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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Rapid Atomic Ordering Transformation toward Intermetallic Nanoparticles

Chemically ordered intermetallic nanoparticles are promising candidates for energy-related applications such as electrocatalysis. However, the synthesis of intermetallics generally requires long annealing (several hours) to achieve the ordered structure, which causes nanoparticles agglomeration and diminished performance, particularly for catalysis. Herein, we demonstrate a new rapid Joule heating approach that can synthesize highly ordered and well-dispersed intermetallic nanoparticles. As a proof-of-concept, we synthesized fully ordered Pd 3 Pb intermetallic nanoparticles that feature small size distribution (~6 nm). Computational analysis of the L1 2 Pd 3 Pb material suggests that this rapid atomic ordering transformation can be attributed to a vacancy-mediated diffusion mechanism. Moreover, the nanoparticles demonstrate excellent electrocatalytic activity and exceptional stability for the oxygen reduction reaction (ORR), retaining >95% of the current density over 10 h of chronoamperometry test with negligible structural and compositional changes. Furthermore, this study demonstrates a new strategy of providing a new direction for intermetallic synthesis and catalyst discovery.

25 ENERGY STORAGE↗
DOE OSTI2023

More Than 30 000-fold Field Enhancement of Terahertz Nanoresonators Enabled by Rapid Inverse Design

The rapid development of 6G communications using terahertz (THz) electromagnetic waves has created a demand for highly sensitive THz nanoresonators capable of detecting these waves. Among the potential candidates, THz nanogap loop arrays show promising characteristics but require significant computational resources for accurate simulation. This requirement arises because their unit cells are 10 times smaller than millimeter wavelengths, with nanogap regions that are 1 000 000 times smaller. To address this challenge, we propose a rapid inverse design method using physics-informed machine learning, employing double deep Q-learning with an analytical model of the THz nanogap loop array. In ~39 h on a middle-level personal computer, our approach identifies the optimal structure through 200 000 iterations, achieving an experimental electric field enhancement of 32 000 at 0.2 THz, 300% stronger than prior results. In conclusion, our analytical model-based approach significantly reduces the amount of computational resources required, offering a practical alternative to numerical simulation-based inverse design for THz nanodevices.

21 terahertz time-domain spectroscopy↗
DOE OSTI2022

Novel Application of Machine Learning Techniques for Rapid Source Apportionment of Aerosol Mass Spectrometer Datasets

In this work, we apply machine learning approaches sparse multinomial logistic regression to classify aerosol mass spectrometer (AMS) unit mass resolution (UMR) data followed by an ensemble regression technique for source apportionment of organic aerosols (OA). The classifier was trained on 60 well characterized laboratory and positive matrix factorization (PMF) deconvolved reference spectra to identify eight OA types. These include four laboratory-derived secondary organic aerosol (SOA) spectra, which include isoprene photooxidation SOA, isoprene epoxydiols (IEPOX) SOA, a monoterpene SOA type that includes a-pinene and ß-pinene SOA, and aromatic SOA from oxidation of naphthalene and m-xylene precursors, as well as PMF deconvolved spectra for three primary organic aerosol (POA) types, namely, hydrocarbon-like organic aerosol (HOA), biomass burning organic aerosol (BBOA), and cooking OA (COA), and a more oxidized oxygenated OA type (MO-OOA). A 5-fold cross-validation strategy, repeated 10 times, was used to assess the classifier’s performance. The classifier had high classification accuracy for COA, aromatic SOA, and isoprene SOA spectra but incorrectly classified ~9% by number of MO-OOA spectra as BBOA, 12% of BBOA spectra as HOA (and vice versa), and 18% of IEPOX-SOA spectra as aromatic SOA. Next, an ensemble regression model was trained on an artificially generated dataset consisting of mixtures of different OA types to assess its ability to predict fractional mass abundances from classification probabilities of various OA species obtained from the multinomial logistic regression classifier trained on the reference spectra. Ultimately, the proposed approach was applied for source apportionment of aircraft-based AMS measurements of OA UMR spectra during the HI-SCALE field campaign. On two representative days (May 6th and 18th, 2016), the algorithm determined that ~50-60% of OA by mass was MO-OOA, which represented a highly aged organic aerosol mixture from different sources. On both days, BBOA was determined to contribute less than 10% to OA by mass. However, on May 18th, the aromatic SOA fraction was higher compared to that on May 6th. The proposed approach is capable of rapidly analyzing AMS data in real time, making it suitable for applications where rapid source apportionment of AMS OA spectra is desirable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Rapid Electrochemical Methane Functionalization Involves Pd–Pd Bonded Intermediates

