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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Crashworthiness of recycled carbon fiber composite sinusoidal structures at dynamic rates

Fiber reinforced polymer composites are finding applications in the automotive space for structurally critical applications including crash management. The use of recycled carbon fiber reinforcement can greatly reduce carbon emissions. In this study, recycled carbon fiber composites were manufactured into a self-supporting geometry using three matrices: polyphenylene sulfide (PPS), acrylonitrile butadiene styrene (ABS), and a structural epoxy, and subsequently crushed between flat platens at dynamic rates ranging from 4.6 to 9.1 ms -1 at temperatures in a range of -40°C to 80°C. Load-displacement data was used to evaluate their specific energy absorption, crush efficiency, and steady-state crush stress. Further, the energy absorption of the ABS composites was strongly sensitive to temperature, while the PPS composites exhibited strong crush efficiency dependence with both rate and temperature. The epoxy composites exhibited stable crush behavior at dynamic crush rates but exhibited a dramatic reduction in crush efficiency relative to quasi-static tests. The results of this study indicate that recycled fiber composites can achieve very high energy absorption levels (50–80kJkg -1 at room temperature) that make them an excellent alternative to more expensive and less environmentally friendly continuous virgin fiber laminates.

42 ENGINEERING↗
DOE OSTI2022

Latent-Space Dynamics for Prediction and Fault Detection in Geothermal Power Plant Operations

This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-step-ahead prediction and fault detection of a geothermal power plant’s operation. The model was trained to learn the dynamics of the power generation process from multivariate time-series data and the effects of exogenous variables, such as control adjustment and ambient temperature. In the LSDNN model, an encoder–decoder architecture was designed to capture cross-correlation among different measured variables. In addition, a latent space dynamic structure was proposed to propagate the dynamics in the latent space to enable prediction. The prediction power of the LSDNN was utilized for monitoring a geothermal power plant and detecting abnormal events. The model was integrated with principal component analysis (PCA)-based process monitoring techniques to develop a fault-detection procedure. The performance of the proposed LSDNN model and fault detection approach was demonstrated using field data collected from a geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Ternary Phosphides Ba M 2 P 2 : Tailoring Crystal and Electronic Structures Enables Highly Efficient HER Electrocatalysis

Binary transition metal phosphides and their solid solutions have emerged as promising hydrogen evolution reaction (HER) catalysts. Although many research endeavors have adopted strategies to vary compositions to optimize catalytic performance, they mainly focus on binary structures, which represent only a small fraction of the abundant phase space of structure types among transition metal phosphides. Here, the largely unexplored class of ternary and multinary ordered phosphides in catalysis comprises two or more metals with quite different chemical nature, concealing the structure–property relationships essential for advancing catalyst design. Here, we explored phosphides crystallizing in one of the most abundant ordered intermetallic structure types, —the ThCr 2 Si 2 type, —where square nets of 3d transition metal M and P atoms are separated by layers of electropositive Ba cations. Four ternary BaM 2 P 2 (M = Fe, Fe/Cu, Fe/Ni, Ni) catalysts were synthesized and characterized. BaNi 2 P 2 showed high HER activity in acidic electrolyte, which required an overpotential, η 10 , of only 62 mV to drive current density j = –10 mA/cm 2 and high stability with a potential drop rate of 0.25 mV/h. BaNi 2 P 2 outperformed other Ni-based catalysts, such as Ni 2 P and Ni 5 P 4 . Notably, at current densities above –170 mA/cm 2 , BaNi 2 P 2 outperformed the standard Pt electrode measured under identical conditions. Electronic structure analysis revealed a volcano-type activity trend among the four BaM 2 P 2 catalysts based on their d-band center positions, highlighting the role of electropositive Ba cations in shifting the Ni-3d orbitals into an optimal position.

