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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 OSTI2022

In situ recording of Mars soundscape

Abstract Before the Perseverance rover landing, the acoustic environment of Mars was unknown. Models predicted that: (1) atmospheric turbulence changes at centimetre scales or smaller at the point where molecular viscosity converts kinetic energy into heat 1 , (2) the speed of sound varies at the surface with frequency 2,3 and (3) high-frequency waves are strongly attenuated with distance in CO 2 (refs. 2–4 ). However, theoretical models were uncertain because of a lack of experimental data at low pressure and the difficulty to characterize turbulence or attenuation in a closed environment. Here, using Perseverance microphone recordings, we present the first characterization of the acoustic environment on Mars and pressure fluctuations in the audible range and beyond, from 20 Hz to 50 kHz. We find that atmospheric sounds extend measurements of pressure variations down to 1,000 times smaller scales than ever observed before, showing a dissipative regime extending over five orders of magnitude in energy. Using point sources of sound (Ingenuity rotorcraft, laser-induced sparks), we highlight two distinct values for the speed of sound that are about 10 m s −1 apart below and above 240 Hz, a unique characteristic of low-pressure CO 2 -dominated atmosphere. We also provide the acoustic attenuation with distance above 2 kHz, allowing us to explain the large contribution of the CO 2 vibrational relaxation in the audible range. These results establish a ground truth for the modelling of acoustic processes, which is critical for studies in atmospheres such as those of Mars and Venus.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-powered tools, in pursuit of improving accuracy and efficiency of this process. While the unique challenges presented by each modality and clinical task demand customized tools, the cumbersome process of making problem-specific choices has triggered the critical need for a generic solution to enable rapid development of models in practice. In this spirit, we develop DDxNet, a deep architecture for time-varying clinical data, which we demonstrate to be well-suited for diagnostic tasks involving different modalities (ECG/EEG/EHR), required level of characterization (abnormality detection/phenotyping) and data fidelity (single-lead ECG/22-channel EEG). Using multiple benchmark problems, we show that DDxNet produces high-fidelity predictive models, and sometimes even provides significant performance gains over problem-specific solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Radiative impact of record-breaking wildfires from integrated ground-based data

The radiative effects of wildfires have been traditionally estimated by models using radiative transfer calculations. Assessment of model-predicted radiative effects commonly involves information on observation-based aerosol optical properties. However, lack or incompleteness of this information for dense plumes generated by intense wildfires reduces substantially the applicability of this assessment. Here we introduce a novel method that provides additional observational constraints for such assessments using widely available ground-based measurements of shortwave and spectrally resolved irradiances and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges. We apply our method to quantify the radiative impact of the record-breaking wildfires that occurred in the Western US in September 2020. For our quantification we use integrated ground-based data collected at the Atmospheric Measurements Laboratory in Richland, Washington, USA with a location frequently downwind of wildfires in the Western US. We demonstrate that remarkably dense plumes generated by these wildfires strongly reduced the solar surface irradiance (up to 70% or 450 Wm -2 for total shortwave flux) and almost completely masked the sun from view due to extremely large AOD (above 10 at 500 nm wavelength). We also demonstrate that the plume-induced radiative impact is comparable in magnitude with those produced by a violent volcano eruption occurred in the Western US in 1980 and continental cumuli.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data

The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. However, it is difficult to know all the relevant codes related to a phenotype due to the large number of codes available. Traditional data mining approaches often require the use of patient-level data, which hinders the ability to share data across institutions. In this project, we demonstrate that multi-center large-scale code embeddings can be used to efficiently identify relevant features related to a disease of interest. We constructed large-scale code embeddings for a wide range of codified concepts from EHRs from two large medical centers. We developed knowledge extraction via sparse embedding regression (KESER) for feature selection and integrative network analysis. We evaluated the quality of the code embeddings and assessed the performance of KESER in feature selection for eight diseases. Besides, we developed an integrated clinical knowledge map combining embedding data from both institutions. The features selected by KESER were comprehensive compared to lists of codified data generated by domain experts. Features identified via KESER resulted in comparable performance to those built upon features selected manually or with patient-level data. The knowledge map created using an integrative analysis identified disease-disease and disease-drug pairs more accurately compared to those identified using single institution data. Analysis of code embeddings via KESER can effectively reveal clinical knowledge and infer relatedness among codified concepts. KESER bypasses the need for patient-level data in individual analyses providing a significant advance in enabling multi-center studies using EHR data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Dynamics of episodic supershear in the 2023 M7.8 Kahramanmaraş/Pazarcik earthquake, revealed by near-field records and computational modeling