High-valent Pd complexes are potent agents for the oxidative functionalization of inert C-H bonds, and it was previously shown that rapid electrocatalytic methane monofunctionalization could be achieved by electro-oxidation of Pd II to a critical dinuclear Pd III intermediate in concentrated or fuming sulfuric acid. However, the structure of this highly reactive, unisolable intermediate, as well as the structural basis for its mechanism of electrochemical formation, remained elusive. Herein, we use X-ray absorption and Raman spectroscopies to assemble a structural model of the potent methane-activating intermediate as a Pd III dimer with a Pd-Pd bond and a 5-fold O atom coordination by H x SO 4 (x-2) ligands at each Pd center. We further use EPR spectroscopy to identify a mixed-valent M-M bonded Pd 2 II,III species as a key intermediate during the Pd II -to-Pd III 2 oxidation. Combining EPR and electrochemical data, we quantify the free energy of Pd dimerization as <-4.5 kcal/mol for Pd 2 II,III and <-9.1 kcal/mol for Pd III 2 . The structural and thermochemical data suggest that the aggregate effect of metal-metal and axial metal-ligand bond formation drives the critical Pd dimerization reaction in between electrochemical oxidation steps. This work establishes a structural basis for the facile electrochemical oxidation of Pd II to a M-M bonded Pd III dimer and provides a foundation for understanding its rapid methane functionalization reactivity.

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

Comparing Liquid Vortex Capture & the Rapid Droplet Sampling Interface for Single Cell Mass Spectrometry

High-throughput single-cell mass spectrometry is a rapidly evolving field that requires innovative sampling and ionization techniques to balance speed, sensitivity, and reliability for metabolomic and lipidomic analyses. This study provides a comparative analysis of two cutting-edge ionization platforms for single-cell analysis: Liquid Vortex Capture (LVC) and Rapid Droplet Sampling Interface (RDSI). The performance was benchmarked by testing pharmaceuticals, EquiSPLASH, and single-cell experiments. RDSI demonstrated up to 100-fold improvements in sensitivity for drugs and lipids such as propranolol, amiodarone, atorvastatin, and phosphocholines in water and phosphate-buffered solutions. This was attributed to its low-flow rate operation (3 μL/min) and reduced dilution. Conversely, LVC excelled in handling higher liquid volumes with greater reproducibility due to its higher solvent flow rate (200 μL/min), enabling increased dilution, solubility, and cleaning. Single-cell uptake of atorvastatin incubated for 10 min, or amiodarone incubated for 24 h in HepG2 cells, similarly revealed up to 85-fold enhancement in sensitivity by RDSI for drugs and lipids. These findings highlight the potential of RDSI for enhancing sensitivity in single-cell drug monitoring and lipidomics.

Cahill, John [ORNL] (ORCID:0000000298664010)↗
DOE OSTI2021

Sea Level-Driven Marsh Migration Results in Rapid Net Loss of Carbon

Sea level rise alters coastal carbon cycling by driving the rapid migration of coastal ecosystems, salinization of freshwater systems, and replacement of terrestrial forests with tidal wetlands. Wetland soils accumulate carbon (C) at faster rates than terrestrial soils, implying that sea level rise may lead to enhanced carbon accumulation. Here, we show that carbon stored in tree biomass greatly exceeds carbon stored in adjacent marsh soils so that marsh migration reduces total carbon stocks by ~50% in less than 100 years. Continued marsh soil carbon accumulation may eventually offset forest carbon loss, but we estimate that the time for replacement is similar to estimates of marsh survival (i.e., centuries), which suggests that forest C may never be replaced. These findings reveal a critical C source not included in coastal C budgets driven by migrating ecosystems and rapidly shifting allocations between carbon stored in soils and biomass.