BaNi2P2↗
DOE OSTI2024

Compensation of Third-order Resonances in the High Intensity Regime

As the Fermilab Accelerator Complex enters the high-intensity era, the Recycler Ring (RR) needs to mitigate the detrimental effect of third-order resonance crossing. Third-order resonance lines can be compensated to first order by cancelling out the global Resonance Driving Terms (RDTs) using the response matrix method. This compensation scheme has been proven to work at low intensities, i.e., in the single-particle regime. In order to evaluate the effectiveness of this compensation scheme at higher intensities, this study looks at dynamic and static tune scans, with and without resonance compensation, and different space charge tune shifts. Special care was taken in order to disentangle effects from space charge tune shift, structure resonances and space charge driven resonances.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Influence of Air and Ethanol Dehydration on Structure, Behavior, and Function of Type I Collagen Scaffolds

Ethanol dehydration is a common step in both scaffold manufacturing and tissue processing, yet the influence of ethanol on collagen is not well understood. This study examined the effects of dehydration, via ethanol treatment and air drying, on collagen structure, behavior, mechanics, and rehydration capacity. Multiple material characterization methods were used including Fourier Transform infrared spectroscopy (FTIR), Raman spectroscopy, scanning electron microscopy, thermogravimetric analysis, small/medium angle x‐ray scattering, volumetric swelling analysis, and tensile testing. Ethanol dehydration removed bulk water from scaffolds, making them stronger and stiffer, but also showed loss of molecular water. This molecular water appears to act as a collagen stabilizer, resulting in less thermally stable scaffolds. The loss of molecular water is also evident in the molecular d‐spacing. Secondary structure of scaffolds was also altered by ethanol, resulting in significantly enhanced rehydration capacity. Bulk water, both before and after rehydration, largely determined mechanical properties, which did not correlate with other structural measures such as FTIR. While rehydration largely returned collagen spacing to pre‐ethanol treated state, structural alterations seen in FTIR cannot be recovered. These results have implications for not only collagen scaffolds, but in many tissue engineering and processing applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Real-space solution to the electronic structure problem for nearly a million electrons

We report a Kohn–Sham density functional theory calculation of a system with more than 200 000 atoms and 800 000 electrons using a real-space high-order finite-difference method to investigate the electronic structure of large spherical silicon nanoclusters. Our system of choice was a 20 nm large spherical nanocluster with 202 617 silicon atoms and 13 836 hydrogen atoms used to passivate the dangling surface bonds. To speed up the convergence of the eigenspace, we utilized Chebyshev-filtered subspace iteration, and for sparse matrix–vector multiplications, we used blockwise Hilbert space-filling curves, implemented in the PARSEC code. For this calculation, we also replaced our orthonormalization + Rayleigh–Ritz step with a generalized eigenvalue problem step. We utilized all of the 8192 nodes (458 752 processors) on the Frontera machine at the Texas Advanced Computing Center. We achieved two Chebyshev-filtered subspace iterations, yielding a good approximation of the electronic density of states. Our work pushes the limits on the capabilities of the current electronic structure solvers to nearly 106 electrons and demonstrates the potential of the real-space approach to efficiently parallelize large calculations on modern high-performance computing platforms.

Chemistry↗
DOE OSTI2020

Time scales for nonlinear processes in preheating after multifield inflation with nonminimal couplings

We have conducted extensive lattice simulations to study the postinflation dynamics of multifield models involving nonminimal couplings. In this work, we explore the parameter dependence of preheating in these models and describe the various time scales that control such nonlinear processes as energy transfer, rescattering, and the approach to radiation domination and thermalization. In the limit of large nonminimal couplings ($ξ_I$ ~ 100), we find that efficient transfer of energy from the inflaton condensate to radiative degrees of freedom, emergence of a radiation-dominated equation of state, and the onset of thermalization each consistently occur within $N_{\text{reh}} ≲ 3 e$-folds after the end of inflation, largely independent of the values of the other couplings in the models. The exception is the case of negative ellipticity, in which there is a misalignment between the dominant direction in field space along which the system evolves and the larger of the nonminimal couplings $ξ_I$. In those cases, the field-space-driven parametric resonance is effectively shut off. More generally, the competition between the scalar fields’ potential and the field-space manifold structure can yield interesting phenomena such as two-stage resonances. Across many regions of parameter space, we find efficient re-scattering between the distinct fields, leading to a partial memory loss of the shape of the initial fluctuation spectrum. Despite the explosive particle production, which can lead to a quick depletion of the background energy density, the nonlinear processes do not induce any superhorizon correlations after the end of inflation in these models, which keeps predictions for cosmic microwave background observables unaffected by the late-time amplification of isocurvature fluctuations. Hence the excellent agreement between primordial observables and recent observations is preserved for this class of models, even when we consider postinflation dynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

