Search NASA⌕ Search

SEARCH · Search NASA

Results for “surpassed”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Surface engineering of polymeric membranes with metal oxides for improved fouling resistance and superior oil-water separation

Rapid industrial growth has increased the need for efficient membranes to separate oil-water emulsions. Polyvinylidene fluoride (PVDF) membranes, although widely used due to their chemical inertness and favorable mechanical properties, suffer from fouling due to their intrinsic hydrophobicity. Modifying these membranes after fabrication offers a practical solution as it easily fits into existing large-scale manufacturing processes. Atomic layer deposition (ALD), an atomically-precise vapor phase surface modification technique, can create ultrathin metal oxide layers that greatly improve membrane hydrophilicity without significantly affecting the original pore size. However, PVDF's lack of reactive chemical moieties makes ALD challenging. Here, in this study, we present a simple alkali treatment that greatly enhances ALD nucleation and growth on PVDF membranes. This treatment imparts exceptional oil-water emulsion separation capabilities and antifouling behavior in PVDF membranes after just a few ALD cycles, surpassing the performance of PVDF membranes coated with hundreds of ALD cycles. This dramatic reduction in the number of ALD cycles required could enable cost-effective modification of commercial PVDF membranes at scale using spatial, roll-to-roll ALD. These modified membranes outperform reported modified PVDF membranes, with >99 % permeance recovery and <1 % irreversible loss of permeance and >98 % oil rejection from oil-water emulsions over 100 h continuous operation, making them promising for advanced water purification technologies.

Atomic layer deposition↗
DOE OSTI2024

Co-, Ni- and Fe-rich grain-boundary phases enhance creep resistance in θ'-strengthened Al-Cu alloys

Here, microstructural evolution and creep response were investigated in the cast Al-5.0Cu-0.3Mn-0.2Zr (wt.%) alloy with and without addition of slow-diffusing, intermetallic-forming elements Fe, Ni, or Co. Baseline Al-5.0Cu-0.3Mn-0.2Zr alloy exhibits high creep resistance at 300 °C, up to ~75 MPa, which is attributed to high-aspect-ratio, intragranular θ'-Al 2 Cu precipitates that effectively suppress dislocation climb. However, θ'-Al 2 Cu precipitate-free zones form along grain boundaries upon heat treatment, whose extent is amplified during subsequent creep. Such weak regions experience dislocation creep, leading to strain localization and acceleration of grain-boundary sliding. Adding Ni and Co, individually or in combination, leads to the formation of grain-boundary precipitates (Al 9 Co 2 , Al 3 Ni 2 ) which are resistant to coarsening, thus suppressing the formation of θ'-Al 2 Cu precipitate-free zones. This microstructure provides high creep resistance at stresses up to 75–80 MPa, with strain rates much lower than in unmodified Al-5.0Cu-0.3Mn-0.2Zr. Adding Fe, which results in extensive decoration of grain boundaries with coarsening-resistant Al 7 Cu 2 Fe, and then increasing the Cu content to compensate for the Cu loss to this new phase, leads to a new Al-7.4Cu-1.6Fe-0.3Mn-0.2Zr alloy with creep resistance at 300 °C that surpasses known cast aluminum alloys. Adding Fe to improve the creep resistance of Al-Cu alloys is both cost-effective and sustainable. Our findings offer guidelines applicable to various alloy systems on controlling the evolution of precipitate-free zones and its ensuing effects on creep deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct observation of key aluminum hydroxide prenucleation oligomers for gibbsite nucleation and crystallization in sodium aluminate solution by liquid ToF-SIMS

