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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data for Process Strategies for Recovery of Sugars, Lipids, and Lignin from Oilcane Bagasse Using Natural Deep Eutectic Solvents (NADES)

Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investigation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. This study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.

Conversion↗
DOE OSTI2024

Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets

Abstract Modern data mining methods have demonstrated effectiveness in comprehending and predicting materials properties. An essential component in the process of materials discovery is to know which material(s) will possess desirable properties. For many materials properties, performing experiments and density functional theory computations are costly and time-consuming. Hence, it is challenging to build accurate predictive models for such properties using conventional data mining methods due to the small amount of available data. Here we present a framework for materials property prediction tasks using structure information that leverages graph neural network-based architecture along with deep-transfer-learning techniques to drastically improve the model’s predictive ability on diverse materials (3D/2D, inorganic/organic, computational/experimental) data. We evaluated the proposed framework in cross-property and cross-materials class scenarios using 115 datasets to find that transfer learning models outperform the models trained from scratch in 104 cases, i.e., ≈90%, with additional benefits in performance for extrapolation problems. We believe the proposed framework can be widely useful in accelerating materials discovery in materials science.

Chemistry↗
NASA NTRS2015

Utilization of the Deep Space Atomic Clock for Europa Gravitational Tide Recovery

Estimation of Europa's gravitational tide can provide strong evidence of the existence of a subsurface liquid ocean. Due to limited close approach tracking data, a Europa flyby mission suffers strong coupling between the gravity solution quality and tracking data quantity and quality. This work explores utilizing Low Gain Antennas with the Deep Space Atomic Clock (DSAC) to provide abundant high accuracy uplink-only radiometric tracking data. DSAC's performance, expected to exhibit an Allan Deviation of less than 3e-15 at one day, provides long-term stability and accuracy on par with the Deep Space Network ground clocks, enabling one-way radiometric tracking data with accuracy equivalent to that of its two-way counterpart. The feasibility of uplink-only Doppler tracking via the coupling of LGAs and DSAC and the expected Doppler data quality are presented. Violations of the Kalman filter's linearization assumptions when state perturbations are included in the flyby analysis results in poor determination of the Europa gravitational tide parameters. B-plane targeting constraints are statistically determined, and a solution to the linearization issues via pre-flyby approach orbit determination is proposed and demonstrated.

Seubert, Jill↗
DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2

Abstract Recent advances in scanning transmission electron microscopy (STEM) allow the real-time visualization of solid-state transformations in materials, including those induced by an electron beam and temperature, with atomic resolution. However, despite the ever-expanding capabilities for high-resolution data acquisition, the inferred information about kinetics and thermodynamics of the process, and single defect dynamics and interactions is minimal. This is due to the inherent limitations of manual ex situ analysis of the collected volumes of data. To circumvent this problem, we developed a deep-learning framework for dynamic STEM imaging that is trained to find the lattice defects and apply it for mapping solid state reactions and transformations in layered WS 2 . The trained deep-learning model allows extracting thousands of lattice defects from raw STEM data in a matter of seconds, which are then classified into different categories using unsupervised clustering methods. We further expanded our framework to extract parameters of diffusion for sulfur vacancies and analyzed transition probabilities associated with switching between different configurations of defect complexes consisting of Mo dopant and sulfur vacancy, providing insight into point-defect dynamics and reactions. This approach is universal and its application to beam-induced reactions allows mapping chemical transformation pathways in solids at the atomic level.

36 MATERIALS SCIENCE↗
DOE OSTI2017

In situ determination of crystal structure and chemistry of minerals at Earth's deep lower mantle conditions

Recent advances in experimental techniques and data processing allow in situ determination of mineral crystal structure and chemistry up to Mbar pressures in a laser-heated diamond anvil cell (DAC), providing the fundamental information of the mineralogical constitution of our Earth's interior. This work highlights several recent breakthroughs in the field of high-pressure mineral crystallography, including the stability of bridgmanite, the single-crystal structure studies of post-perovskite and H-phase as well as the identification of hydrous minerals and iron oxides in the deep lower mantle. The future development of high-pressure crystallography is also discussed.

58 GEOSCIENCES↗
DOE OSTI2019

Absorption Spectra of Acetylene, Vinylidene, and Their Deuterated Isotopologues on Ab Initio Potential Energy and Dipole Moment Surfaces

Here, the absorption spectra of acetylene (HCCH) and vinylidene (H 2 CC) as well as their deuterated isotopologues are investigated theoretically on a near spectroscopically accurate full-dimensional potential energy surface reported in an earlier publication, using dipole moment surfaces reported in this work, which are constructed with a neural network method from a large number of ab initio data points. These global surfaces cover not only the deep acetylene well, but also the vinylidene well, as well as the transition region between the two isomers. The agreement with available experimental data for acetylene is excellent, validating both the potential energy surface and the dipole moment surfaces. The infrared spectra of vinylidene and its deuterated isotopologues are predicted. The potential and dipole moment surfaces lay the foundation for future spectroscopic studies of the acetylene-vinylidene isomerization involving large amplitude motions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Serendipitous EUV sources detected during the first year of the Extreme Ultraviolet Explorer right angle program