On the structure of isometrically embeddable metric spaces

Since its popularization in the 1970s, the Fiedler vector of a graph has become a standard tool for clustering of the vertices of the graph. Recently, Mendel and Noar, Dumitriu and Radcliffe, and Radcliffe and Williamson have introduced geometric generalizations of the Fiedler vector. Motivated by questions stemming from their work, we provide structural characterizations for when a finite metric space can be isometrically embedded in a Hilbert space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine learning and algebraic approaches towards complete matter spectra in 4d F-theory

Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generate 1.8 million pairs of line bundles and curves embedded in dP 3 , for which we compute the cohomologies. A white-box machine learning approach trained on this data provides intuition for jumps due to curve splittings, which we use to construct additional vector-like Higgs-pairs in an F-Theory toy model. We also find that, in order to explain quantitatively the full dataset, further tools from algebraic geometry, in particular Brill-Noether theory, are required. Using these ingredients, we introduce a diagrammatic way to express cohomology jumps across the parameter space of each family of matter curves, which reflects a stratification of the F-theory complex structure moduli space in terms of the vector-like spectrum. Furthermore, these insights provide an algorithmically efficient way to estimate the possible cohomology dimensions across the entire parameter space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Crystal structure of the $τ_{11}$ Al 4 Fe 1.7 Si phase from neutron diffraction and ab initio calculations

The intermetallic τ 11 Al 4 Fe 1.7 Si phase is of interest for high-temperature structural application due to its combination of low density and high strength. We determine the crystal structure of the τ 11 phase through a combination of powder neutron diffraction and density functional theory calculations. Using Pawley and Rietveld refinements of the neutron diffraction data provides an initial crystal structure model. Since Al and Si have nearly identical neutron scattering lengths, we use density-functional calculations to determine their preferred site occupations. The τ 11 phase exhibits a hexagonal crystal structure with space group P6 3 /mmc and lattice parameters of a = 7.478 Å and c = 7.472 Å. The structure comprises five Wyckoff positions; Al occupies the 6h and 12k sites, Fe the 2a and 6h sites, and Si the 2a sites. Here we observe site disorder and partial occupancies on all sites with a large fraction of 80% Fe vacancies on the 2d sites, indicating an entropic stabilization of the τ 11 phase at high temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design, Selection, and Evaluation of Reinforcement Learning Single Agents for Ground Target Tracking

Previous approaches for small fixed-wing unmanned air systems that carry strapdown rather than gimbaled cameras achieved satisfactory ground target tracking performance using both standard and deep reinforcement learning algorithms. However, these approaches have significant restrictions and abstractions to the dynamics of the vehicle, such as constant airspeed and constant altitude, because the number of states and actions was necessarily limited. Thus, extensive tuning was required to obtain good tracking performance. The expansion from 4 state–action degrees of freedom to 15 enabled the agent to exploit previous reward functions that produced novel yet undesirable emergent behavior. This paper investigates the causes of and various potential solutions to undesirable emergent behavior in the ground target tracking problem. A combination of changes to the environment, reward structure, action space simplification, command rate, and controller implementation provides insight into obtaining stable tracking results. Consideration is given to reward structure selection and refinement to mitigate undesirable emergent behavior. Results presented in the paper for a simulated environment of a single unmanned air system tracking a randomly moving single ground target show that a soft actor–critic algorithm can produce feasible tracking trajectories without limiting the state space and action space, provided that the environment is properly posed.

