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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Substitution Effect on Thiobarbituric Acid End Groups for High Open-Circuit Voltage Non-Fullerene Organic Solar Cells

Recent advances in non-fullerene acceptors (NFAs) have resulted in significant improvement in the power conversion efficiencies (PCEs) of organic solar cells (OSCs). In our efforts to boost open-circuit voltage (V OC ) for OSCs, the molecular design employing thiobarbituric acid (TBTA) end groups and an indacenodithieno[3,2-b]thiophene (IDTT) core gives rise to NFAs with significantly raised lowest unoccupied molecular orbital (LUMO) energy level, which, when paired with PCE10, can achieve V OC 's over 1.0 V and decent PCEs that outperform the equivalent devices based on the benchmark ITIC acceptor. While the use of a TBTA end group is effective in tuning energy levels, very little is known about how the alkyl substitution on the TBTA group impacts the solar cell performance. To this end, TBTA end groups are alkylated with linear, branched, and aromatic sidechains to understand the influence on thin-film morphology and related device performances. We report our study has confirmed the dependence of solar cell performance on the end-group substituents. More importantly, we reveal the presence of an ideal window of crystallinity associated with the medium-length hydrocarbon chains such as ethyl and benzyl. Deviation to the shorter methyl group makes the acceptor too crystalline to mix with the polymer donor and form proper domains, whereas longer and branched alkyl chains are too sterically bulky and hinder charge transport due to nonideal packing. Such findings underline the comprehensive nature of thin-film morphology and the subtle end-group effects for the design of non-fullerene acceptors.

14 SOLAR ENERGY↗
DOE OSTI2023

A rule-free workflow for the automated generation of databases from scientific literature

Abstract In recent times, transformer networks have achieved state-of-the-art performance in a wide range of natural language processing tasks. Here we present a workflow based on the fine-tuning of BERT models for different downstream tasks, which results in the automated extraction of structured information from unstructured natural language in scientific literature. Contrary to existing methods for the automated extraction of structured compound-property relations from similar sources, our workflow does not rely on the definition of intricate grammar rules. Hence, it can be adapted to a new task without requiring extensive implementation efforts and knowledge. We test our data-extraction workflow by automatically generating a database for Curie temperatures and one for band gaps. These are then compared with manually curated datasets and with those obtained with a state-of-the-art rule-based method. Furthermore, in order to showcase the practical utility of the automatically extracted data in a material-design workflow, we employ them to construct machine-learning models to predict Curie temperatures and band gaps. In general, we find that, although more noisy, automatically extracted datasets can grow fast in volume and that such volume partially compensates for the inaccuracy in downstream tasks.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Strong and recyclable bio-derived poly(ester amide) hot-melt adhesive

Bio-based adhesives offer inherent advantages over conventional petrochemical-derived systems, including renewable sourcing, reduced environmental impact and potential degradability. However, most bio-based adhesives suffer from poor adhesion strength, limited substrate compatibility and a lack of chemical recyclability. Here, in this work, we present a bio-derived multiblock poly(ester amide) adhesive that leverages microphase segregation between different segments to reconcile mechanical robustness with strong interfacial bonding. Notably, this multiblock architecture is accessed through a one-pot, selective acceptorless dehydrogenative polymerization, obviating the need for multistep synthesis. The materials exhibit excellent adhesion across a range of substrates including metals, glass and wet wood surpassing commercial benchmarks, while also demonstrating thermal stability, tunable mechanical properties and closed-loop chemical recyclability even in the presence of other commodity plastics. Furthermore, the adhesive strength of these materials could be tuned for various potential applications through control over the chemical composition of the polymer. By integrating renewable feedstocks, high-performance functionality and efficient chemical circularity within a single platform, this work provides a viable pathway toward more sustainable adhesive technologies and contributes to advancing circular materials manufacturing.

09 BIOMASS FUELS↗
DOE OSTI2024

Numerical studies of collinear laser-assisted injection from a foil for plasma wakefield accelerators

We present a laser-assisted electron injection scheme for beam-driven plasma wakefield acceleration. The laser is collinear with the driver and triggers the injection of hot electrons into the plasma wake by interaction with a thin solid target. We present a baseline case using the AWAKE Run 2 parameters and then perform variations on key parameters to explore the scheme. It is found that the trapped witness electron charge may be tuned by altering laser parameters, with a strong dependence on the phase of the wake upon injection. Normalized emittance settles at the order of micrometres and varies with witness charge. The scheme is robust to misalignment, with a 1/10th plasma skin-depth offset ( 20 μ m for the AWAKE case) having a negligible effect on the final beam. The final beam quality is better than similar existing schemes, and several avenues for further optimization are indicated. The constraints on the AWAKE experiment are very specific, but the general principles of this mechanism can be applied to future beam-driven plasma wakefield accelerator experiments. Published by the American Physical Society 2024

