Search NASA⌕ Search

SEARCH · Search NASA

Results for “structural ordering”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthesis and characterization of properties of (Tb1/3Mo2/3)2AlC polycrystalline

When molecules, atoms, or ions are grouped in a highly ordered microscopic structure to form a crystal lattice that stretches in all directions, the result is a solid material known as a crystal or crystalline solid. They are arranged in a highly ordered microscopic structure to form a crystal lattice. The smallest group of particles in material that constitutes this repeating pattern is unit cell of the structure. The unit cell is a repeating unit formed by the vectors spanning the points of a lattice.

Bretana, Alex↗
DOE OSTI2021

A systematic approach to generating accurate neural network potentials: the case of carbon

Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, sampled adequately from an often unknown potential energy surface. Here we propose a self-consistent approach that is based on crystal structure prediction formalism and is guided by unsupervised data analysis, to construct an accurate, inexpensive, and transferable artificial neural network potential. Using this approach, we construct an interatomic potential for carbon and demonstrate its ability to reproduce first principles results on elastic and vibrational properties for diamond, graphite, and graphene, as well as energy ordering and structural properties of a wide range of crystalline and amorphous phases.

Chemistry↗
DOE OSTI2023

Enhancing Organic Semiconductor Molecular Packing Using Perovskite Interfaces to Improve Singlet Fission

Singlet fission, a process by which one singlet exciton is converted into two lower energy triplet excitons, is sensitive to the degree of electronic coupling within a molecular packing structure. Variations in molecular packing can be detrimental to triplet formation and triplet–triplet separation, ultimately affecting the harvesting of triplets for electricity in organic photovoltaic devices. Here, six phase-pure molecular packing structures of 6,13-bis(triisopropylsilylethynyl)pentacene (TIPS-pentacene) with varying optoelectronic properties are isolated using 2D lead halide perovskites as tunable, crystalline surfaces for crystallization. Transient absorption spectroscopy reveals that while triplet formation is fast (<100 fs) regardless of template structure, the increased ordering in perovskite-templated samples speeds up triplet–triplet separation and recombination, providing evidence that the benefits of phase-purity offset minor variations in molecular packing. Molecular dynamics modeling of the interface reveals that perovskite-templating allows for closer packing of TIPS-pentacene molecules for all perovskite templates. With an extensive number of organic molecule-perovskite pairings, this work provides a methodology to use ordered, periodic surfaces to elucidate structure–property relationships of small organic molecules in order to adjust structural or optoelectronic responses, such as molecular packing and singlet fission.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Higher-Order VLP-Based Protein Macromolecular Framework Structures Assembled via Coiled-Coil Interactions

Hierarchical organization is one of the fundamental features observed in biological systems that allows for efficient and effective functioning. Virus-like particles (VLPs) are elegant examples of a hierarchically organized supramolecular structure, where many subunits are self-assembled to generate the functional cage-like architecture. Utilizing VLPs as building blocks to construct two- and three-dimensional (3D) higher-order structures is an emerging research area in developing functional biomimetic materials. VLPs derived from P22 bacteriophages can be repurposed as nanoreactors by encapsulating enzymes and modular units to build higher-order catalytic materials via several techniques. In this study, we have used coiled-coil peptide interactions to mediate the P22 interparticle assembly into a highly stable, amorphous protein macromolecular framework (PMF) material, where the assembly does not depend on the VLP morphology, a limitation observed in previously reported P22 PMF assemblies. Many encapsulated enzymes lose their optimum functionalities under the harsh conditions that are required for the P22 VLP morphology transitions. Therefore, the coiled-coil-based PMF provides a fitting and versatile platform for constructing functional higher-order catalytic materials compatible with sensitive enzymes. Finally, we have characterized the material properties of the PMF and utilized the disordered PMF to construct a biocatalytic 3D material performing single- and multistep catalysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structural changes upon magnetic ordering in magnetocaloric AlFe 2 B 2

