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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The Multi-Mission Earth Entry Vehicle for Sample Return Missions – Past, Present, and Future

The Multi-Mission Earth Entry Vehicle (MMEEV) is an enabling technology developed at NASA’s Langley Research Center (LaRC) over the last two decades for returning samples to Earth across a wide array of space science missions. Currently, the MMEEV is being considered for NASA’s Mars Sample Return (MSR) mission. The original vehicle concept, the Earth Entry Vehicle (EEV), was innovated at LaRC in 1998 as a robust solution to return Mars soil samples to Earth under stringent backward contamination requirements. These backward contamination requirements drove the EEV to have higher reliability than any capsule previously designed for a return-to-Earth sample return mission. The EEV achieved this high reliability by employing a passive (no active systems) vehicle architecture optimized for fault tolerance in a compact, low-mass configuration that is extensible to virtually any sample return mission. The original EEV concept utilized a carbon-carbon primary structure with high-density carbon phenolic thermal protection system. The capsule had a 60-degree sphere-cone forebody and a backshell geometry uniquely tailored to produce aerodynamics that would passively re-orient the vehicle if it entered the atmosphere with an off-nominal attitude. Contrary to every other sample return capsule conceived at the time, the EEV was designed to land without a parachute. The vehicle incorporated an integral energy-absorbing crushable structure that protected the Mars sample for landings on surfaces ranging from soft soil to solid concrete. This paper describes 20 years of technological advancements LaRC has incorporated into the EEV architecture to evolve it from the original, MSR-enabling vehicle, to a true multi-mission capability relevant to any sample return mission. The vehicle’s unique Integrated Composite Stiffener Structure (ICoSS) has been optimized for specific strength - supporting high-G atmospheric entries with steep entry angles that produce precise landing footprints on the ground. The vehicle geometry has been refined through wind tunnel testing and computational fluid dynamics simulations to improve the vehicle’s aerodynamic stability and robustness to off-nominal conditions from hypersonic to subsonic flight. The resulting configuration of the current MMEEV architecture is described, with details provided on its sample carrying capacity and atmospheric entry trajectory capabilities. The upgraded vehicle performance is mapped into current space science objectives, showing how the MMEEV supports future sample return missions and continues to be an enabling technology for NASA’s vision to return samples from Mars.

J M Corliss↗
DOE OSTI2023

Operator inference with roll outs for learning reduced models from scarce and low-quality data

Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, often polluted with noise and affected by measurement errors and other perturbations, which makes learning the dynamics of systems challenging. Here, in this work, we propose to combine data-driven modeling via operator inference with the dynamic training via roll outs of neural ordinary differential equations. Operator inference with roll outs inherits interpretability, scalability, and structure preservation of traditional operator inference while leveraging the dynamic training via roll outs over multiple time steps to increase stability and robustness for learning from low-quality and noisy data. Numerical experiments with data describing shallow water waves and surface quasi-geostrophic dynamics demonstrate that operator inference with roll outs provides predictive models from training trajectories even if data are sampled sparsely in time and polluted with noise of up to 10%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Synthesis of nickel selenide thin films for high performance all-solid-state asymmetric supercapacitors

As a significant semiconductor, nickel selenide shows enormous potential and extensive application prospects in the field of sensor, photocatalysis and supercapacitor. In this paper, nickel selenide (Ni 3 Se 2 , NiSe) thin films were successfully fabricated on stainless-steel sheet using a facile, effective electrodeposition technique. The morphologies, microstructures and chemical compositions of the thin films are characterized systematically. Electrochemical tests exhibit that the Ni3Se2 and NiSe possess high specific capacitance of 581.1 F/g and 1644.7 F/g, respectively. A flexible, all-solid-state asymmetric supercapacitor is assembled by utilizing NiSe film as positive electrode and activated carbon as negative electrode. The solid device delivers a high areal capacitance of 27.0 mF/cm 2 at the current density of 0.7 mA/cm 2 . Furthermore, the maximum volumetric energy density and power density of the NiSe//AC asymmetric SCs can achieve 0.26 mWh/cm 3 and 33.35 mW/cm 3 , respectively. The device shows robust cycling stability with 84.6% capacitance retention after 10000 cycles, outstanding flexibility and satisfactory mechanical stability. Moreover, two devices in series can light up a red light-emitting diode, which displayed great potential applications for energy storage.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Design and characterization of hierarchical aluminosilicate composite materials for Cs entrapment: Adsorption efficiency tied to microstructure

