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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Arbitrary Low-Dimensional Film Transfer Enabled by GeO 2 Release Layer

Low-dimensional materials show great promise for enhanced computing and sensing performance in mission-relevant environments. However, integrating low-dimensional materials into conventional electronics remains a challenge. Here, we demonstrate a novel transfer method by which low-dimensional materials and their heterostructures can be transferred onto any arbitrary substrate. Our method relies on a water soluble GeO 2 substrate from which lowdimensional materials are transferred without significant perturbation. We apply the method to transfer a working electronic device based on a low-dimensional material. Process developments are achieved to enable the fabrication and transfer of a working electronic device, including the growth of high-k dielectric on GeO 2 by atomic layer deposition and inserting an indium diffusion barrier into the device gate stack. This work supports Sandia’s heterogeneous integration strategy to broaden the implementation of low-dimensional films and their devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advancing the Limits of InSAR to Detect Crustal Displacement from Low-Magnitude Earthquakes through Deep Learning

Detecting surface deformation associated with low-magnitude (M w ≤ 5) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic events, and thus characterizing the crustal displacement associated with them is crucial for regional seismic hazard assessment. We combine InSAR time-series techniques with a Deep Learning (DL) autoencoder denoiser to detect the magnitude and extent of crustal deformation from the M w = 3.4 Gallina, New Mexico earthquake that occurred on 30 July 2020. Although InSAR alone cannot detect event-related deformation from such a low-magnitude seismic event, application of the DL method reveals maximum displacements as small as (±2.5 mm) in the vicinity of both the fault and earthquake epicenter without prior knowledge of the fault system. This finding improves small-scale displacement discernment with InSAR by an order of magnitude relative to previous studies. We additionally estimate best-fitting fault parameters associated with the observed deformation. The application of the DL technique unlocks the potential for low-magnitude earthquake studies, providing new insights into local fault geometries and potential risks from higher-magnitude earthquakes. This technique also permits low-magnitude event monitoring in areas where seismic networks are sparse, allowing for the possibility of global fault deformation monitoring.

58 GEOSCIENCES↗
DOE OSTI2025

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗
DOE OSTI2026

Next-generation anodes for high-energy and low-cost sodium-ion batteries

Sodium-ion batteries (NIBs) are increasingly becoming commercially viable alternatives to lithium-ion batteries (LIBs), driven by sodium’s lower cost and greater resource availability. However, current NIB technology still falls short of established LIB systems, such as those based on LiFePO 4 , in both cost efficiency and energy density. Although since the early 2020s, industrial advances have raised NIB energy densities to around 175 Wh kg −1 , performance remains limited by the relatively low specific capacity (typically 200–350 mAh g −1 ) and low tap density (0.3–1.0 g cm −3 ) of the prevailing hard carbon anodes. This Review analyses emerging anode materials that could unlock higher-energy and lower-cost NIBs, with a focus on high-capacity hard carbon and alloy-based systems. We discuss the latest progress, fundamental challenges and future directions in these anode materials across the key themes of electrode design, structure–property engineering and characterization. Here, by offering forward-looking insights into the rational design and optimization of anode materials, this Review aims to accelerate the research and development of commercially viable NIBs and support the broader advancement of energy storage technologies.

Batteries↗
DOE OSTI2026

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Bacteria rapidly adapt to environmental cues through morphological and ultrastructural changes that correlate with physiology and behavior. Cryogenic transmission electron microscopy (cryo‐TEM) can capture these phenotypic changes in near‐native, vitrified states, but manual analysis of low‐dose micrographs is labor intensive and limits throughput. Here, we present an end‐to‐end workflow that combines low‐dose cryo‐TEM imaging with a YOLOv11‐based instance‐segmentation model to automatically identify bacteria and quantify key structural features directly from the micrographs. This workflow enables (i) robust bacterial localization and counting from low‐magnification atlas/montage images, (ii) automated measurements of cell‐envelope (outer–inner membrane) thickness and anisotropy from higher‐magnification views, and (iii) detection and quantification of bacteria–flagella interactions, including overlap length and curvature metrics for interacting versus noninteracting flagella. Using Pantoea sp. YR343 grown under distinct media conditions, we show that the automated measurements agree with manual annotations while substantially reducing analysis time. Together, these tools provide a practical framework for scalable bacterial identification and quantitative phenotyping in low‐dose cryo‐TEM datasets and establish a foundation for extending cryo‐TEM image analysis toward higher‐throughput studies of microbial heterogeneity and biointerfaces.