58 GEOSCIENCES↗
DOE OSTI2024

Rapid-charging aluminium-sulfur batteries operated at 85 °C with a quaternary molten salt electrolyte

Molten salt aluminum-sulfur batteries are based exclusively on resourcefully sustainable materials, and are promising for large-scale energy storage owed to their high-rate capability and moderate energy density; but the operating temperature is still high, prohibiting their applications. Here we report a rapid-charging aluminium-sulfur battery operated at a sub-water-boiling temperature of 85°C with a tamed quaternary molten salt electrolyte. The quaternary alkali chloroaluminate melt – possessing abundant electrochemically active high-order Al-Cl clusters and yet exhibiting a low melting point – facilitates fast Al 3+ desolvation. A nitrogen-functionalized porous carbon further mediates the sulfur reaction, enabling the battery with rapid-charging capability and excellent cycling stability with 85.4% capacity retention over 1400 cycles at a charging rate of 1 C. Importantly, we demonstrate that the asymmetric sulfur reaction mechanism that involves formation of polysulfide intermediates, as revealed by operando X-ray absorption spectroscopy, accounts for the high reaction kinetics at such temperature wherein the thermal management can be greatly simplified by using water as the heating media.

25 ENERGY STORAGE↗
DOE OSTI2023

Rapid loss of complex polymers and pyrogenic carbon in subsoils under whole-soil warming

Subsoils contain more than half of soil organic carbon (SOC) and are expected to experience rapid warming in the coming decades. Yet our understanding of the stability of this vast carbon pool under global warming is uncertain. In particular, the fate of complex molecular structures (polymers) remains debated. Here we show that 4.5 years of whole-soil warming (+4 °C) resulted in less polymeric SOC (sum of specific polymers contributing to SOC) in the warmed subsoil (20–90 cm) relative to control, with no detectable change in topsoil. Warming stimulated the subsoil loss of lignin phenols (–17 ± 0%) derived from woody plant biomass, hydrolysable lipids cutin and suberin, derived from leaf and woody plant biomass (–28 ± 3%), and pyrogenic carbon (–37 ± 8%) produced during incomplete combustion. Given that these compounds have been proposed for long-term carbon sequestration, it is notable that they were rapidly lost in warmed soils. We conclude that complex polymeric carbon in subsoil is vulnerable to decomposition and propose that molecular structure alone may not protect compounds from degradation under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Rapid advances enabling high-performance inverted perovskite solar cells

Perovskite solar cells (PSCs) that have a positive–intrinsic–negative (p–i–n, or often referred to as inverted) structure are becoming increasingly attractive for commercialization owing to their rapid increase in power conversion efficiency, easily scalable fabrication, reliable operation and compatibility with various perovskite-based tandem device configurations. In this report we review key material and device considerations for making highly efficient and stable p–i–n PSCs. First, we summarize key advances in charge transport materials, which were critical to the rapid power conversion efficiency progress. Second, we discuss promising perovskite compositions and fabrication methods. We highlight various additive engineering approaches to improve the perovskite layer as well as interface engineering strategies that target either the buried or top perovskite surface layer. Third, we review progress in tandem devices, focusing on optimization of the interconnection layer. Next, we summarize the status and strategies for improving p–i–n PSC stability, especially considering the challenges of outdoor applications. We also provide prospects for future research directions and challenges.