We report the detection of 114 extreme ultraviolet (EUV; 58 - 740 A) sources, of which 99 are new serendipitous sources, based on observations made with the imaging telescopes on board the Extreme Ultraviolet Explorer (EUVE) during the Right Angle Program (RAP). These data were obtained using the survey scanners and the Deep Survey instrument during the first year of the spectroscopic guest observer phase of the mission, from January 1993 to January 1994. The data set consists of 162 discrete pointings whose exposure times are typically two orders of magnitude longer than the average exposure times during the EUVE all-sky survey. Based on these results, we can expect that EUVE will serendipitously detect approximately 100 new EUV sources per year, or about one new EUV source per 10 sq deg, during the guest observer phase of the EUVE mission. New EUVE sources of note include one B star and three extragalactic objects. The B star (HR 2875, EUVE J0729 - 38.7) is detected in both the Lexan/B (approximately 100 A) and Al/Ti/C (approximately 200 A) bandpasses, and the detection is shown not to be a result of UV leaks. We suggest that we are detecting EUV and/or soft x rays from a companion to the B star. Three sources, EUVE J2132+10.1, EUVE J2343-14.9, and EUVE J2359-30.6 are identified as the active galactic nuclei MKN 1513, MS2340.9-1511, and 1H2354-315, respectively.

Mcdonald, K.↗
NASA NTRS1995

Interplanetary space science data base and access/display tool on the NSSDC heliospheric CD-ROM

The National Space Science Data Center (NSSDC) has accumulated a rich archive of heliospheric, magnetospheric, and ionospheric data, as well as data from most other NASA-involved science disciplines. To facilitate access to and use of these data, NSSDC has begun to put selected data onto CD-ROM's. This paper describes one such CD-ROM, and the access and display software developed at NSSDC to support its use. The data on the CD-ROM consist primarily of hourly solar wind magnetic field and plasma data from many near-Earth spacecraft (OMNI) and deep space spacecraft (Voyagers, Pioneers, Helios, Pioneer Venus Orbiter). In addition, 5-minute resolution IMP-8 and ISEE-3 magnetic field and plasma data are also included. Data are stored in both ASCII and CDF formats.

Papitashvili, N. E.↗
NASA NTRS1993

Thin current sheets in the deep geomagnetic tail

The International Sun-Earth Explorer 3 (ISEE-3) magnetic field and plasma electron data from Jan - March 1983 have been searched to study thin current sheets in the deep tail region. 33 events were selected where the spacecraft crossed through the current sheet from lobe to lobe within 15 minutes. The average thickness of the observed current sheets was 2.45 R(sub E), and in 24 cases the current sheet was thinner than 3.0 R(sub E); 6 very thin current sheets (thickness lambda less than 0.5 R(sub E) were found. The electron data show that the very thin current sheets are associated with considerable temperature anisotropy. On average, the electron gradient current was about 17% of the total current, whereas the current arising from the electron temperature anisotropy varied between 8-45% of the total current determined from the lobe field magnitude.

Pulkkinen, T. I.↗
DOE OSTI2026

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗
NASA NTRS2011

The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.

quality of service↗
NASA NTRS2015

Programmable Ultra-Lightweight System Adaptable Radio

The programmable ultra-lightweight system adaptable radio (PULSAR) is a NASA Marshall Space Flight Center transceiver designed for the CubeSat market, but has the potential for other markets. The PULSAR project aims to reduce size, weight, and power while increasing telemetry data rate. The current version of the PULSAR has a mass of 2.2 kg and a footprint of 10.8 cm2. The height depends on the specific configuration. The PULSAR S-Band Communications Subsystem is an S- and X-band transponder system comprised of a receiver/detector (receiver) element, a transmitter element(s), and related power distribution, command, control, and telemetry element for operation and information interfaces. It is capable of receiving commands, encoding and transmitting telemetry, as well as providing tracking data in a manner compatible with Earthbased ground stations, near Earth network, and deep space network station resources. The software-defined radio's (SDR's) data format characteristics can be defined and reconfigured during spaceflight or prior to launch. The PULSAR team continues to evolve the SDR to improve the performance and form factor to meet the requirements that the CubeSat market space requires. One of the unique features is that the actual radio design can change (somewhat), but not require any hardware modifications due to the use of field programmable gate arrays.

Werkheiser, Arthur↗
NASA NTRS1966

DSIF FR-900 video recorders

Deep Space Instrumentation Facility FR-900 ROTARY head magnetic tape recorders for acquiring video data from lunar orbiter

MAGNETIC TAPE RECORDER↗
DOE OSTI2021

End-to-End Jet Classification of Boosted Top Quarks with CMS Open Data

We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use lowlevel detector information from the simulated CMS Open Data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves a ROC-AUC score of 0.975±0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier ROC-AUC score increases to 0.9824±0.0013, serving as the first performance benchmark for these CMS Open Data samples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2014

The Upside-Down Biosphere: Evidence for the Partially Oxygenated Oceans During the Archean Eon

This is a commentary on the preceding chapter by Ohmoto et al., in which it is suggested that oxygen concentrations have been high throughout Earth history. This is a contentious suggestion at odds with the prevailing view in the field, which contends that atmospheric oxygen concentrations rose from trace levels to a few percent of modern-day levels around 2.5 b.y. ago. This comment notes that many of the data sets cited by Ohmoto et al. as evidence for a relatively oxidized environment come from deep-ocean settings. This presents a possibility to reconcile some of these data and suggestions with the overwhelming evidence for an atmosphere free of oxygen at that time. Specifically, it is possible that deep-ocean waters were relatively oxidized with respect to certain redox pairs. These deep-ocean waters would have been more oxidized than surface waters, thus representing an "upside-down biosphere," as originally proposed 25 years ago by Jim Walker.

oxygenated oceans↗