The mechanism of gibbsite (aluminum hydroxide) crystallization from highly alkaline solutions such as Bayer liquors remains poorly understood, where aluminum (Al) transforms from largely tetrahedrally coordinated aluminate monomers in sodium aluminate solutions into a network of octahedra in gibbsite crystals. A variety of traditional analytical approaches applied to this system do not readily reveal the presence of higher-order oligomeric intermediates. To overcome this limitation, we employed in-situ liquid Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to examine the Al species present in concentrated sodium aluminate solutions favoring crystallization of gibbsite or sodium aluminate. A complex mixture of Al oligomers was found. By comparing the change in the relative concentration of Al oligomers with +1 and -1 charge, we were able to identify three major Al oligomer candidates, iso-tetramers, iso-pentamers, and cyclic-hexamers, for the nucleation and crystallization of gibbsite. The concentrations of iso-tetramers and iso-pentamers significantly surpass those of cyclic-hexamers. Time-dependent in-situ Raman spectroscopy analysis indicated that the appearance of gibbsite coincided with the peak concentration of these oligomers. The Density-functional theory (DFT) calculation suggests that the formation of iso-oligomers is more favorable than that of cyclic-hexamers. The combined results suggest that iso-tetramers and iso-pentamers play the most substantial role in the nucleation and growth of gibbsite in the sodium aluminate solutions. Our findings also suggest that the oligomers that promote gibbsite crystallization are more stable in dilute sodium aluminate solutions, making these solutions particularly suitable for efficient gibbsite crystallization. In conclusion, our study fills a major knowledge gap in understanding Al speciation that leads to the nucleation and crystallization of gibbsite in concentrated sodium aluminate solutions.

Bayer liquor↗
DOE OSTI2025

Optimizing the impacts of solid additives on the operational stability and processing reliability of organic solar cells

Previous reports have revealed that by leveraging solid additives, organic solar cells (OSCs) can surpass the device’s performance beyond the intrinsic limitations of host photoactive molecules, a remarkable advancement. However, the impacts of more complex interactions introduced by solid additives are not yet well understood. Herein, optimizing the fabrication process based on the traditional efficiency-guided approach fails to represent the ideal and most practical devices. In particular, achieving superior operational stability while minimizing the device performance scattering was found to require processing solvent evaporation to be synchronized with the volatility of the chosen solid additive. However, this may be challenging since most organic photoactive materials display excellent efficiencies only with selected solvents. Accordingly, this work also demonstrates the potential of dual and complementary solvents selection, consisting of low boiling point (primary) and high boiling point (secondary). This strategy allows for the suppression of any potential trade-offs in efficiency. Meanwhile, the operational stability and precision of device performance are substantially enhanced. Additionally, solid additives have demonstrated that the singlet exciton dissociation rate does not limit the free charge generation yield. Finally, these findings are expected to reformulate OSC device fabrication strategies towards more practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Superconductivity in CH 4 and BH – 4 containing compounds derived from the high-pressure superhydrides

Inspired by the synthesis of the high-pressure Fm3m LaH 10 superconducting superhydride, systematic density functional theory (DFT) calculations are performed to study ternaries that could be derived from it by replacing two of the hydrogen atoms with boron or carbon and varying the identity of the electropositive element. Though many of the resulting alkali-metal and alkaline-earth MC 2 H 8 phases are predicted to be dynamically stable at mild pressures, their superconducting critical temperatures (T c s) are low because their metallicity results from the filling of an electride-like band. Substitution with a trivalent element leads to phases with substantial metal d- character at the Fermi level whose T c s are typically above 40 K. Here, among the MB 2 H 8 phases examined, KB 2 H 8 , RbB 2 H 8 and CsB 2 H 8 are predicted to be dynamically stable at very mild pressures, and their stability is rationalized by a DFT-Chemical Pressure analysis that elucidates the role of the M atom size. Quantum anharmonic effects strongly affect the properties of KB 2 H 8 , the highest predicted T c compound, near 10 GPa, but molecular dynamics simulations reveal it would decompose below its T c at this pressure. Nonetheless, at ca. 50 GPa KB 2 H 8 is predicted to be thermally stable with a superconducting figure of merit surpassing that of the recently synthesized LaBeH 8 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rooting MnO 2 into protonated g-C 3 N 4 by intermolecular hydrogen bonding for endurable supercapacitance