Engineering↗
DOE OSTI2025

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Synthesis, Structure, and Properties of the Complex Zintl Phase Eu 9 Zn 4.5 As 9 : A Candidate Topological Insulator and Thermoelectric Material

Reported are the synthesis and detailed analysis of the crystal and electronic structure of the novel Zintl phase Eu 9 Zn 4.5 As 9 . This material was identified in the densely populated Eu–Zn–As compositional space. For structure determination and for property measurements, suitable single crystals of this compound were grown from either Sn- or Pb-flux. Single-crystal X-ray diffraction methods indicate that Eu 9 Zn 4.5 As 9 crystallizes in the orthorhombic crystal system with the space group Pnma (a = 12.1953(7) Å, b = 4.3730(2) Å, c = 42.674(2) Å) and is formally isostructural to Ca 9 Mn 4+x Sb 9 , the less common “9–4–9” type. The structure is heavily disordered, with multiple partially occupied sites, yet, according to the Zintl-Klemm formalism, a charge-balanced composition (Eu 2+ ) 9 (Zn 2+ ) 4.5 (As 3− ) 9 is attained. Electronic structure calculations for a model, disorder-free structure indicate no energy gap between the valence and the conduction bands and suggest (semi)metallic behavior. Preliminary susceptibility measurements confirm the expected divalent nature of Eu 2+ ([Xe] 4 f 7 ground state).

Zintl phases↗
DOE OSTI2023

An extended Vlasov–Fokker–Planck approach for kinetic simulations of laser plasmas

Vlasov–Fokker–Planck simulation codes occupy an important niche in modeling laser-produced plasmas, since they are well suited to studying the effect of collisions on electron kinetic phenomena, especially energy transport. One of the most important elements of energy transport is the absorption of laser light by the plasma; however, simulating this in detail requires resolving oscillations of the laser light, whose characteristic timescale is orders of magnitude shorter than the simulation time needed to study transport physics. For this reason, most Vlasov–Fokker–Planck codes used to study electron transport in laser plasmas rely on simplified models of the laser–plasma coupling. Their underlying assumptions nominally preclude their use for modeling laser light having short-scale structure in space or time, such as broadband lasers. In this work, we derive a more general computational framework suitable for arbitrarily structured laser fields. Furthermore, our approach is based on an extended set of Vlasov–Fokker–Planck equations that separately solve for the low- and high-frequency plasma response. We implement these extended Vlasov–Fokker–Planck equations in the spherical harmonic code K2 and demonstrate the performance of the method on several laser absorption test problems, with particular attention to the judicious selection of time steps, time integrators, and spherical harmonic truncation, according to the intensity and spectrum of the laser light under consideration. Comparison with the widely used Langdon absorption operator shows the Langdon operator performs remarkably well for predicting laser heating in the simple cases considered here, even in situations that would seem to violate its underlying assumptions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Materials design, synthesis, and transport properties of disordered rare-earth Zintl bismuthides with the anti -Th 3 P 4 structure type

The synthesis, structural elucidation, and transport properties of the extended series Ca 4–x RE x Bi 3 (RE = Y, La–Nd, Sm, Gd–Tm, and Lu; x ≈ 1) and Ca 4–x RE x Bi 3–δ Sb δ (RE = La, Ho, Er, and Lu; x ≈ 1, δ ≈ 1.5) are presented. Structural elucidation is based on single-crystal X-ray diffraction data and confirms the chemical drive of Ca4Bi3 with the cubic anti-Th 3 P 4 structure type (space group I4 ¯3d, no. 220, Z = 4) into a Zintl phase by the introduction of trivalent rare-earth atoms. The structure features complex bonding, heavy elements, and electron count akin to that of valence-precise semiconductors, making it an ideal target for thermoelectrics development. Introducing crystallographic site disorders at the cation site for the Ca 4–x RE x Bi 3 phase and both the cation and anion sites for the Ca 4–x RE x Bi 3–δ Sb δ phase brings about additional desirable characteristics for thermoelectric materials in the context of tuning knobs for lowering thermal conductivity. Electronic structure calculations of idealized Ca 3 YBi 3 and Ca 3 LaBi 3 compounds indicate the opening of indirect bandgaps at the Fermi level with magnitudes Eg = 0.38 eV and 0.57 eV, respectively. The electrical resistivity ρ(T) of some of the investigated phases measured on single crystals evolve in a metallic manner with magnitudes of order 1.4 mΩ cm near 500 K, thus supporting the notion of a degenerate semiconducting state, with the temperature dependence of the Seebeck coefficient α(T) suggesting the p-type behavior. Furthermore, the low electrical resistivity and the realization of a degenerate semiconducting state in the title phases present a window of opportunity for optimizing their carrier concentrations for enhanced thermoelectric performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine learning unifies flexibility and efficiency of spinodal structure generation for stochastic biomaterial design