Abstract The 2023 M7.8 Kahramanmaraş/Pazarcik earthquake was larger and more destructive than what had been expected. Here we analyzed nearfield seismic records and developed a dynamic rupture model that reconciles different currently conflicting inversion results and reveals spatially non-uniform propagation speeds in this earthquake, with predominantly supershear speeds observed along the Narli fault and at the southwest (SW) end of the East Anatolian Fault (EAF). The model highlights the critical role of geometric complexity and heterogeneous frictional conditions in facilitating continued propagation and influencing rupture speed. We also constrained the conditions that allowed for the rupture to jump from the Narli fault to EAF and to generate the delayed backpropagating rupture towards the SW. Our findings have important implications for understanding earthquake hazards and guiding future response efforts and demonstrate the value of physics based dynamic modeling fused with near-field data in enhancing our understanding of earthquake mechanisms and improving risk assessment.

Environmental Sciences & Ecology↗
DOE OSTI2024

Sulfur isotopes from the Paleoproterozoic Francevillian Basin record multigenerational pyrite formation, not depositional conditions

Bulk-rock sulfur isotope data from pyrite in the ~2.1 billion-year sedimentary rocks of the Francevillian Basin, Gabon, have underpinned ideas about initial oxygenation of Earth’s surface environments and eukaryote evolution. In this paper, we show, using micro-scale analytical methods, that the bulk sulfur isotope record represents progressive diagenetic modification. Our findings indicate no significant change in microbial sulfur cycling processes and seawater sulfate composition throughout that initial phase of atmosphere-ocean oxygenation of Paleoproterozoic time. This offers an alternative view of Earth system evolution during the transition from an anoxic to an oxic state and highlights the need for a judicious reappraisal of conceptual models using sulfur isotope data as primary depositional signals linked to global-scale biogeochemical processes.

58 GEOSCIENCES↗
DOE OSTI2026

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗
DOE OSTI2022

Historical record of tritium from tree cores at the Savannah River Site

In this work, tree cores from various locations at the Savannah River Site (SRS) and local area were measured for total tritium (T) content and T speciation to include tritiated water (HTO), exchangeable organic bound T (E-OBT) and non-exchangeable organic bound T (NE-OBT) species. The tree cores dated back to the 1960's or prior which provided an opportunity to measure T over the last 60–70 years. The total T levels from pine and oak tree cores were consistent with the record of known T atmospheric releases from nuclear activities at the SRS between the mid-1950's and 1990's with a notable peak in T tree core levels during the late 1960's. The T speciation data for some tree core samples from SRS demonstrated elevated levels of OBT : HTO and NE-OBT : E-OBT identified primarily in the last ~20 years due to T inputs from remedial irrigation with OBT-rich pond water. Elevated but lower levels of OBT : HTO and NE-OBT : E-OBT were observed due to inputs from SRS operations during the last 70 years and prior to irrigation with the T-rich pond water.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dielectric constant engineering of nonfullerene acceptors enables a record fill factor of 83.58% and a high efficiency of 20.80% in organic solar cells