Physics↗
DOE OSTI2021

An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty

A modern power system is characterized by a stochastic variation of the loads and an increasing penetration of renewable energy generation, which results in large uncertainties in its states. These uncertainties bring formidable challenges to the power system planning and operation process. To address these challenges, we propose a cost-effective, iterative response-surface-based approach for the chance-constrained AC optimal power-flow problem that aims to ensure the secure operation of the power systems considering dependent uncertainties. Starting from a stochastic-sampling-based framework, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose, instead of using the original complicated power-system model, to rely on a polynomial-chaos-based response surface. This response surface allows us to efficiently evaluate the time-consuming power-system model at arbitrary distributed sampled values with a negligible computational cost. This further enables us to efficiently conduct an online stochastic testing for the system states that not only screens out the statistical active constraints, but also assists in a better design of the tightened bounds without using any Gaussian or symmetric assumption. Finally, an iterative procedure is executed to fine-tune the optimal solution that better satisfies a predefined probability. The simulations conducted in multiple test systems demonstrate the excellent performance of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Measurement of the Lund jet plane in hadronic decays of top quarks and W bosons with the ATLAS detector

The Lund jet plane (LJP) is measured for the first time in $t\bar{t}$ events, using 140 $\textrm{fb}^{-1}$ of $\sqrt{s} = 13$ TeV pp collision data collected with the ATLAS detector at the LHC. The LJP is a two-dimensional observable of the sub-structure of hadronic jets that acts as a proxy for the kinematics of parton showers and hadron formation. The observable is constructed from charged particles and is measured for R = 1.0 anti-$k_t$ jets with transverse momentum above 350 GeV containing the full decay products of either a top quark or a daughter W boson. The other top quark in the event is identified from its decay into a b-quark, an electron or a muon and a neutrino. The measurement is corrected for detector effects and compared with a range of Monte Carlo predictions sensitive to different aspects of the hadronic decays of the heavy particles. In the W-boson-initiated jets, all the predictions are incompatible with the measurement. In the top quark initiated jets, disagreement with all predictions is observed in smaller subregions of the plane, and with a subset of the predictions across the fiducial plane. The measurement could be used to improve the tuning of Monte Carlo generators, for better modelling of hadronic decays of heavy quarks and bosons, or to improve the performance of jet taggers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

(Invited) Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO 2 R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. We specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

42 ENGINEERING↗
DOE OSTI2020

Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO2R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. Here, we specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying solely on machine learning interatomic potential (MLIP) models. To this end, we first curate a large-scale molecular relaxation dataset comprising 3.5 million molecules and 300 million snapshots. Then MLIP pre-trained models are trained with supervised learning to predict energy and forces given 3D molecular structures. Once trained, we show that the pre-trained models can be used in different ways to obtain geometries either explicitly or implicitly. First, it can be used to obtain approximate low-energy 3D geometries via geometry optimization. While these geometries do not consistently reach DFT-level chemical accuracy or convergence, they can still improve downstream performance compared to non-relaxed structures. To mitigate potential biases and enhance downstream predictions, we introduce geometry fine-tuning based on the relaxed 3D geometries. Second, the pre-trained models can be directly fine-tuned for property prediction when ground truth 3D geometries are available. Our results demonstrate that MLIP pre-trained models trained on relaxation data can learn transferable molecular representations to improve downstream molecular property prediction and can provide practically valuable but approximate molecular geometries that benefit property predictions. Our code is publicly available at: https://github.com/divelab/AIRS/.

Fu, Cong [Texas A & M Univ., College Station, TX (↗
DOE OSTI2022

Factors Controlling a Synthetic Aperture Radar (SAR) Derived Root-Zone Soil Moisture Product over The Seward Peninsula of Alaska