14 SOLAR ENERGY↗
DOE OSTI2024

Rapid spin changes around a magnetar fast radio burst

Magnetars are neutron stars with extremely high magnetic fields (≳10 14 gauss) that exhibit various X-ray phenomena such as sporadic subsecond bursts, long-term persistent flux enhancements and variable rotation-period derivative. In 2020, a fast radio burst (FRB), akin to cosmological millisecond-duration radio bursts, was detected from the Galactic magnetar SGR 1935+2154, confirming the long-suspected association between some FRBs and magnetars. However, the mechanism for FRB generation in magnetars remains unclear. Here we report the X-ray observation of two glitches in SGR 1935+2154 within a time interval of approximately nine hours, bracketing an FRB that occurred on 14 October 2022. Each glitch involved a significant increase in the magnetar’s spin frequency, being among the largest abrupt changes in neutron-star rotation observed so far. Between the glitches, the magnetar exhibited a rapid spin-down phase, accompanied by an increase and subsequent decline in its persistent X-ray emission and burst rate. Here we postulate that a strong, ephemeral, magnetospheric wind provides the torque that rapidly slows the star’s rotation. The trigger for the first glitch couples the star’s crust to its magnetosphere, enhances the various X-ray signals and spawns the wind that alters magnetospheric conditions that might produce the FRB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

High-temperature high-pressure microfluidic system for rapid screening of supercritical CO 2 foaming agents

CO 2 foam helps to increase the viscosity of CO 2 flood fluid and thus improve the process efficiency of the anthropogenic greenhouse gas’s subsurface utilization and sequestration. Successful CO 2 foam formation mandates the development of high-performance chemicals at close to reservoir conditions, which in turn requires extensive laboratory tests and evaluations. This work demonstrates the utilization of a microfluidic reservoir analogue for rapid evaluation and screening of commercial surfactants (i.e., Cocamidopropyl Hydroxysultaine, Lauramidopropyl Betaine, Tallow Amine Ethoxylate, N,N,N' Trimethyl-N'-Tallow-1,3-diaminopropane, and Sodium Alpha Olefin Sulfonate) based on their performance to produce supercritical CO 2 foam at high salinity, temperature, and pressure conditions. The microfluidic analogue was designed to represent the pore sizes of the geologic reservoir rock and to operate at 100 °C and 13.8 MPa. Values of the pressure drop across the microfluidic analogue during flow of the CO 2 foam through its pore network was used to evaluate the strength of the generated foam and utilized only milliliters of liquid. The transparent microfluidic pore network allows in-situ quantitative visualization of CO 2 foam to calculate its half-life under static conditions while observing if there is any damage to the pore network due to precipitation and blockage. The microfluidic mobility reduction results agree with those of foam loop rheometer measurements, however, the microfluidic approach provided more accurate foam stability data to differentiate the foaming agent as compared with conventional balk testing. The results obtained here supports the utility of microfluidic systems for rapid screening of chemicals for carbon sequestration or enhanced oil recovery operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Martensite decomposition during rapid heating of Ti-6Al-4V studied via in situ synchrotron X-ray diffraction

Martensite, α‘, commonly appears in Ti-6Al-4V upon rapid cooling from above the β-transus temperature. It is known that α‘ decomposes into α and β at high temperatures but well below the β-transus temperature. Here, we study the decomposition of martensitic Ti-6Al-4V under rapid laser heating, employing in situ synchrotron X-ray diffraction. A comparison is made with post-annealed Ti-6Al-4V under heating to elucidate changes without martensite decomposition. The fast acquisition of X-ray diffraction data at 250 Hz temporally resolves the decomposition process initiated by annihilating dislocations in α‘. The recovery process is accompanied by structural changes in martensite, followed by the phase transformation to β. Thermal profiles estimated from the lattice parameter data reveal the influence of heating rates and dislocation densities on the decomposition process. Throughout the analysis of the diffraction profiles with respect to estimated temperature, we propose a straightforward method for approximating the initiation temperature of martensite decomposition.