Organic solar cells (OSCs) have achieved power conversion efficiencies (PCEs) surpassing 20%, but their development remains hindered by the inherently low dielectric constant (εr) of organic semiconductors, which limits charge transport and contributes to serious recombination losses. Herein, we present a comprehensive strategy to overcome the challenge by engineering the dielectric properties of nonfullerene acceptors (NFAs). Two Y-series NFAs of BTP-N3F and BTP-C3F have been synthesized featuring trifluoromethyl (CF 3 ) end-capped alkyl side chains. This molecular design significantly enhances the dipole moment and ε r (up to ∼5.9) when compared to the reference acceptor Y6 (∼3), reducing the exciton binding energy (E b ) and improving charge transport. Furthermore, the incorporation of a high-εr polymer additive, poly(pentafluorostyrene) (PPFS), synergistically improves the active layer morphology and dielectric properties, enabling efficient charge extraction and reduced recombination losses. Devices based on the optimized D18-Cl/BTP-C3F system have achieved a record-high fill factor (FF) of 83.58% and an impressive PCE of 20.80%, setting a new benchmark for OSCs. Finally, our results underscore the pivotal role of ε r in enhancing device performance and establish a versatile pathway for advancing OSC efficiency and stability through molecular and morphological optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Achieving record hot spot energies with large HDC implosions on NIF in HYBRID-E

HYBRID-E is an inertial confinement fusion implosion design that increases energy coupled to the hot spot by increasing the capsule scale in cylindrical hohlraums while operating within the current experimental limits of the National Ignition Facility. HYBRID-E reduces the hohlraum scale at a fixed capsule size compared to previous HYBRID designs, thereby increasing the hohlraum efficiency and energy coupled to the capsule, and uses the cross-beam energy transfer (CBET) to control the implosion symmetry by operating the inner (23° and 30°) and outer (44° and 50°) laser beams at different wavelengths (Δλ> 0). Small case to capsule ratio designs can suffer from insufficient drive at the waist of the hohlraum. We show that only a small amount of wavelength separation between the inner and outer beams (Δλ1-2 Å) is required to control the symmetry in low-gas-filled hohlraums (0.3 mg/cm3 He) with enough drive at the waist of the hohlraum to symmetrically drive capsules 1180 μm in outer radius. This campaign is the first to use the CBET to control the symmetry in 0.3 mg/cm3 He-filled hohlraums, the lowest gas fill density yet fielded with Δλ> 0. We find a stronger sensitivity of hot spot P2 in μm per Angstrom (40–50 μm/Å wavelength separation) than observed in high-gas-filled hohlraums and previous longer pulse designs that used a hohlraum gas fill density of 0.6 mg/cm3. There is currently no indication of transfer roll-off with increasing Δλ, indicating that even longer pulses or larger capsules could be driven using the CBET in cylindrical hohlraums. We show that the radiation flux symmetry is well controlled during the foot of the pulse, and that the entire implosion can be tuned symmetrically in the presence of the CBET in this system, with low levels of laser backscatter out of the hohlraum and low levels of hot electron production from intense laser–plasma interactions. Radiation hydrodynamic simulations can accurately represent the early shock symmetry and be used as a design tool, but cannot predict the late-time radiation flux symmetry during the peak of the pulse, and semi-empirical models are used to design the experiments. Deuterium–tritium (DT)-layered tests of 1100 μm inner radius implosions showed performance close to expectations from simulations at velocities up to ~360 km/s, and record yields at this velocity, when increasing the DT fuel layer thickness to mitigate hydrodynamic mixing of the ablator into the hot spot as a result of defects in the ablator. However, when the implosion velocity was increased, mixing due to these defects impacted performance. The ratio of measured to simulated yield for these experiments was directly correlated with the level of observed mixing. These simulations suggest that reducing the mixing, e.g., by improving the capsule defects, could result in higher performance. In addition, future experiments are planned to reduce the coast time at this scale, delay between the peak compression and the end of the laser, to increase the hot spot convergence and pressure. To reduce the coast time by several hundred ps compared to the 1100 μm inner radius implosions, HYBRID-E has also fielded 1050 μm inner radius capsules, which resulted in higher hot spot pressure and a fusion energy yield of ~170 kJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Record >10 MV/cm mesa breakdown fields in Al 0.85 Ga 0.15 N/Al 0.6 Ga 0.4 N high electron mobility transistors on native AlN substrates