The growing quantity of nuclear waste and the serious threats to the environment challenge researchers to innovate and target new waste form technologies. In the past decades, considerable efforts have been devoted to developing highly selective sorbents followed by safe disposal with the assurance of chemical stability and robust retention performance. Zeolite-containing geopolymers are regarded as a possible 2-in-1 material able to both capture and sequester elements such as Cs in bed fixed column application perspective. Here, these composites show promise for combining extraction properties of zeolite powder due to its crystalline structure (high capacity and selective adsorption), with the tunable microstructure and the shaping feasibility of the geopolymer binder. For the development of materials devoted to Cs immobilization, porous zeolite/geopolymer composites were prepared by dispersing NaY zeolite particles in a geopolymer binder. The influence of the structural properties of such composites on their ability to entrap a large amount of Cs by an ionic exchange process was notably studied. Composites' compositions, porosities, morphologies and crystallinity were analyzed by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (SEM-EDX), x-ray diffraction analysis (XRD) and nitrogen adsorption/desorption studies. Experimental Cs sorption in batch mode was used to follow the ionic exchange phenomenon in these materials. Along with 5 wt% amount of zeolite in geopolymer improves the Cs adsorption performance offering multiple new adsorption sites. Additionally, the geopolymer mesopores are beneficial facilitating the access of Cs and its role as a binder is advantageous to tailor granular hierarchical structure for safer industrial application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fabrication of Ionic Covalent Triazine Framework-Linked Membranes via a Facile Sol–Gel Approach

Covalent triazine framework (CTF)-based membranes have shown unique properties and wide applications in energy-related fields, but there is still no efficient strategy capable of affording CTF membranes functionalized with ionic moieties, which will bring extra merits and application possibilities. In this work, a robust CTF membrane with ionic functionalities was fabricated via a sol–gel approach promoted by a superacid (FSO 3 H). The CTF skeleton was constructed via the trimerization of cyano groups in the monomer, and piperazine moieties were introduced as reactive sites for the formation of ammonium cations coupled with FSO 3 – anions within the backbone. The obtained transparent and red protonated polymeric CTF-based membrane (PP-CTF) exhibited significant absorption at 646 nm in the solid-state ultraviolet–visible diffuse reflectance spectrum. Comparatively, the neutralized deprotonated counterparts turned to yellow color with a significant blueshift absorption to 492 nm. The theoretical calculation demonstrated that PP-CTF and deprotonated polymeric CTF membrane (DP-CTF) were stable with AB-stacking mode, and PP-CTF had a smaller band gap (0.90 eV) than that of DP-CTF (2.17 eV). The significant optical absorption and emission behavior change of PP-CTF and its robust chemical stability endowed it with the capability to act as pH indicators. The synthetic pathway developed in this work and the performance of the resultant ionic membrane opens new opportunities in the aspects of membrane design, fabrication, and application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable Polymeric Few-Nanometer Organosilica Membranes with Hydrothermal Stability for Selective Hydrogen Separation

