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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Quantification of [MTBD][beti] loading and its effects on Pt/HSC electrode performance in hydrogen fuel cells

High surface area carbon-supported platinum catalysts (Pt/HSC) are widely used in polymer electrolyte membrane fuel cells but often suffer from limited proton and oxygen transport within porous domains. To address these challenges, we integrate the ionic liquid [MTBD][beti] into Pt/HSC catalyst layers using two deposition methods-one-pot and sequential deposition-to tune IL distribution within micropores and mesopores. A combination of ex situ and in operando techniques were employed to elucidate electrode structure-performance relationships across a range of IL loadings. Sequential deposition achieved more efficient pore filling and higher IL retention at lower IL:C ratios, enabling enhanced proton conductivity and protection of active sites. Compared to the IL-free Pt/HSC, IL-modified electrodes demonstrated up to 28% improvement in mass activity and enhanced high-current-density performance under low relative humidity, while maintaining comparable performance under humidified conditions. Electrochemical impedance spectroscopy and CO displacement experiments reveal that improvements are linked to reduced ionic resistance and lower sulfonate adsorption on Pt sites, rather than changes in electrochemical surface area. However, excessive IL loading leads to mass transport losses. These results highlight the importance of selective pore filling and efficient IL distribution in achieving kinetic gains without compromising ionic and gas transport.

08 HYDROGEN↗
DOE OSTI2022

Chemical Tuning Meets 2D Molecular Magnets

Two-dimensional (2D) magnets provoke a surge of interest in large anisotropy in reduced dimensions and are promising for next-generation information technology where dynamic magnetic tuning is essential. Until recently, the crucial metal-organic magnet Cr(pyz) 2 ∙xLiCl∙yTHF with considerable high coercivity and high-temperature magnetic order opens up a new platform to control magnetism in metal-organic materials at room temperature. Here we report an in-situ chemical tuning route to realize the controllable transformation of low-temperature magnetic order into room-temperature hard magnetism in Cr(pyz) 2 ∙xLiCl∙yTHF. The chemical tuning via electrochemical lithiation and solvation/desolvation exhibits continuously variable magnetic features from cryogenic magnetism to the room-temperature optimum performance of coercivity (H c ) of 8500 Oe and energy product of 0.6 MGOe. Such chemically flexible tunability of room-temperature magnetism is ascribed to the different degrees of lithiation and solvation that modify the stoichiometry and Cr-pyrazine coordination framework. Furthermore, the additively manufactured hybrid magnets show air stability and electromagnetic induction, providing potential applications. Our findings here suggest chemical tuning as a universal approach to control the anisotropy and magnetism of 2D hybrid magnets at room temperature, promising for data storage, magnetic refrigeration, and spintronics.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Large format imaging arrays for the Atacama Cosmology Telescope

We describe progress in the fabrication, characterization, and production of detector arrays for the Atacama Cosmology Telescope (ACT). The completed ACT instrument is specified to image simultaneously at 145, 225, and 265 GHz using three 32x32 filled arrays of superconducting transition edge sensors (TES) read out with time-division-multiplexed SQUID amplifiers. We present details of the pixel design and testing including the optimization of the electrical parameters for multiplexed readout. Using geometric noise suppression and careful tuning of operation temperature and device bias resistance, the excess noise in the TES devices is balanced with detector speed for interfacing with the ACT optics. The design also accounts for practical tolerances such as transition temperature gradients and scatter that occur in the production of multiple wafers to populate fully the kilopixel cameras. We have developed an implanted absorber layer compatible with our silicon-on-insulator process that allows for tunable optical resistance with requisite on-wafer uniformity and wafer-to-wafer reproducibility. Arrays of 32 elements have been tested in the laboratory environment including electrical, optical, and multiplexed performance. Given this pixel design, optical tests and modeling are used to predict the performance of the filled array under anticipated viewing conditions. Integration of the filled array of pixels with a tuned backshort and dielectric plate in front of the array maximize absorption and the focal plane and suppress reflections. A mechanical design for the build of the full structure is completed and we report on progress toward the construction of a prototype array for first light on the ACT.