YOLOv11↗
DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗
DOE OSTI2024

Low‐Volume Cores for Fabrication of Compact, Versatile, and Intelligent Soft Systems

Abstract This study introduces the low‐volume core (LVC) fabrication method, which enables the monolithic molding of compact, complex, versatile, and intelligent soft robotic systems. This method uses thin and flexible thermoplastic sheets to mold internal chambers in soft fluidic actuators, valves, and circuits. The LVC fabrication method creates low‐volume networks in soft actuators (LV‐net actuators) that can be made with compact and complex geometries, enabling both low actuation volume input and multi‐degree‐of‐freedom actuators. LVC fabrication can also be used for compact, completely soft, and monolithic logic components (valves with low‐volume core, also called as LV valves) to provide directional resistance as well as a switching mechanism that enables fluidic logic in soft systems. The compatibility of the fabrication methods for both soft actuators and valves facilitates the creation of compact, integrated, and versatile soft robotic systems with embodied intelligence. This study introduces two examples of such intelligent soft robotic systems that integrate both LV‐net actuators and LV valves to demonstrate capability for complex system fabrication.

Yu, Qifan↗
DOE OSTI2025

Radiative corrections relating leptoquark-fermion couplings probed at low and high energy

Scalar leptoquarks (LQ) with masses between 2 TeV and 50 TeV are prime candidates to explain deviations between measurements and Standard-Model predictions in decay observables of b-flavored hadrons (“flavor anomalies”). Explanations of low-energy data often involve $\mathcal{O}$ (1) LQ-quark-lepton Yukawa couplings, especially when collider bounds enforce a large LQ mass. This calls for the calculation of radiative corrections involving these couplings. Studying such corrections to LQ-mediated b → cτν and b → sℓ + ℓ − amplitudes, we find that they can be absorbed into finite renormalizations of the LQ Yukawa couplings. If one wants to use Yukawa couplings extracted from low-energy data for the prediction of on-shell LQ decay rates, one must convert the low-energy couplings to their high-energy counterparts, which subsume the corrections to the on-shell LQ-quark-lepton vertex. We present compact formulae for these correction factors and find that in scenarios with S 1 , R 2 , or S 3 LQ the high-energy coupling is always smaller than the low-energy one, which weakens the impact of collider data on the determination of the allowed parameter spaces. For the R 2 scenario addressing b → cτν, in which one of the two involved Yukawa coupling must be significantly larger than 1, we find this coupling reduced by 15% at high energy. If both S 1 and R 2 are present, the high-energy coupling can also be larger and the size of the correction is unbounded, because tree contribution and vertex corrections involve different couplings. We further present the conversion formula to the $\overline{MS}$ scheme for the Yukawa couplings of the S 3 scenario.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Search for higgsinos in compressed mass spectra using low-momentum tracks in pp collisions at s=13 TeV with the ATLAS detector

This paper presents two searches for the electroweak production of higgsinos with compressed mass spectra using 140 fb−1 of s=13$$ \sqrt{s}=13 $$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events are required to feature an energetic jet, large missing transverse momentum, and at least one low-momentum charged particle that serves as a candidate higgsino decay product. In the first search, targeting higgsino mass splittings in the range of 0.3–1 GeV, the higgsinos are expected to predominantly decay into pions that are identified as low-momentum charged particles with large transverse impact parameters due to the long higgsino lifetime (cτ ≈ ?(0.1–10 mm)), and neural networks are used to discriminate between signal and background processes. The second search targets larger mass splittings in the range of 1–3 GeV, where the higgsinos are expected to decay promptly into low-momentum leptons, one of which is identified by dedicated low-momentum electron or muon taggers based on neural networks utilising tracking and calorimeter information. No significant excess above the Standard Model prediction is observed in either search and the results are interpreted within simplified models, to set lower limits on the masses of the higgsino-like charginos and neutralinos. Together, these searches exclude chargino masses below 126 GeV at 95% confidence level for mass splittings between the chargino and lightest neutralino in the range of 0.3–2 GeV. This represents the first ATLAS constraints in a portion of this parameter space and surpasses the limits previously set by other experiments.

Aad, G↗
DOE OSTI2024

A supersymmetric SYK model with a curious low energy behavior

We consider N = 2,4 supersymmetric SYK models that have a peculiar low energy behavior, with the entropy going like S = S 0 + (constant)T a , where a ≠ 1. The large N equations for these models are a generalization of equations that have been previously studied as an unjustified truncation of the planar diagrams describing the BFSS matrix quantum mechanics or other related matrix models. Here we reanalyze these equations in order to better understand the low energy physics of these models. We find that the scalar fields develop large expectation values which explore the low energy valleys in the potential. The low energy physics is dominated by quadratic fluctuations around these values. These models were previously conjectured to have a spin glass phase. We did not find any evidence for this phase by using the usual diagnostics, such as searching for replica symmetry breaking solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Evaluating indoor thermal resilience of passive and low-power cooling shelters for outdoor workers in India