Nanoporous silica membranes exhibit excellent H 2 /CO 2 separation properties for sustainable H 2 production and CO 2 capture but are prepared via complicated thermal processes above 400 °C, which prevent their scalable production at a low cost. Here, we demonstrate the rapid fabrication (within 2 min) of ultrathin silica-like membranes (~3 nm) via an oxygen plasma treatment of polydimethylsiloxane-based thin-film composite membranes at 20 °C. The resulting organosilica membranes unexpectedly exhibit H2 permeance of 280-930 GPU (1 GPU = 3.347 x 10 -10 mol m -2 s -1 Pa -1 ) and H2/CO2 selectivity of 93-32 at 200 °C, far surpassing state-of-the-art membranes and Robeson’s upper bound for H 2 /CO 2 separation. When challenged with a 3 d simulated syngas test containing water vapor at 200 °C and a 340 d stability test, the membrane shows durable separation performance and excellent hydrothermal stability. The robust H 2 /CO 2 separation properties coupled with excellent scalability demonstrate the great potential of these organosilica membranes for economic H 2 production with minimal carbon emissions.

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

Revolutionizing Lithium Storage Capabilities in TiO 2 by Expanding the Redox Range

TiO 2 is a widely recognized intercalation anode material for lithium-ion batteries (LIBs), yet its practical capacity is kinetically constrained due to sluggish lithium-ion diffusion, leading to a lithiation number of less than 1.0 Li + (336 mAh g -1 ). Here, the growth of TiO 2 crystallites is restrained by integrating Si into the TiO 2 framework, thereby enhancing the charge transfer and creating additional active sites potentially residing at grain boundaries for Li + storage. This strategy is corroborated by the expanded redox range of Ti, as thoroughly demonstrated via synchrotron radiation-based X-ray spectroscopy and Cs-corrected electron microscopy. Consequently, when deployed for lithium storage, the tailored material achieves an extraordinarily high reversible capacity of 559 mAh g -1 , 116% of the theoretical maximum of 483 mAh g -1 calculated based on all active species, while simultaneously retaining superior rate capability and robust cycling stability. Further, this work offers fresh perspectives on the revitalization of traditional electrode materials to achieve enhanced capacities.

25 ENERGY STORAGE↗
DOE OSTI2025

Nitrogen Vacancies Induce Fatigue in Ferroelectric Al 0.93 B 0.07 N

Wurtzite ferroelectrics (e.g., Al 0.93 B 0.07 N) are being explored for high-temperature and emerging near-, or in-compute, memory architectures due to the material advantages offered by their large remanent polarization and robust chemical stability. Despite these advantages, current Al0.93B0.07N devices do not have sufficient endurance lifetime to meet roadmap targets. To identify the defects responsible for this limited endurance, a combination of electronic measurements and optical spectroscopies characterized the evolution of defect states within Al 0.93 B 0.07 N with cycling. Ultrathin (∼10 nm) metal contacts were used to optically probe regions subject to ferroelectric switching; photoluminescence spectroscopy identified the emergence of a transition near 2.1 eV whose intensity scaled with the non-switching polarization quantified via positive-up negative-down (PUND) measurements. Accompanying thermally stimulated depolarization current (TSDC) and modulus spectroscopy measurements also observed the strengthening of a state near 2.1 eV. The origin of this feature is ascribed to transitions between a nitrogen vacancy and another defect deeper in the bandgap. Recognizing that the impurity concentration is largely fixed, strengthening of this transition indicates an increase in the number of nitrogen vacancies. Switching, therefore, creates vacancies in Al 0.93 B 0.07 N likely due to hot-atom damage induced by the aggressive fields necessary to switch wurtzite materials that ultimately limits endurance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

1D topological phases in transition-metal monochalcogenide nanowires

The Su–Schrieffer–Heeger (SSH) model is a prototypical one-dimensional (1D) diatomic lattice model for non-trivial topological phases and topological excitations. In theory, many variations and extensions of the SSH model have been proposed and explored to better understand the novel aspects of topological physics in low dimensions on the nanoscale. However, the outstanding challenge remains to find real nanomaterials with robust structural stability for realizing the 1D topological states. Here, we develop an extended version of the SSH model with multi-atomic bases of four, six and eight atoms and an imposed screw rotation symmetry. Furthermore, based on first-principles calculations, we demonstrate the realization of this model in transition metal monochalcogenide M 6 X 6 (M = Mo and W; X = S, Se and Te) nanowires. The topological features of the doped M 6 X 6 nanowires are confirmed with non-trivial edge modes and e/2 fractional charges, representative of the 1D non-trivial Zak phase. Our finding not only sheds new light on our fundamental understanding of 1D topological physics, but also significantly extends the scope of 1D topological materials that will attract immediate experimental interest, since isolated M 6 X 6 nanowires have already been synthesized in experiments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