Root-zone soil moisture exerts a fundamental control on vegetation, energy balance, and the carbon cycle in Arctic ecosystems, but it is still not well understood in vast, remote, and understudied regions of discontinuous permafrost. The root-zone soil moisture product (30 m resolution) used in this analysis was retrieved from a time-series P-Band (420–440 MHz) synthetic aperture radar (SAR) backscatter observations (August 2017 & October 2017). While similar approaches have been taken to retrieve surface (0 cm to 5 cm) soil moisture from L-Band (1.2 GHz) SAR backscatter, this is one of the first known attempts at reaching the root-zone in permafrost regions. Here, we analyze secondary factors (excluding primary factors, such as precipitation) controlling summer (August) soil moisture at depths of 6 cm, 12 cm, and 20 cm over a 4500 km2 area on the Seward Peninsula of Alaska. Using a random forest model, we quantify the impact of topography, vegetation, and meteorological factors on soil moisture distributions. In developing the random forest model, we explore a variety of feature scales (30 m, 60 m, 90 m, 120 m, 180 m, and 240 m), tune hyperparameters (the structure of individual decision trees making up the ensemble including the number and depth of trees), and perform the final feature selection using cross-validated recursive feature elimination. Results suggest that root-zone soil moisture on the Seward Peninsula is primarily controlled by vegetation at 6 cm, but deeper in the soil column topography and meteorological factors, such as predominant winter wind direction and summer insolation, play a larger role. The random forest model accounts for 40% to 60% of the variation observed (R2 = 0.44 at 6 cm, R2 = 0.52 at 12 cm, R2 = 0.58 at 20 cm). These results indicate that vegetation is the dominant control on soil moisture shallow in the soil column, but the impact of vegetation does not extend to deeper layers retrieved from P-Band SAR backscatter.

Dann, Julian↗
NASA NTRS1993

A low noise 665 GHz SIS quasi-particle waveguide receiver

Recent results on a 565-690 GHz SIS heterodyne receiver employing a 0.36 micron(sup 2) Nb/AlOx/Nb SIS tunnel junction with high quality circular non-contacting back short and E-plane tuners in a full height wave guide mount are reported. No resonant tuning structures were incorporated in the junction design at this time, even though such structures are expected to help the performance of the receiver. The receiver operates to at least the gap frequency of Niobium, approximately 680 GHz. Typical receiver noise temperatures from 565-690 GHz range from 160K to 230K with a best value of 185K DSB at 648 GHz. With the mixer cooled from 4.3K to 2K the measured receiver noise temperatures decreased by approximately 15 percent, giving roughly 180K DSB from 660 to 680 GHz. The receiver has a full 1 GHz IF pass band and was successfully installed at the Caltech Submillimeter Observatory in Hawaii.

Kooi, J. W.↗
NASA NTRS1994

Mobile robot exploration and navigation of indoor spaces using sonar and vision

Integration of skills into an autonomous robot that performs a complex task is described. Time constraints prevented complete integration of all the described skills. The biggest problem was tuning the sensor-based region-finding algorithm to the environment involved. Since localization depended on matching regions found with the a priori map, the robot became lost very quickly. If the low level sensing of the world is not working, then high level reasoning or map making will be unsuccessful.

Kortenkamp, David↗
NASA NTRS2007

Recommendations for Refinement and Validation of Intermittent Artificial Gravity

The IMAG Pilot Study, recently completed at the University of Texas Medical Branch, filled in the second major gap in knowledge standing in the way of development of a practical Short Radius Centrifuge (SRC) and the use of Artificial Gravity (AG) as a multi-system countermeasure to combat the deconditioning associated with extended weightlessness. (The first challenge, to adapt rapidly rotating subjects to permit unlimited head movements without excessive motion sickness, was achieved in a series of studies at MIT involving incremental increases in head and centrifuge velocity.) It remained to be demonstrated that intermittent exposure to AG, at only one hour per day for 21 days, would have any positive effect on slowing or eliminating of deconditioning. Bed-rested normal subjects were used as a ground analog for astronauts in weightlessness. The results are clearly positive for the key physiological systems of interest: cardiovascular, muscle, and bone. No functionally relevant changes were observed in immune, cognitive, or sensory-motor function. Furthermore, we found that our initial concerns about the inability of deconditioned subjects to withstand daily centrifugation without syncope were misplaced. These encouraging initial results clearly support the further development of AG protocols. We recommend, as the next steps, the integration of a controlled exercise device on the SRC to determine the synergy between AG and exercise. Coupled with appropriate exercise device(s) the AG protocol will be tuned to-ward an optimal prescription for minimum exposure duration and frequency, maximum AG level and SRC speed.. Performance of these next steps will require extensive use of bed-rest/centrifuge facilities and eventually validation using an SRC in space. A space SRC could be placed in the ISS or on a planetary surface.

Young, Lauren R.↗
NASA NTRS2007

High Temperature Metallic Seal/Energizer Development for Aero Propulsion and Gas Turbine Applications

The Ultra High Temperature seal program has successfully progressed and developed a high temperature static seal solution. The third prototype has successfully combined the first and second prototypes high performance capabilities in a commercially viable solution. Prototype II and Prototype III are viable solutions: Prototype II offers flexible load tune ability and seating load adjustment and Prototype III offers commercial viability for continuous hoop seals.