Chervenak, J. A.↗
NASA NTRS1984

Analytic investigation of helicopter rotor blade appended aeroelastic devices

Analytic evaluations of four different passive aeroelastic devices appended to helicopter rotor blades are presented. The devices consist of a passive tuned tab, a control coupled tab, an all-flying tip and a harmonic dilational airfoil tip. Each device was conceived for improving either aerodynamic performance or reducing vibratory control loads or hub shears. The evaluation was performed using a comprehensive rotor aeroelastic analysis (the G400PA code with appropriate modifications), together with data for a realistic helicopter rotor blade (the UH-60A Blackhawk), in high speed flight (90 m/s, 175 kts). The results of this study show that significant performance (L/(D sub e)) gains can be achieved with the all-flying free tip. Results from the harmonic dilational airfoil tip show the potential for moderate improvements in L/(D sub e). Finally, the results for the passive tuned tab and the control coupled tab, as configured for this study, show these devices to be impractical. Sections are included which describe the operation of each device, the required G400PA modifications, and the detailed results obtained for each device.

Bielawa, Richard L.↗
DOE OSTI2021

Stoichiometric tuning of lattice flexibility and Na diffusion in NaAlSiO 4 : quasielastic neutron scattering experiment and ab initio molecular dynamics simulations

We have performed quasielastic neutron scattering (QENS) experiments up to 1243 K and ab initio molecular dynamics (AIMD) simulations to investigate the Na diffusion in various phases of NaAlSiO4 (NASO), namely, low-carnegieite (L-NASO; trigonal), high-carnegieite (H-NASO; cubic) and nepheline (N-NASO; hexagonal) phases. The QENS measurements reveal Na ions localized diffusion behavior in L-NASO and N-NASO, but long-range diffusion behavior in H-NASO. Furthermore, the AIMD simulation supplemented the QENS measurements and showed that excess Na ions in H-NASO enhance the host network flexibility and activate the AlO 4 /SiO 4 tetrahedra rotational modes. These framework modes enable the long-range diffusion of Na across a pathway of interstitial sites. The simulations also show Na diffusion in Na-deficient N-NASO through vacant Na sites along the hexagonal c-axis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis

Local Fourier analysis is a useful tool for predicting and analyzing the performance of many efficient algorithms for the solution of discretized PDEs, such as multigrid and domain decomposition methods. The crucial aspect of local Fourier analysis is that it can be used to minimize an estimate of the spectral radius of a stationary iteration, or the condition number of a preconditioned system, in terms of a symbol representation of the algorithm. In practice, this is a “minimax” problem, minimizing with respect to solver parameters the appropriate measure of work, which involves maximizing over the Fourier frequency. Often, several algorithmic parameters may be determined by local Fourier analysis in order to obtain efficient algorithms. Analytical solutions to minimax problems are rarely possible beyond simple problems; the status quo in local Fourier analysis involves grid sampling, which is prohibitively expensive in high dimensions. In this paper, we propose and explore optimization algorithms to solve these problems efficiently. Finally, several examples, with known and unknown analytical solutions, are presented to show the effectiveness of these approaches.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

High performance data acquisition, identification, and monitoring for active magnetic bearings

Future active magnetic bearing systems (AMB) must feature easier on-site tuning, higher stiffness and damping, better robustness with respect to undesirable vibrations in housing and foundation, and enhanced monitoring and identification abilities. To get closer to these goals we developed a fast parallel link from the digitally controlled AMB to Matlab, which is used on a host computer for data processing, identification, and controller layout. This enables the magnetic bearing to take its frequency responses without using any additional measurement equipment. These measurements can be used for AMB identification.