A macromolecular assembly directed ceramic aerogel monolith material

Ceramic aerogels exhibit remarkable thermal insulation for energy efficient building applications, while it is indispensable to understand their nanoporous structure evolution to control their thermal regulation performance. In this study, we design and synthesize a lightweight porous silica aerogel monolithic material, and demonstrate its thermal insulation performance regulated by the morphology of porous nanostructures controlled by surfactant induced self-assembly. The micelle networks and in situ gas bubble formation guide the formation of uniform pores in the as-synthesized monolith, which shows superior thermal and acoustic insulation and robust mechanical stability with a thermal conductivity of 0.032 W m –1 K –1 , a soundproof performance improvement by 17% at a frequency of 800 Hz, and a 1.3 MPa compressive strength with a Young's modulus of 15 MPa. Lastly, these findings provide a new route to manufacture low-cost aerogel monolithic insulation materials for energy efficient building applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

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

Amorphous zinc–molybdenum–sulfide chalcogel as a long-cycle, high-capacity electrode for lithium-ion batteries

The inherent limitations of intercalation-based electrodes in lithium-ion batteries have prompted the search for alternative materials with higher specific capacities and robust electrochemical stability. Sulfur-based electrodes, despite their high theoretical capacities (1672 mAh g −1 ), typically suffer from poor cycling performance. In this work, zinc molybdenum polysulfide (Zn x Mo 3 S 13 , 0.5 ≤ x), an amorphous semiconductor chalcogel, exhibits high specific capacity and excellent cycling stability. Synchrotron X-ray pair distribution function and extended X-ray absorption fine structure analyses reveal a short-range atomic structure comprising Mo–Mo, M–S (M = Mo, Zn), and S–S bonding motifs. The coordination environment of Mo and S closely resembles that of Mo 3 S 13 clusters, interconnected via S–S bridges and Zn 2+ cations. The Li/Zn x Mo 3 S 13 cell delivers an initial discharge capacity of 844 mAh g −1 at C/3, and retains 386.2 mAh g −1 after 1000 cycles with an average coulombic efficiency of 99.99%. The distribution of relaxation times analysis confirms the formation of a stable solid electrolyte interphase, which underpins the cell's long-term stability. In conclusion, this outstanding performance is attributed to the synergistic effects of the chalcogel's unique amorphous framework, semiconductive character, Zn-mediated polysulfide anchoring, and structural resilience, positioning Zn x Mo 3 S 13 chalcogel among the most durable pure metal sulfide cathodes reported for next-generation LIBs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On-the-fly data set combinations with RNTuple

With the expected data volume increase for HL-LHC and the even more complex computing challenges set by future colliders, the need for efficient data storage and processing becomes more pressing. ROOT’s next-generation data format and I/O subsystem, RNTTuple, is designed to address these challenges. RNTTuple already demonstrates a clear improvement in storage and I/O efficiency, as well as overall stability and robustness with respect to its predecessor, TTTree. These improvements provide a solid baseline to introduce novel extensions to common high-energy and nuclear physics (HENP) workflows. Notably, many workflows could benefit from the ability to arbitrarily join and chain data set samples at runtime, which could reduce overall storage requirements and improve application runtime and ergonomics. In this paper, we present the RNTupleProcessor, which enables HENP data set combinations with RNTuple. We will discuss the main design considerations, present the interfaces to support data set combinations and show how they integrate in typical workflows.

de Geus, Florine Willemijn [CERN; Twente U., Ensch↗
DOE OSTI2025

An implementation of a high-order generalized finite difference method for solving the time-harmonic cold plasma wave equation in toroidal geometry