India’s 231 million outdoor workers are exposed to deadly heat during heat waves. We report results from a simulation-based study that focuses on passive design of cooling shelters for the hot and dry climate zone of India. The goal is to design a cooler-than-outdoor shelter for outdoor workers’ intermittent rest and recovery from heat stress during their arduous outdoor work, to avoid heat-related morbidities and mortality. Expected indoor thermal conditions in low-cost cooling shelters deploying a range of passive designs and low-power active measures are investigated, consistent with the current Indian standards and practices, located in the city of Jodhpur in western India. Heat resilience of the shelter was measured with the predicted reduction of hazardous hours inside the shelter based on the wet-bulb globe temperature (WBGT) and extended heat index. These measures include improving the building envelope, installing cool roofs, using internal thermal mass, and natural ventilation. Additionally, a low-power active measure of using ventilation fans and ceiling fans is explored. EnergyPlus-based simulation results show that simple, commonly available measures, particularly natural ventilation and ceiling fans, achieve the most significant reductions in overheating danger hours, by 22% and 21%, respectively, while more complex or costly passive strategies yield only marginal additional benefits. Moreover, combined measure packages are identified that can reduce the indoor WBGT by 8 to 10 °C, eliminating overheating danger hours. These findings highlight the critical importance of scalable, low-cost, and easily deployable cooling solutions for developing resilient cooling shelters for vulnerable outdoor workers during heat waves in India.

building performance↗
DOE OSTI2026

A finite viscoelastic constitutive model for low to high strain rate response of elastomers with application of strain rate-induced glass transition

Amorphous elastomers exhibit significant rate-stiffening and unique viscous flow characteristics across a wide range of strain rates, often undergoing glass transition above a strain rate threshold. We have developed a thermodynamically-consistent and micromechanically-inspired constitutive model for soft elastomeric materials to capture the rate-dependent stress-strain behavior and hysteresis when subjected to low to high strain rates. Here, our proposed constitutive model encapsulates the viscous flow of materials through molecular motion at low strain rates and local rearrangement and alignment of the molecules trying to overcome the intermolecular resistance at high strain rates, essentially covering the glass transition. We applied our constitutive model to uniaxial compression experiments performed at low and high strain rates for polyborosiloxane (PBS) to identify the material parameters, and subsequently, performed numerical simulations of single and multi-cycle compression, stress relaxation, and small amplitude oscillatory tension-compression. Our analyses indicate that the model predicts higher total energy dissipation with increasing strain rate; however, dissipation associated with molecular relaxation decreases (forming a cusp) because, beyond a crossover strain rate, intermolecular rearrangement and alignment become dominant, which is consistent with the onset of the glass transition. For cyclic loading-unloading, we observed that dissipation over a cycle remains constant at low strain rates but decreases non-monotonically at high strain rates before becoming constant, with the peak stress over the cycle becoming higher, which can be interpreted as more loading being carried elastically by the polymer network as the intermolecular rearrangement process occurs. Additionally, our model was able to predict the qualitative nature of the storage modulus and loss modulus in the limit of small strain over a wide range of frequency sweeps.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High protonic resistance of hydrocarbon-based cathodes in PEM fuel cells under low humidity conditions: Origin, implication, and mitigation

Hydrocarbon-based electrodes for proton-exchange membrane fuel cells face challenges in closing the performance gap with electrodes based on perfluorosulfonic acid ionomers, particularly under low humidity conditions. Alongside increased oxygen transport resistance and higher kinetic-induced overpotentials, the protonic resistance of these fluorine-free electrodes is the primary hurdle to improved performance. This study systematically investigates the origin and impact of the cathode protonic resistance on fuel cell performance, utilizing sulfonated phenylated polyphenylenes as hydrocarbon ionomers. Electrochemical characterization at low relative humidity (≤50 %) reveal a high protonic resistance arising from both lower conductivity of the hydrocarbon thin film compared to the bulk membrane and increased cathode tortuosity at a gas transport-optimized ionomer to carbon (I/C) ratio of 0.2. The poor protonic resistance at low relative humidities leads to a non-homogeneous current distribution across the thickness of the cathode electrode, resulting in lower catalyst utilization. To address this issue, reducing the thickness of the cathode CL while maintaining a constant Pt loading (i.e., increasing the Pt on carbon ratio) significantly reduces protonic resistance. This improvement compensates for the kinetic disadvantages of highly loaded carbon particles and results in a considerable performance increase by 40 % at 0.75 V under low relative humidities.