Herzog, Raoul↗
DOE OSTI2022

Electron Redistributed S-Doped Nickel Iron Phosphides Derived from One-Step Phosphatization of MOFs for Significantly Boosting Electrochemical Water Splitting

Nonprecious transition metal-organic frameworks (MOFs) are one of the most promising precursors for developing electrocatalysts with high porosity and structural rigidity. This study reports the synthesis of high efficiency electrocatalysts based on S-doped NiFeP. MOF-derived S-doped NiFeP structure is synthesized by a one-step phosphorization process with using S-doped MOFs as the precursor, which is more convenient and environment friendly, and also helps retain the samples’ framework. The oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) performance of the NiFeP catalysts can be improved after partially replacing P by S due to the tunable electronic structure. The optimized CCS-NiFeP-10 reaches a current density of 10 mA cm –2 for OER with an overpotential of 201 mV and outperforms most NiFe-based catalysts. The S doping plays an important role in tuning the ΔG values for intermediates formation in Ni atoms to a suitable value and exhibits a pronouncedly improved the OER performance. CCS-NiFeP-20 sample presents excellent HER performance due to the d-band center downshifting from the Fermi level. When the voltage of the electrolytic cell is 1.50 V, a current density of 10 mA cm –2 can be obtained. This strategy paves the way for designing highly active none-noble metal catalysts.

36 MATERIALS SCIENCE↗
NASA NTRS2003

An Integrated Approach to Thermal Management of International Space Station Logistics Flights, Improving the Efficiency

The efficiency of re-useable aerospace systems requires a focus on the total operations process rather than just orbital performance. For the Multi-Purpose Logistics Module this activity included special attention to terrestrial conditions both pre-launch and post-landing and how they inter-relate to the mission profile. Several of the efficiencies implemented for the MPLM Mission Engineering were NASA firsts and all served to improve the overall operations activities. This paper will provide an explanation of how various issues were addressed and the resulting solutions. Topics range from statistical analysis of over 30 years of atmospheric data at the launch and landing site to a new approach for operations with the Shuttle Carrier Aircraft. In each situation the goal was to "tune" the thermal management of the overall flight system for minimizing requirement risk while optimizing power and energy performance.

Holladay, Jon↗
DOE OSTI2023

Lignin conversion to β-ketoadipic acid by Pseudomonas putida via metabolic engineering and bioprocess development

Bioconversion of a heterogeneous mixture of lignin-related aromatic compounds (LRCs) to a single product via microbial biocatalysts is a promising approach to valorize lignin. Here, Pseudomonas putida KT2440 was engineered to convert mixed p-coumaroyl– and coniferyl-type LRCs to β-ketoadipic acid, a precursor for performance-advantaged polymers. Expression of enzymes mediating aromatic O-demethylation, hydroxylation, and ring-opening steps was tuned, and a global regulator was deleted. β-ketoadipate titers of 44.5 and 25 grams per liter and productivities of 1.15 and 0.66 grams per liter per hour were achieved from model LRCs and corn stover-derived LRCs, respectively, the latter representing an overall yield of 0.10 grams per gram corn stover-derived lignin. Technoeconomic analysis of the bioprocess and downstream processing predicted a β-ketoadipate minimum selling price of $\$2.01$ per kilogram, which is cost competitive with fossil carbon-derived adipic acid ($\$1.10$ to 1.80 per kilogram). Overall, this work achieved bioproduction metrics with economic relevance for conversion of lignin-derived streams into a performance-advantaged bioproduct.