With a Curie temperature just above room temperature, AlFe 2 B 2 is a useful magnetocaloric material composed of earth-abundant elements. Here, we employ temperature-dependent high-resolution synchrotron X-ray diffraction to establish with high certainty that the paramagnetic to ferromagnetic transition in AlFe 2 B 2 is of second order, showing no discontinuity in lattice parameters or cell volume. Nevertheless, the lattice parameters undergo anisotropic changes across the transition with distinct differences in the thermal expansion coefficients. While the $a$ and $b$ lattice parameters show a positive thermal expansion, $c$ shows a negative thermal expansion. We link these changes to the respective interatomic distances to determine the contribution of magnetism to the anisotropic structural evolution. The work underpins the possible role of magnetostructural coupling in driving the magnetocaloric effect in AlFe 2 B 2 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The influence of hydrostatic pressure and annealing conditions on the magnetostructural transitions in MnCoGe

In this work, the phase transitions of stoichiometric MnCoGe alloys were studied by systematically varying the annealing conditions and applying hydrostatic pressure. First-order martensitic structural transitions from the Ni2In-type hexagonal austenite phase to the TiNiSi-type orthorhombic martensite phase spanned a wide temperature window (>200 K) as a result of quenching the samples at temperatures ranging from the solid phase at 700 °C to the liquid phase at 1150 °C. Despite the large variation in their structural transition temperatures, the changes in cell parameters across the structural transitions and the Curie–Weiss temperatures of the martensite/austenite phase were relatively small. For the sample quenched from 800 °C, coupled magnetostructural transitions were observed, and the largest maximum magnetic entropy change was found to be -ΔS max = 33:6 J/kg K for a 7-T field change. The coupled magnetostructural transitions and the corresponding magnetic entropy enhancements were found to also be achievable by applying hydrostatic pressures. Meanwhile, as the quenching temperatures or hydrostatic pressures increased, the first-order martensitic structural transition shifted toward lower temperature until it was ultimately absent, in which case only the crystal structure and magnetic transition of the Ni 2 In-type hexagonal austenite phase were present.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

BaCu 4/3 Si 2/3 P 2 and BaCu 2–( x + y ) Zn x Si y P 2 : Expanding the Semiconducting Landscape in the ThCr 2 Si 2 -Type Family

ThCr 2 Si 2 -type layered materials are a large family of compounds with applications ranging from thermoelectricity to magnetism, with the vast majority of the members exhibiting metallic behavior. Here, in this study, we synthesized a new group of materials with Cu-Si and Cu-Zn-Si square nets with the general formula BaCu 1.33 Si 0.67 P 2 and BaCu 2–(x+y) Zn x Si y P 2 (0 ≤ x ≤ 0.9; 0.3 ≤ y ≤ 0.7). Several synthesized compounds are charge-balanced semiconductors, which are rare in the ThCr 2 Si 2 family. All the reported compounds crystallize in the ThCr 2 Si 2 -type tetragonal I4/mmm space group, with Cu/Zn/Si jointly occupying the same 4d crystallographic site. In the Zn-free composition, BaCu 1.33 Si 0.67 P 2 , Ba, and P each occupy a single crystallographic site. The introduction of Zn results in the expansion of the unit cell and splitting the Ba atomic sites along the [001] direction. Such structural displacement of the Ba atoms was confirmed by the heat capacity measurements. Band structure and density-of-states calculations on ordered hypothetical structural models reveal either a small bandgap (∼0.2 eV) or semimetallic band structures. The compounds reported here exhibit high Seebeck coefficients and ultralow thermal conductivity, making them promising candidates for the development of thermoelectric materials.

crystal structure↗
DOE OSTI2024

Ordered porous solid electrolyte structures, electrochemical devices with same, methods of making same

Provided are solid-state electrolyte structures. The solid-state electrolyte structures are ion-conducting materials. The solid-state electrolyte structures may be formed by 3-D printing using 3-D printable compositions. 3-D printable compositions may include ion-conducting materials and at least one dispersant, a binder, a plasticizer, or a solvent or any combination of one or more dispersant, binder, plasticizer, or solvent. The solid-state electrolyte structures can be used in electrochemical devices.