Composited electrode materials for energy storage typically benefit from the merits of each component but meanwhile largely suffer from the vulnerable structural integrity during repetitive cycling. Realizing the merely physical attachment in most composited structures being too weak to survive harsh cycling, we report here a facile one-step synthesis strategy with generation of chemical bonds, more specifically, intermolecular hydrogen bonds, to tightly combine each component. Here, we demonstrate this concept by designing a composite featuring MnO 2 nanorods chemically rooted into protonated g-C 3 N 4 , where the protonation of 2D g-C 3 N 4 substrate (pg-C 3 N 4 ), the nucleation/growth of MnO 2 and the formation of hydrogen bonding between pg-C 3 N 4 and MnO 2 simultaneously occur. The obtained composite, when applied for supercapacitive energy storage, yields maximum specific capacitances of 348.4 F·g -1 at a current density of 1.0 A·g -1 as well as a high retention of ~85.0% after 10000 cycles at 6.0 A·g -1 , surpassing most previously reported composited electrode materials based on either MnO 2 or g-C 3 N 4 . Finally, we expect this work to inspire the synthesis of composited electrode materials with consolidated 3D architecture for endurable energy storage performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Design and simulation of a SiPM-on-tile ZDC for the future EIC, and its performance with graph neural networks

We present a design for a high-granularity zero-degree calorimeter (ZDC) for the upcoming Electron-Ion Collider (EIC). The design uses SiPM-on-tile technology and features a novel staggered-layer arrangement that improves spatial resolution. To fully leverage the design’s high granularity and non-trivial geometry, we employ graph neural networks (GNNs) for energy and angle regression as well as signal classification. The GNN-boosted performance metrics meet, and in some cases, significantly surpass the requirements set in the report on science requirements and detector requirements for the EIC (Yellow Report), laying the groundwork for enhanced measurements that will facilitate a wide physics program. Our studies show that GNNs can significantly enhance the performance of high-granularity CALICE-style calorimeters by automating and optimizing the software compensation algorithms required for these systems. This improvement holds true even in the case of complicated geometries that pose challenges for image-based AI/ML methods.

Calorimeter↗
DOE OSTI2026

Sim-to-real supervised domain adaptation for radioisotope identification

Machine learning has the potential to improve the speed and reliability of radioisotope identification using gamma spectroscopy. However, meticulously labeling an experimental dataset for training is often prohibitively expensive, while training models purely on synthetic data is risky due to the domain gap between simulated and experimental measurements. In this research, we demonstrate that supervised domain adaptation can substantially improve the performance of radioisotope identification models by transferring knowledge between synthetic and experimental data domains. We consider two domain adaptation scenarios: (1) a simulation-to-simulation adaptation, where we perform multi-label proportion estimation using simulated high-purity germanium detectors, and (2) a simulation-to-experimental adaptation, where we perform multi-class, single-label classification using measured spectra from handheld lanthanum bromide (LaBr) and sodium iodide (NaI) detectors. We begin by pretraining a spectral classifier on synthetic data using a custom transformer-based neural network. After subsequent fine-tuning on just 64 labeled experimental spectra, we achieve a test accuracy of 96% in the sim-to-real scenario with a LaBr detector, far surpassing a synthetic-only baseline model (75%) and a model trained from scratch (80%) on the same 64 spectra. Furthermore, we demonstrate that domain-adapted models learn more human-interpretable features than experiment-only baseline models. Overall, our results highlight the potential for supervised domain adaptation techniques to bridge the sim-to-real gap in radioisotope identification, enabling the development of accurate and explainable classifiers even in real-world scenarios where access to experimental data is limited.