09 BIOMASS FUELS↗
DOE OSTI2022

Zinc oxide (ZnO) hybrid metasurfaces exhibiting broadly tunable topological properties

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Performance and Commissioning of the BigBite Timing Hodoscope for Nucleon Form Factor Measurements at Jefferson Lab

The BigBite Timing Hodoscope detector is the primary subject of this thesis. The Super BigBite Spectrometer is a Jefferson Lab Hall A Collaboration project that has and will continue to measure nucleon electromagnetic form factors. This spectrometer includes the Timing Hodoscope which provides high resolution particle timing data for scattered electrons in the electron arm of BigBite. The Timing Hodoscope utilizes 90, 25 × 25 × 600 mm3 scintillator bars stacked on top of each other to form a single detector plane, and these bars are connected to 180 photo-multiplier tubes via light guides. Particles collide with the scintillating material creating a shower of optical photons and these particle events in the bars are collected to generate signals that are readout by the data acquisition (DAQ) electronics. NINO ASIC amplifier-discriminator cards output signals from the photo-multiplier tubes into analogue and logic signals, which are sent to analogue-to-digital (ADC) and time-to-digital (TDC) converter data acquisition readout modules. This data is then used for analysis of the detector. The focus of this thesis is the construction, commissioning, calibration, and performance of the BigBite Timing Hodoscope before and during the first of five nucleon electromagnetic form factor experiments at Jefferson Lab Hall A. Before the neutron magnetic form factor, G n M, experiment, cosmic ray data was collected during commissioning to confirm proper operation of the Timing Hodoscope electronics by observing the ADC and TDC data. Commissioning studies for charge normalization, gain matching, and other ADC and TDC detector data variables were performed before moving the detector into Hall A. Following installation in Hall A, several calibration studies were implemented to fine-tune the detector in preparation for use in the experiment. The calibration studies included analysis of timing cuts, TDC alignment, the time-walk effect, time difference offsets, and scintillator velocity corrections. Once the Timing Hodoscope was well-calibrated, data-taking during the experiment commenced and the beam-on-target data was used to characterize the Timing Hodoscope performance during the G n M experiment run-time. The performance analysis included studies observing energy deposit, cluster size, rates, accidentals, pile-up, tracking efficiency, position resolution, and time resolution. After application of physics cuts to ensure a data set comprised of particle tracks corresponding to elastic electrons, which is the main data of interest for measurement of G n M, the Timing Hodoscope is shown on average across all kinematic settings to have a >98% tracking efficiency, a position resolution of 4-6 cm in the non-dispersive plane and 1.5-2 cm in the dispersive plane, and a time resolution of 500-750 ps. These performance results are compared to a GEANT4 based performance simulation of the BigBite Timing Hodoscope for reference, showing to what degree the measured performance values match those taken from the simulation.

Marinaro, Ralph↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
NASA NTRS2024

Optimized bandpasses for the Habitable Worlds Observatory's exoEarth survey

A primary scientific goal of the future Habitable Worlds Observatory will be the direct detection and characterization of Earth-like planets. Estimates of the exoplanet yields for this concept will help guide mission design through detailed trade studies. It is therefore critical that yield estimation codes optimally adapt observations to the mission’s performance parameters to ensure accurate trade studies. To aid in this, we implement wavelength optimization in yield calculations for the first time, allowing the yield code to determine the ideal detection and characterization bandpasses. We use this capability to confirm the observational wavelength assumptions made for the large UV/Optical/IR surveyor, design B (LUVOIR-B) study, namely that the optimum detection wavelength is 500 nm for the majority of targets and the optimum wavelength to detect water is near 1000 nm, given LUVOIR-B’s assumed instrument performance parameters. We show that including the wavelength-dependent albedo of an Earth twin as a prior provides no significant benefit to the yields of exoEarth candidates and caution against tuning observations to modern Earth twins. We also show that coronagraphs whose inner working angles are similar to step functions may benefit from wavelength optimization and demonstrate how wavelength-dependent instrument performance can impact the optimum wavelengths for detection and characterization. The optimization methods we implement automate wavelength selection and remove uncertainties regarding these choices, helping to adapt the observations to the instrument’s performance parameters.

telescopes↗
DOE OSTI2020

Performance of the missing transverse momentum triggers for the ATLAS detector during Run-2 data taking