A high-order physics-informed meshless finite difference numerical technique is introduced for solving the time-harmonic cold plasma wave equation in toroidal geometries, presenting a novel application of the generalized finite difference (GFD) method to plasma wave simulations. The algorithm employs an irregular distribution of computational points, with local point density informed by the shortest wavelength derived from the cold plasma dispersion relation. Numerical stability and robustness are addressed using regularization techniques. The algorithm, implemented for two spatial dimensions, solves for the wave electric field and is demonstrated to achieve convergence rates of $\mathcal{O}$($\mathcal{h}$ $\mathcal{P}$ )⁠. Verification tests reproduce plane wave solutions, and example simulations of ion cyclotron resonance heating and electron cyclotron resonance heating demonstrate its capability, approaching realistic tokamak plasma scenarios. This work contributes to laying a foundation for the GFD method to be used in more sophisticated, optimized, and physically realistic full-wave simulations in time-harmonic plasma wave research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Ohmic contacts to nitrogen-incorporated n-type ultrananocrystalline diamond film grown on intrinsic single crystal diamond substrate

Nitrogen-incorporated ultrananocrystalline diamond (n-UNCD) films offer tremendous potential for diverse electronic applications. However, the absence of a reliable Ohmic contact at room temperature limits their practical integration and broader applicability. Here, in this study, we investigate the room temperature specific contact resistivity (ρ c ) of Ti/Pt/Au metal stack deposited on n-UNCD films grown on an intrinsic single crystal diamond substrate using a microwave plasma chemical vapor deposition system. We employ a circular transfer length model (c-TLM) and find the room temperature ρ c to be ∼4.67 × 10 −5 Ω cm 2 , which is among the lowest reported value for n-UNCD films. High temperature vacuum annealing conducted at 700 and 800 °C results in an initial improvement, followed by a minor degradation in ρ c values, respectively. The electrical contacts remain highly Ohmic for all measurements. Furthermore, cross-sectional transmission electron microscopy analysis suggests formation of conductive titanium carbide layer with no significant inter metallic diffusion. Overall, the electrical contacts demonstrate robust thermal stability, both of which are critical for attaining high-performance nanocrystalline diamond-based electronic devices.

Low resistance contacts↗
DOE OSTI2025

Soft x-ray high-harmonic generation in an anti-resonant hollow core fiber driven by a 3 μ m ultrafast laser

High-harmonic upconversion driven by a mid-infrared femtosecond laser can generate coherent soft x-ray beams in a tabletop-scale setup. Here, we report on a compact ytterbium-pumped optical parametric chirped pulse amplifier (OPCPA) laser system seeded by an all-fiber front-end and employing periodically poled lithium niobate (PPLN) nonlinear media operated near the pulse fluence limits of current commercially available PPLN crystals. The OPCPA delivers 3 µm wavelength pulses with 775 µJ energy at 1 kHz repetition rate, with transform-limited 120 fs pulse duration, diffraction-limited beam quality, and ultrahigh 0.33% rms energy stability over >18 h. Using this laser, we generate soft x-ray high harmonics (HHG) in argon gas by focusing into a low-loss, high-pressure gas-filled anti-resonant hollow core fiber (ARHCF), generating coherent light at photon energies up to the argon L-edge (250 eV) and carbon K-edge (284 eV), with high beam quality and ∼1% rms energy stability. This work demonstrates soft x-ray HHG in a high-efficiency guided-wave phase matched geometry, overcoming the high losses inherent to mid-IR propagation in unstructured waveguides, or the short interaction lengths of gas cells or jets. The ARHCF can operate in the long term without damage and with the repetition rate, stability, and robustness required for demanding applications in spectromicroscopy and imaging. Finally, we discuss routes for further optimizing the soft x-ray HHG flux by driving He at higher laser intensities using either the signal (1.5 μm) or idler wavelengths (3 μm).

Femtosecond lasers↗
DOE OSTI2026

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