Lalor, Peter W.↗
DOE OSTI2026

Ultra-pure nickel for structural components of low-radioactivity instruments

The next generation of nuclear and particle physics rare-event search experiments demand structural materials combining ultra-low levels of radioactive contamination with exceptional mechanical strength. Here, this study evaluates chemical vapor deposition (CVD) nickel as a low radioactive background candidate structural material for such applications. Manufacturer-supplied CVD Ni grown on aluminum substrates was assayed via inductively coupled plasma mass spectrometry (ICP-MS) employing isotope-dilution. These material assays produced measured bulk concentration of 232 Th, 238 U, and nat K at the levels of ~70 ppq, ≲100 ppq, and ~900 ppt, respectively, which is the lowest reported in nickel. Surface-etch profiling uncovered higher concentrations of these contaminants extending ~10 μ m beneath the surface, likely associated with the aluminum growth substrate. Additionally, the CVD Ni underwent tensile testing alongside standard Ni samples. CVD Ni exhibited a planar tensile strength of ~600 MPa, significantly surpassing standard nickel. However, heat treatment was found to reduce the tensile strength to levels comparable to standard Ni, with implications for high-temperature weld joining methods. The results reported are compared to the one other well documented usage of CVD Ni in a low radioactive background physics research experiment and a discussion is provided on how the currently reported results may arise from changes in CVD fabrication or testing process. These results establish CVD Ni as a promising low-radioactivity structural material, while outlining the need for further development in surface cleaning and weld-joining techniques to fully realize its potential in large-scale, low radioactive background rare-event search experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Electron/hadron separation with the TRD based on GaAs pixel detectors

Transition Radiation Detectors (TRDs) are widely used for particle identification in both high-energy physics and astroparticle physics. They are typically equipped with gaseous detectors. The main limitation of these types of detectors is that TR photons and ionization losses cannot be decoupled, which significantly reduces the particle separation power. Recent advancements in the development of pixel detectors based on GaAs sensors offer a unique opportunity to effectively detect TR photons and separate them from ionization losses. Such detectors represent novel devices that combine precise tracking capabilities with particle identification (PID) properties. The present work is dedicated to an experimental study of particle identification properties of the TRD prototype based on 500 μ m-thick GaAs sensor bonded to a Timepix3 chip. Studies were performed at the CERN SPS and it was shown that at a particle momentum of 20 GeV/c, the probability of misidentifying a hadron as an electron is below 10 −2 for an electron detection efficiency of 98%–99%, and it is 1 . 6⋅10 −4 for electron detection efficiency of 90%. This performance surpasses the electron/hadron rejection power of all known TRDs by an order of magnitude for the same detector length.

GaAs detectors↗
DOE OSTI2026

A 24-channel ultra-low-noise preamplifier for dN/dx measurements with drift tube detectors

Cluster counting $(dN/dx)$ is a promising method to enhance particle identification for gaseous detectors, especially in next-generation collider experiments like the FCC-ee, where good $π/K$ separation over a broad momentum range is essential. However, its implementation in large-scale systems has been limited by the challenging requirements for high-resolution signal amplification and readout. This paper presents a 24-channel ultra-low-noise preamplifier board designed for drift tube detectors to enable $dN/dx$ measurements. The three-stage amplification topology employs SiGe transistors and integrates dedicated noise-minimization techniques, achieving a charge gain of 21.11 mV/fC from 0.3 fC to 50 fC, a bandwidth of 542 MHz, and a voltage gain of 47.8 dB. The measured voltage noise density is 0.35 nV/$\sqrt{\textrm{Hz}}$ , surpassing most of the state-of-the-art preamplifiers for gaseous and silicon detectors. Validation tests conducted on the sMDT chambers at the CERN Proton Synchrotron test beam facility demonstrate that the proposed design meets the stringent preamplifier requirements for implementing the $dN/dx$ method in drift-tube detector systems, achieving an equivalent noise charge of 0.14 fC and a signal-to-noise ratio of 73 when operated with a He:iC 4 H 10 (90:10) gas mixture. The design also shows promise for broader application in other gaseous or semiconductor detectors.