More, Greg↗
NASA NTRS2012

Extreme Tele-Echocardiography: Methodology for Remote Guidance of In-Flight Echocardiography Aboard the International Space Station

Methods: In the year before launch of an ISS mission, potential astronaut echocardiographic operators participate in 5 sessions to train for echo acquisitions that occur roughly monthly during the mission, including one exercise echocardiogram. The focus of training is familiarity with the study protocol and remote guidance procedures. On-orbit, real-time guidance of in-flight acquisitions is provided by a sonographer in the Telescience Center of Mission Control. Physician investigators with remote access are able to relay comments on image quality to the sonographer. Live video feed is relayed from the ISS to the ground via the Tracking and Data Relay Satellite System with a 2- second transmission delay. The expert sonographer uses these images, along with twoway audio, to provide instructions and feedback. Images are stored in non-compressed DICOM format for asynchronous relay to the ground for subsequent off-line analysis. Results: Since June, 2009, a total of 27 resting echocardiograms and 5 exercise studies have been performed during flight. Average acquisition time has been 45 minutes, reflecting 26,000 km of ISS travel per study. Image quality has been adequate in all studies, and remote guidance has proven imperative for fine-tuning imaging and prioritizing views when communication outages limit the study duration. Typical resting studies have included 27 video loops and 30 still-frame images requiring 750 MB of storage. Conclusions: Despite limited crew training, remote guidance allows research-quality echocardiography to be performed by non-experts aboard the ISS. Analysis is underway and additional subjects are being recruited to define the impact of microgravity on cardiac structure and systolic and diastolic function.

Martin, David S.↗
NASA NTRS2013

Investigation of International Space Station Major Constituent Analyzer Anomalous ORU 02 Performance

The Major Constituent Analyzer (MCA) is a mass spectrometer based system that measures the major atmospheric constituents on the International Space Station. In 2011, two MCA ORU 02 analyzer assemblies experienced premature on-orbit failures. These failures were determined to be the result of off-nominal ion source filament performance. Recent product improvements to ORU 02 designed to improve the lifetime of the ion pump also constrained the allowable tuning criteria for the ion source filaments. This presentation describes the filament failures as well as the corrective actions implemented to preclude such failures in the future.

Gardner, Ben D.↗
NASA NTRS2014

Co(x)Ni(4-x)Sb(12-y)Sn(y) Ternary Skutterudites: Processing and Thermoelectric Properties

Skutterudites have proven to be a useful thermoelectric system as a result of their high figure of merit, favorable mechanical properties, and good thermal stability. Binary skutterudites have received the majority of interest in recent years, as a result of successful double and triple filling schemes. Ternary skutterudites, such as Ni4Sb7Sn5, also demonstrate good thermoelectric performance, with high power factor and low thermal conductivity. Ternary skutterudites, as contrasted to binary systems, provide more possibility for tuning electronic structure as substitutions can be studied on three elements. The Co(x)Ni(4-x)Sb(12-y)Sn(y) system has been investigated as both a p- and n-type thermoelectric material, stable up to 200 C. The system is processed through a combination of solidification, mechanical alloying, and hot pressing steps. Rietveld structure refinement has revealed an interesting occupancy of Sn on both the 24g Wyckoff position with Sb as well as the 2a position as a rattler. In addition to thermoelectric properties, detailed processing routes have been investigated on the system.

Seebeck effect↗
NASA NTRS2022

HYPERFIRE

The two main sub-scale, ground-based rocket aerodynamics testing techniques – hot-fire testing and cold-flow testing – pose a series of tradeoffs. Hot-fire testing is generally much more accurate, but is often burdensome, costly, and requires long lead times due to design work, infrastructure preparation, etc. Cold-flow testing is much less expensive and has a rapid turnaround time, but conventional simulants (e.g., nitrogen, steam) used in cold-flow testing yield less accurate results (i.e., results that are not sufficiently representative of test article performance). While researching methods to optimize such tradeoffs, engineers at NASA’s Stennis Space Center discovered that ethane can be tuned to approximate rocket exhaust plumes generated by several common rocket propellants. This led NASA to develop the HYdrocarbon Propellants Enabling Reproduction of Flows in Rocket Engines (HYPERFIRE), a sub-scale, non-reacting flow test system. HYPERFIRE uses heated ethane to enable physical simulation of rocket engines powered by a broad range of propellants in an inexpensive, accurate, and simple fashion.

sub-scale↗