The ultra-wide bandgap of Al-rich AlGaN is expected to support a significantly larger breakdown field compared to GaN, but the reported performance thus far has been limited by the use of foreign substrates. In this Letter, the material and electrical properties of Al 0.85 Ga 0.15 N/Al 0.6 Ga 0.4 N high electron mobility transistors (HEMT) grown on a 2-in. single crystal AlN substrate are investigated, and it is demonstrated that native AlN substrates unlock the potential for Al-rich AlGaN to sustain large fields in such devices. We further study how Ohmic contacts made directly to a Si-doped channel layer reduce the knee voltage and increase the output current density. High-quality AlGaN growth is confirmed via scanning transmission electron microscopy, which also reveals the absence of metal penetration at the Ohmic contact interface and is in contrast to established GaN HEMT technology. Two-terminal mesa breakdown characteristics with 1.3 μm separation possess a record-high breakdown field strength of ~11.5 MV/cm for an undoped Al 0.6 Ga 0.4 N-channel layer. The breakdown voltages for three-terminal devices measured with gate-drain distances of 4 and 9 μm are 850 and 1500 V, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Time-domain self-broadened and air-broadened nitrogen S-branch Raman linewidths at 80–200 K recorded in an underexpanded jet

We report pure-rotational N 2 –N 2 , N 2 –air, and O 2 –air S-branch linewidths for temperatures of 80–200 K by measuring the time-dependent decay of rotational Raman coherences in an isentropic free-jet expansion from a sonic nozzle. We recorded pure-rotational hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) spectra along the axial centerline of the underexpanded jet, within the barrel shock region upstream of the Mach disk. The dephasing of the pure-rotational Raman coherence was monitored using probe-time-delay scans at different axial positions in the jet, corresponding to varying local temperatures and pressures. The local temperature was obtained by fitting CARS spectra acquired at zero probe time delay, where the impact of collisions was minimal. The measured decay of each available Raman transition was fit to a dephasing constant and corrected for the local pressure, which was obtained from the CARS-measured static temperature and thermodynamic relationships for isentropic expansion from the known stagnation state. Nitrogen self-broadened transitions decayed more rapidly than those broadened in air for all temperatures, corresponding to higher Raman linewidths. In general, the measured S-branch linewidths deviated significantly in absolute and relative magnitudes from those predicted by extrapolating the modified exponential gap model to low temperatures. The temperature dependence of the Raman linewidth for each measured rotational state of nitrogen (J ≤ 10) and oxygen (N ≤ 11) was fit to a temperature-dependent power law over the measurable temperature domain (80–200 K) and extrapolated to both higher rotational states and room temperature. Furthermore, the measured and modeled low-temperature linewidth data provided here will aid low temperature gas-phase pressure measurements with fs/ps CARS.

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

Record quantum efficiency from strain compensated superlattice GaAs/GaAsP photocathode for spin polarized electron source

Photocathodes based on GaAs and other III–V semiconductors are capable of producing highly spin-polarized electron beams. GaAs/GaAsP superlattice photocathodes exhibit high spin polarization; however, the quantum efficiency (QE) is limited to 1% or less. To increase the QE, we fabricated a GaAs/GaAsP superlattice photocathode with a Distributed Bragg Reflector (DBR) underneath. This configuration creates a Fabry–Pérot cavity between the DBR and GaAs surface, which enhances the absorption of incident light and, consequently, the QE. These photocathode structures were grown using molecular beam epitaxy and achieved record quantum efficiencies exceeding 15% and electron spin polarization of about 75% when illuminated with near-bandgap photon energies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Record magnetic field generation by short-pulse laser-driven capacitor-coil targets

Magnetic fields generated by capacitor-coil targets driven by intense short-pulse lasers have been characterized using ultrafast proton radiography. A 1-kJ, 15-ps laser at a center wavelength of 1053 nm irradiated the back plate of the capacitor with an intensity of ∼8.3 × 10 18 W/cm 2 , creating ultra large currents in the connecting coils. High-quality proton data obtained in the axial probing geometry show definitive signatures of magnetic field generation, allowing precision measurement of the field distribution and strength. The data show a coil current of 120 ± 10 kA producing 200 ± 20 Tesla magnetic fields at the coil center at 1.127 ns after the laser drive. In conclusion, this sets a record for magnetic field generation by the short-pulse-powered capacitor-coil targets.