Drift tube detector↗
DOE OSTI2022

Improved light yield and growth of large-volume ultrafast single crystal scintillators Cs 2 ZnCl 4 and Cs 3 ZnCl 5

Due to their reported fast decay times, Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are promising candidates for detection of gamma rays and X-rays in high count rate and fast timing applications. In this work, we show that single crystals with better optical quality than previously demonstrated – and larger in size – can be grown via the vertical Bridgman method. Highly transparent Ø7 mm crystals of undoped Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are grown and measured to have light yields surpassing those previously reported, achieving 1980 ± 100 ph/MeV and 1460 ± 70 ph/MeV at 662 keV – a 55% and 232% improvement, respectively. We observe single-component scintillation decay times for both Cs 2 ZnCl 4 (1.66 ns) and Cs 3 ZnCl 5 (0.82 ns) and radioluminescence emission with maximum intensity at ~290 nm. Scalability of these materials is also evaluated based on growth of Ø22 mm crystals. Minimal cracking is observed, and the fast decay times are maintained at this size. Coincidence time resolution of 3 × 3 × 5 mm 3 and 7 × 7 × 10 mm 3 pixels cut from Ø22 mm Cs 2 ZnCl 4 are measured to be 148 ± 1 ps FWHM and 175 ± 1 ps FWHM, respectively. Here, the improved performance and ability to be fabricated in large sizes now place Cs 2 ZnCl 4 and Cs 3 ZnCl 5 on the map as potential contenders for radiation detection applications where BaF 2 – the most commonly used ultrafast inorganic scintillator – is typically considered.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Variable rate neural compression for sparse detector data

Particle colliders produce data at extraordinary rates, posing major challenges for transmission and storage. High-throughput compression algorithms are therefore essential. In the sPHENIX experiment taking data at the Relativistic Heavy Ion Collider, a time projection chamber records three-dimensional (3D) particle trajectories that are highly sparse, making conventional learning-free lossy compression ineffective. Convolutional neural networks have surpassed traditional methods in compression ratio and accuracy. However, they fail to exploit sparsity for efficiency. To address these gaps, we present BCAE-VS, a bicephalous convolutional autoencoder with variable compression ratio for sparse data, which adapts compression to input complexity through key-point identification and sparse convolution. BCAE-VS achieves higher accuracy and compression ratios than prior neural approaches while being orders of magnitude smaller. Moreover, its throughput increases with sparsity—a property not observed in other methods. Although it was developed for collider experiments, BCAE-VS readily extends to other sparse data domains, such as light detection and ranging (LiDAR) sensing and 3D microscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Deep inverse photonic design: A tutorial

Deep learning (DL) has been used to design deep neural networks (DNNs) which have recently been applied to solving inverse problems in artificial electromagnetic materials (AEMs). Although inverse problems are often ill-posed, and therefore are difficult to solve, deep inverse models (DIMs) have achieved impressive results often surpassing capabilities possible with other approaches. We overview the process of deep inverse learning applied to AEM problems, including the building of data sets, design of a forward model, and comparison of inverse approaches including limitations. We conclude by detailing some important outstanding issues of deep inverse design of AEMs, and present an outlook of this exciting field.

42 ENGINEERING↗
DOE OSTI2025

Searching for neutrino self-interactions at future muon colliders

Multi-TeV muon colliders offer a powerful means of accessing new physics coupled to muons while generating clean and intense high-energy neutrino beams via muon decays. We study a fixed-target experiment leveraging the neutrino beams and a forward detector pointing at the interaction point of the muon collider. The sensitivity to neutrino self-interactions is analyzed as a feasibility study, focusing on the leptonic scalar ϕ exclusively coupled to the Standard Model neutrinos. Our work shows that projections from both the main and forward detectors can enhance the existing limits by two orders of magnitude, surpassing other future experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Tuning gas separation performance of polyimide membranes with macrocyclic crown ether units

