation loops, which bind tritium less strongly, leading to a sharp reduction in the fraction of trapped tritium and a corresponding increase in tritium diffusivity at high temperature. In contrast, SIAs increase tritium diffusion through α-Zr. Analysis of atomic trajectories shows that tritium does not interact directly with SIAs. In conclusion, diffusion enhancement is instead related to expansion of the lattice.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A nearsighted force-training approach to systematically generate training data for the machine learning of large atomic structures

A challenge of atomistic machine-learning (ML) methods is ensuring that the training data are suitable for the system being simulated, which is particularly challenging for systems with large numbers of atoms. Most atomistic ML approaches rely on the nearsightedness principle (“all chemistry is local”), using information about the position of an atom’s neighbors to predict a per-atom energy. Here, in this work, we develop a framework that exploits the nearsighted nature of ML models to systematically produce an appropriate training set for large structures. We use a per-atom uncertainty estimate to identify the most uncertain atoms and extract chunks centered around these atoms. It is crucial that these small chunks are both large enough to satisfy the ML’s nearsighted principle (that is, filling the cutoff radius) and are large enough to be converged with respect to the electronic structure calculation. We present data indicating when the electronic structure calculations are converged with respect to the structure size, which fundamentally limits the accuracy of any nearsighted ML calculator. These new atomic chunks are calculated in electronic structures, and crucially, only a single force—that of the central atom—is added to the growing training set, preventing the noisy and irrelevant information from the piece’s boundary from interfering with ML training. The resulting ML potentials are robust, despite requiring single-point calculations on only small reference structures and never seeing large training structures. We demonstrated our approach via structure optimization of a 260-atom structure and extended the approach to clusters with up to 1415 atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