Gao, Lan [Princeton Plasma Physics Laboratory (PPP↗
DOE OSTI2020

The effect of Cu additions in FePt–BN–SiO 2 heat-assisted magnetic recording media

Structural and chemical order impact magnetic properties of solids, which are governed by spin–orbit coupling and exchange interaction. The ordered L1 0 phase of FePt is a key material to heat-assisted magnetic recording; to enable high storage density, a solid understanding is needed of structural and chemical disorder at small length scales, as well as associated modifications of the electronic band structure. Here, we investigate the effect of boron and copper additions (≲6 mol% Cu) on structural and magnetic properties of L1 0 FePt granular media. Two copper-driven mechanisms, although competing, can lead to improvements in both structural and magnetic properties. In particular, the Cu substitution on the Fe-site leads to a degradation of magnetic properties due to the delocalized electron orbitals originating from a larger Cu d -orbital occupancy. At the same time, Cu substitution leads to an enhanced crystallographic order and consequently magneto-crystalline anisotropy, which offsets the former effect to a large extent. Our study is based on magnetometry, x-ray absorption spectroscopy, ab-initio calculations and a phenomenological theory of disordered FePt granular media. We do not observe a sizable modification to Fe moments and electronic configuration; Cu reveals two different resonances associated with the presence and absence of Cu–B bonds that vary with total Cu concentration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

WEST L-mode record long pulses guided by predictions using Integrated Modeling

A new record was set on the WEST Tokamak, designed to operate long duration plasmas in a tungsten (W) environment, with an injected energy of 1.15 GJ and a plasma duration 364s. Scenario development was supported by integrated modeling using the High Fidelity Plasma Simulator (HFPS), the European IMAS-coupled version of JETTO/JINTRAC, which integrates physics-driven modules into a unified framework. In particular, a reduced model for Lower-Hybrid heating and Current-Drive (LHCD) and the quasi-linear turbulent transport model TGLF are crucial for long pulses predictions up to the Last Closed Flux Surface (LCFS). Using this workflow, a 100 s reference discharge was modeled and plasma kinetic profiles and loop voltage were quantitatively well matched. In preparation for the recent long duration experiments, non-inductive current-drive actuators (I P , n e , P LHCD ) were varied to determine the operational domain going towards fully non-inductive discharges. In particular, decreasing the plasma current is shown to ease the access to such conditions, with a careful monitoring of (n e , P LHCD ) to avoid machine limitations. In addition, post-prediction experiments conducted within the investigated parameter range validated the predicted dependencies and were shown to be in quantitative agreement. Exploratory work on the use of ECCD for MHD stability purpose is also introduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Reconstruction of events recorded with the surface detector of the Pierre Auger Observatory

Cosmic rays arriving at Earth collide with the upper parts of the atmosphere, thereby inducing extensive air showers. When secondary particles from the cascade arrive at the ground, they are measured by surface detector arrays. We describe the methods applied to the measurements of the surface detector of the Pierre Auger Observatory to reconstruct events with zenith angles less than $60^\circ$ using the timing and signal information recorded using the water-Cherenkov detector stations. In addition, we assess the accuracy of these methods in reconstructing the arrival directions of the primary cosmic ray particles and the sizes of the induced showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Deep learning approaches for neural decoding across architectures and recording modalities

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method in many machine learning tasks ranging from speech recognition to image segmentation. The success of deep networks in other domains has led to a new wave of applications in neuroscience. In this article, we review deep learning approaches to neural decoding. Here, we describe the architectures used for extracting useful features from neural recording modalities ranging from spikes to functional magnetic resonance imaging. Furthermore, we explore how deep learning has been leveraged to predict common outputs including movement, speech and vision, with a focus on how pretrained deep networks can be incorporated as priors for complex decoding targets like acoustic speech or images. Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.

59 BASIC BIOLOGICAL SCIENCES↗