25 ENERGY STORAGE↗
DOE OSTI2025

Characterization of 4H-SiC Low Gain Avalanche Detectors (LGADs)

4H-SiC Low Gain Avalanche Detectors (LGADs) have been fabricated and characterized. The devices employ a circular mesa design with low-resistivity contacts and an SiO 2 passivation layer. The I–V and C–V characteristics of the 4H-SiC LGADs are compared with complementary 4H-SiC PiN diodes to confirm a high breakdown voltage and low leakage current. Both LGADs and PiN diodes were irradiated with alpha particles from a $^{210}_{84}$Po source. The charge collected by each device was compared, and it was observed that low-gain charge carrier multiplication is achieved in the 4H-SiC LGAD.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Characterization of detachment inferred from the Balmer line ratios in JET-ILW low-confinement mode plasmas

Spectroscopic measurements of the hydrogenic Balmer-α and Balmer-γ line emission in JET-ILW low-confinement mode (L-mode) deuterium plasmas are used to assess the onset of volume recombination in the low-field side (LFS) divertor. The evolution of the EDGE2D-EIRENE predicted Balmer-γ to Balmer-α emission ratio from low-recycling to detached conditions is in qualitative agreement with the measured ratio. In low-recycling conditions the EDGE2D-EIRENE predicted line-emission is within 30% of measured emission, in high-recycling within 20%t, and in detached conditions lower by a factor of 2.5.

Divertor visible spectroscopy↗
DOE OSTI2025

Balmer emission measurements in JET-ILW hydrogen, deuterium, tritium and deuterium-tritium low-confinement mode plasmas

Measurements of Balmer-alpha (B-α) and Balmer-gamma (B-γ), where B = H, D, or T isotopes of hydrogen, emission across the low-field side (LFS) divertor in JET ITER-like Wall (ILW), low-confinement mode (L-mode) plasma indicate that the divertor plasma was more strongly detached in deuterium, tritium and deuterium–tritium than in hydrogen plasmas. These measurements are consistent with the lower degree of detachment in hydrogen versus tritium plasmas inferred from Langmuir probes (Groth et al., 2023). The ratio of B-γ to B-α is a suitable indicator of high density/low temperature conditions because B-α emission is dominated by electron impact excitation with a small electron–ion recombination component regardless of electron temperature and density (for conditions in tokamak plasmas) whilst for B-γ the recombination component increases and the excitation component decreases as the electron temperature decreases and the electron density increases. Within the uncertainty of the measurements, the electron density at the low-field side separatrix and the power crossing the separatrix are similar to permit these comparisons. The B-©/B-α ratio is well correlated with the onset of detachment as measured by Langmuir probes (McCracken et al., 1998; Groth et al., 2023). The ratios of B-γ and B-α varied between 0.005 and 0.035 for low-recycling, high-recycling and partially detached conditions, and were 60–70 % higher in partially detached hydrogen than in tritium plasmas. In contrast, the difference between deuterium, tritium and 40–60 % deuterium–tritium is within 10 % and thus within the uncertainties of the measurements. Profiles of the B-α and B-γ emission was measured with two filtered CCDs connected to the visible lost light leg of JET’s mirror link spectroscopy system (Meigs et al., 2010; Lomanowski et al., 2014). Spatially (radial) narrower B-α profiles were measured with increasing isotope mass, while similarly broadened B-γ profiles were measured.

Balmer↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2024

Investigation of Low-Energy Lattice Dynamics and Their Role in Superionic Na Diffusion and Ultralow Thermal Conductivity of Na 3 PSe 4 as a Solid-State Electrolyte

The atomic dynamics of Na 3 PSe 4 were investigated using a combination of neutron scattering experiments and ab initio and machine-learned molecular dynamics simulations to probe the interplay of fast ionic diffusion with atomic vibrations (phonons) of the host lattice. Our results reveal the existence of low-energy vibrational modes, simultaneously involving motions of Na + ions and framework polyanion subunits, and show that these modes become strongly overdamped in the superionic regime as they couple with the Na + hopping process. In particular, the Na+ migration energy landscape is strongly impacted by low-energy phonons derived from a soft acoustic branch of the host lattice, which modulates the diameter of the Na + diffusion channel at the bottleneck. We find that an additional factor for the enhanced Na + conductivity in Na 3 PSe 4 is the presence of Na-vacancies, which also affect the low-frequency dynamics and thermal vibration amplitudes, pointing to an interplay between Na + vacancies and host dynamics, jointly enhancing ionic diffusivity. Finally, we investigate the origin of ultralow thermal conductivities in Na 3 PSe 4 and Na 3 PS 4 using Green–Kubo simulations and find that low-energy acoustic phonon modes of the overall crystal framework provide a dominant contribution to the thermal conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