Abstract Porous biomaterials design for bone repair is still largely limited to regular structures (e.g. rod-based lattices), due to their easy parameterization and high controllability. The capability of designing stochastic structure can redefine the boundary of our explorable structure–property space for synthesizing next-generation biomaterials. We hereby propose a convolutional neural network (CNN) approach for efficient generation and design of spinodal structure—an intriguing structure with stochastic yet interconnected, smooth, and constant pore channel conducive to bio-transport. Our CNN-based approach simultaneously possesses the tremendous flexibility of physics-based model in generating various spinodal structures (e.g. periodic, anisotropic, gradient, and arbitrarily large ones) and comparable computational efficiency to mathematical approximation model. We thus successfully design spinodal bone structures with target anisotropic elasticity via high-throughput screening, and directly generate large spinodal orthopedic implants with desired gradient porosity. This work significantly advances stochastic biomaterials development by offering an optimal solution to spinodal structure generation and design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Early Career: Mesoscale Fragments of Crystalline Silicon by Chemical Synthesis (Final Technical Report)

Silicon has transformed the modern era, with applications in computing, solar cells, energy storage, and beyond. The traditional approach to making silicon is a high-temperature “top-down” process that affords only the most stable form of silicon, leaving hidden vast swathes of structure-function space. The goal of this program was to establish new approaches to making silicon-based materials from the bottom-up, allowing structural precision from the atomic level up to the bulk, and to understand how structure influences function. Key results included the development of the cyclosilane building blocks and low-temperature methods for their polymerization, as well as new tools for spectroscopic characterization. In addition to revealing new materials chemistry insights, in the five-year period covered by this award, this work resulted in 11 publications and three graduate student theses.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bismuth as a Reactive Solvent in the Synthesis of Multicomponent Transition-Metal-Bearing Bismuthides

Employment of liquid bismuth (Bi) allows the facile single-crystal growth of compounds containing elements with high melting points, provided that these elements have reasonably high solubility in Bi. Utilization of the Bi flux approach yielded two new ternary bismuthides, SrNi 0.17(1) Bi 2 [a defect variant of the BaCuSn 2 type, space group Cmcm , α = 4.879(2) Å, b = 17.580(6) Å, and c = 4.696(2) Å] and CaTi 3 Bi 4 [NdTi 3 (Sn 0.1 Sb 0.9 ) 4 structure type, space group Fmmm , a = 5.6295(7) Å, b = 9.8389(1) Å, and c = 23.905(3) Å]. In addition, the ternary antimonide CaV3Sb4, isostructural with CaTi 3 Bi 4 , was synthesized from antimony (Sb) flux, and analyzed with the goal of validating structural assessment of the bismuthide analogue, where the X-ray crystallographic work proved to be very challenging. All synthesized compounds exhibit complex crystal structures featuring quasi-two-dimensional building blocks of different topologies. First-principle calculations reveal hypervalent bonding in the homoatomic Bi subunits. Lastly, physical property measurements indicate metallic conductivity and the absence of localized magnetism in the studied compounds.

36 MATERIALS SCIENCE↗