Wachsman, Eric D.↗
DOE OSTI2025

Block-Structured Operator Inference for Coupled Multiphysics Model Reduction

This work presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the governing equation structure for each physics component and the structure of the coupling terms. Once the multiphysics structure is specified, the reduced-order model is learned from snapshot data following the nonintrusive Operator Inference methodology. In addition to preserving physical system structure, which in turn permits preservation of system properties such as stability and second-order structure, the block-structured approach has the advantages of reducing the overall dimensionality of the learning problem and admitting tailored regularization for each physics component. The numerical advantages of the block-structured formulation over a monolithic Operator Inference formulation are demonstrated for aeroelastic analysis, which couples aerodynamic and structural models. For the benchmark test case of the AGARD 445.6 wing, block-structured Operator Inference provides an average 20% online prediction speedup over monolithic Operator Inference across subsonic and supersonic flow conditions in both the stable and fluttering parameter regimes while preserving the accuracy achieved with monolithic Operator Inference.

42 ENGINEERING↗
DOE OSTI2024

Structure transition and zigzag magnetic order in Ir/Rh-substituted honeycomb lattice α - RuCl 3

Here, we report magnetization and neutron diffraction studies on crystal and magnetic structures of Ir- and Rh-substituted honeycomb lattice α-RuCl 3 . The iridium or rhodium atoms are distributed at the Ru site with little structural modification. Both systems undergo a room-temperature monoclinic C2/m to low-temperature trigonal $R\bar{3}$ phase transformation with a large recoverable hysteresis. At low temperature, a zigzag spin order is observed with the same characteristic wave vector (0,0.5,1) as in the parent α-RuCl 3 . Detailed magnetic structure refinement reveals an ordered moment of 0.32(5)µB/Ru and an upper boundary of canting angle of 15(4)º away from the basal plane at 5 K for the 10% Ir-substituted α-RuCl 3 , which is different from the 0.45–0.73 µB/Ru and 32°–48° canting angle reported in the parent compound α-RuCl 3 . The observation of unchanged RuCl 6 local octahedral environment, reduced ordered magnetic moment size and canting angle compared to previously reported highlights the potential to study quantum spin-liquid behavior through nonmagnetic ion doping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The seventh blind test of crystal structure prediction: structure ranking methods

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol −1 at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases.

Chemistry↗
DOE OSTI2020

Structure and properties of densified silica glass: characterizing the order within disorder

The broken symmetry in the atomic-scale ordering of glassy versus crystalline solids leads to a daunting challenge to provide suitable metrics for describing the order within disorder, especially on length scales beyond the nearest neighbor that are characterized by rich structural complexity. Here, we address this challenge for silica, a canonical network-forming glass, by using hot versus cold compression to (i) systematically increase the structural ordering after densification and (ii) prepare two glasses with the same high-density but contrasting structures. The structure was measured by high-energy X-ray and neutron diffraction, and atomistic models were generated that reproduce the experimental results. The vibrational and thermodynamic properties of the glasses were probed by using inelastic neutron scattering and calorimetry, respectively. Traditional measures of amorphous structures show relatively subtle changes upon compacting the glass. The method of persistent homology identifies, however, distinct features in the network topology that change as the initially open structure of the glass is collapsed. The results for the same high-density glasses show that the nature of structural disorder does impact the heat capacity and boson peak in the low-frequency dynamical spectra. Densification is discussed in terms of the loss of locally favored tetrahedral structures comprising oxygen-decorated SiSi 4<:sub> tetrahedra.

36 MATERIALS SCIENCE↗