The factor of four increase in the LHC luminosity, from 0.5 × 10 34 cm -2 s -1 to 2.0 × 10 34 cm -2 s -1 , and the corresponding increase in pile-up collisions during the 2015–2018 data-taking period, presented a challenge for the ATLAS trigger, particularly for those algorithms that select events with missing transverse momentum. The output data rate at fixed threshold typically increases exponentially with the number of pile-up collisions, so the legacy algorithms from previous LHC data-taking periods had to be tuned and new approaches developed to maintain the high trigger efficiency achieved in earlier operations. A study of the trigger performance and comparisons with simulations show that these changes resulted in event selection efficiencies of > 98% for this period, meeting and in some cases exceeding the performance of similar triggers in earlier run periods, while at the same time keeping the necessary bandwidth within acceptable limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Alloying effects on the microstructure and properties of laser additively manufactured tungsten materials

A large body of literature within the additive manufacturing (AM) community has focused on successfully creating stable tungsten (W) microstructures due to significant interest in their application for extreme environments. However, cracking and additional embrittling features at grain boundaries have resulted in poorly performing materials, stymying the application of AM as a manufacturing technique for W. Several alloying strategies, such as ceramic particles and ductile elements, have emerged with the promise to eliminate cracking while simultaneously enhancing stability against recrystallization. Here, in this work, we provide new insights regarding the defects and microstructural features that result from the introduction of ZrC for grain refinement and NiFe as a ductile reinforcement phase – in addition to the resulting thermophysical and mechanical properties. ZrC is shown to promote microstructural stability with increased hardness due to the formation of ZrO 2 dispersoids. Conversely, NiFe forms into micron-scale FCC phase regions within a BCC W matrix, producing enhanced toughness relative to pure AM W. A combination of these effects is realized in the WNiFe + ZrC system and demonstrates that complex chemical environments coupled with the tuning of AM microstructures provides an effective pathway for enabling laser AM W materials with enhanced stability and performance.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Overcoming Pitfalls When Using HDF5 Compression

Compression of large datasets in S-NPP, JPSS and other HDF5 data files may substantially reduce their size, in turn reducing disk space requirements and file download time. However, mismatches between the layout of the files' datasets, the HDF5 instance's cache settings, choice of compression algorithm, and the access pattern of applications using the data can sometimes result in poor performance or exhausting machine resources when running the application. Whether designed in advance or modified in response to encountered problems, applications can be tuned to optimize efficiency of data access, avoid unnecessary repeated decompression, and reduce the amount of memory used. Examples will be given of problems that may be encountered, how to use available tools to diagnose or work around them, changing cache settings to conserve memory, and designing access strategies to avoid both performance and memory issues when creating or modifying applications.

performance↗
DOE OSTI2021

Fracture properties and microstructure formation of hardened alkali-activated slag/fly ash pastes

This study presents a comprehensive experimental investigation on the fracture properties of hardened alkali-activated slag/fly ash (AASF) pastes in relation to the microstructure formation and reaction product composition. The main reaction product in AASF is C-(N-)A-S-H gel along with minor hydrotalcite phase, with the polymerization of C-(N-)A-S-H gel substantially governed by its Ca/Si ratio. Strong positive correlations are identified between the Ca/Si ratios of C-(N-)A-S-H gel and the fracture properties K{sub Ic} (J{sub tip}), whereas, the compressive strength of AASF pastes is primarily determined by its capillary porosity (>0.01 μm). The disagreements between the Ca/Si ratios and corresponding intrinsic mechanical properties of C-(N-)A-S-H gel as proof by contradiction indicate that the fracture properties K{sub Ic} (J{sub tip}) of AASF pastes could be dominated by a cohesion/adhesion-based mechanism. These findings provide promising guidance for fine-tuning the fracture properties of AASF and also advise on the tailoring strategies for high-performance composite such as strain-hardening geopolymer composite.

36 MATERIALS SCIENCE↗