Membrane-based gas separation is an energy-efficient alternative to conventional thermally-driven separation processes. However, polymer membranes face the permeability-selectivity trade-off challenge, which stems from the broad size distribution of free volume voids. Here, this study reports a molecular design strategy to address this challenge through incorporating macrocyclic crown ether (CE) moieties into the backbone of Matrimid® polyimide, a commercial gas separation membrane. A series of CE-containing Matrimid®-like copolyimides were synthesized with systematically varied CE molar contents ranging from 3 to 20%. These copolyimides formed ductile, defect-free thin films suitable for membrane fabrication. Gas permeation tests revealed a non-monotonic relationship between permeability/selectivity and CE content. Notably, the copolyimide with only 5% CE demonstrated a 61% increase in CO 2 /CH 4 selectivity and a 13% increase in CO 2 permeability relative to pristine Matrimid®. Higher CE contents did not yield further performance improvements, which is likely due to the competing effects of chain packing disruption and π–π interactions among CE moieties at high content. This hypothesis was supported by wide-angle X-ray scattering (WAXS) analysis, density measurements, and fractional free volume calculations. These findings highlight the potential of macrocyclic crown ether incorporation strategies in fine tuning the microstructure of commercial polyimide gas separation membranes to surpass the traditional permeability-selectivity trade-off.

CO2 separation↗
DOE OSTI2022

Heavy quarks and jets as probes of the QGP

Quark–Gluon Plasma (QGP), a QCD state of matter created in ultra-relativistic heavy-ion collisions, has remarkable properties including, for example, a low shear viscosity over entropy ratio. By detecting the collection of low-momentum particles that arise from the collision, it is possible to gain quantitative insight into the created matter. However, its fast evolution and thermalization properties remain elusive. Further, only the usage of high momentum objects as probes of QGP can unveil its constituents at different wavelengths. In this review, we attempt to provide a comprehensive picture of what was, so far, possible to infer about QGP given our current theoretical understanding of jets, heavy-flavor, and quarkonia. We will bridge the resulting qualitative picture to the experimental observations done at both the LHC and RHIC. We will focus on the phenomenological description of experimental observations, provide a brief analytical summary of the description of hard probes, and an outlook towards the main difficulties we will need to surpass in the following years. To benchmark QGP-related effects, we will also address nuclear modifications to the initial state and hadronization effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Lacustrine leaf wax hydrogen isotopes indicate strong regional climate feedbacks in Beringia since the last ice age

The Late-Quaternary climate of Beringia remains unresolved despite the region's role in modulating glacial-interglacial climate and as the likely conduit for human dispersal into the Americas. In this work, we investigate Beringian temperature change using an ~32,000-year lacustrine record of leaf wax hydrogen isotope ratios (δ2Hwax) from Arctic Alaska. Based on Monte Carlo iterations accounting for multiple sources of uncertainty, the reconstructed summertime temperatures were ~3 °C colder (range: –8 to +3 °C) during the Last Glacial Maximum (LGM; 21-25 ka) than the pre-industrial era (PI; 2–0.1 ka). This ice-age summer cooling is substantially smaller than in other parts of the Arctic, reflecting altered atmospheric circulation and increased continentality which weakened glacial cooling in the region. Deglacial warming was punctuated by abrupt events that are largely synchronous with events seen in Greenland ice cores that originate in the North Atlantic but which are also controlled locally, such as by the opening of the Bering Strait between 13.4 and 11 ka. Our reconstruction, together with climate modeling experiments, indicates that Beringia responds more strongly to North Atlantic freshwater forcing under modern-day, open-Bering Strait conditions than under glacial conditions. Furthermore, a 2 °C increase (Monte Carlo range: –1 to +5 °C) over the anthropogenic era reverses a 6 °C decline (Monte Carlo range: –10 to 0 °C) through the Holocene, indicating that recent warming in Arctic Alaska has not surpassed peak Holocene summer warmth.

54 ENVIRONMENTAL SCIENCES↗