42 ENGINEERING↗
DOE OSTI2023

Exploration of LIBS as a novel and rapid elemental mapping technique of nuclear fuels in the form of surrogate TRISO particles

Laser-induced breakdown spectroscopy (LIBS) was employed to characterize coatings on surrogate fuel particles. Tri-structural isotropic (TRISO) particles are a proposed nuclear fuel alternative for high temperature reactors. These particles are constructed of a ZrO 2 kernel (as a surrogate to uranium), surrounded by an inner pyrolytic carbon layer and are surrounded by an outer carbide layer (ZrC, presented here) to act as a barrier to fission products generated during nuclear reactions. These particles are embedded within a graphite compact and housed within the reactor core. Simply put, due to their robust nature, performing elemental analysis of these particles poses a challenge. Presented here, LIBS is explored as a method for characterizing elemental constituents of these particles, with the focus being on rapid elemental mapping and depth profiling. Different from traditional elemental analysis techniques (e.g., inductively coupled plasma – based methods), LIBS is advantageous because it can directly analyze the sample surface and can detect light elements such as C and O, making it a viable technique for the analysis of small, multilayered particles as spatial elemental information is warranted in the production of these particles. In the work presented here, LIBS was successfully used for discerning small layers (30–50 μm), detecting the location of carbon and oxygen layers, providing fast 2-D mapping (<5 min per particle) and rapid depth profiling (10 s per particle).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

TOFHunter—unlocking rapid untargeted screening of inductively coupled plasma–time-of-flight–mass spectrometry data

This study provides an overview of a newly developed open source program written in Python, TOFHunter, which permits the rapid and untargeted screening of inductively coupled plasma (ICP)-time-of-flight (TOF)-mass spectrometry (MS) datasets. ICP-TOF-MS is an analytical tool capable of providing quasi simultaneous detection of all nuclides from Li to Pu. This capability has triggered an increase in studies investigating single-particle analysis in which the TOF-MS provides correlated elemental/isotopic signatures on a particle basis in time. Similarly, laser ablation mapping has seen rapid growth owing to ICP-TOF-MS's capacity to handle fast washout times (<10 ms) while providing a broad nuclide coverage. The caveat to this broad mass coverage and high time resolution comes in the form of large, overwhelming datasets. With datasets typically on the scale of gigabytes, it is easy for a user to only focus on very targeted analytes; however, this focus diminishes the opportunity offered by the TOF-MS detector. TOFHunter applies chemometric methods, principal component analysis (PCA), and interesting features finder (IFF) on ICP-TOF-MS data, allowing for investigation of correlations, major and minor variance sources, and sample screening. The unique spectra identified by the (IFF) are used to generate a list of mass peaks, which are then matched with both nuclides and potential interferences before being exported for the user to investigate. Several case studies are discussed herein, demonstrating TOFHunter's ability to screen aqueous injections, single-particle/single-cell analysis, and probe laser ablation mapping files for unique regions of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions

Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Dynamics of rapidly spinning blob-filaments: Fluid theory with a parallel kinetic extension

Blob-filaments (or simply “blobs”) are coherent structures formed by turbulence and sustained by nonlinear processes in the edge and scrape-off layer (SOL) of tokamaks and other magnetically confined plasmas. The dynamics of these blob-filaments, in particular, their radial motion, can influence the scrape-off layer width and plasma interactions with both the divertor target and with the main chamber walls. Motivated by recent results from the XGC1 gyrokinetic simulation code reported on elsewhere [J. Cheng et al., Nucl. Fusion 63, 086015 (2023)], a theory of rapidly spinning blob-filaments has been developed for this work. The theory treats blob-filaments in the closed flux surface region or the region that is disconnected from sheaths in the SOL. It extends previous work by treating blob spin, arising from partially or fully adiabatic electrons, as the leading-order effect and retaining inertial (ion charge polarization) physics in next order. Spin helps to maintain blob coherency and affects the blob's propagation speed. Dipole charge polarization, treated perturbatively, gives rise to blob-filaments with relatively slow radial velocity, comparable to that observed in the simulations. The theory also treats the interaction of rapidly spinning blob-filaments with a zonal flow layer. It is shown analytically that the flow layer can act like a transport barrier for these structures. Finally, parallel electron kinetic effects are incorporated into the theory. Various asymptotic parameter regimes are discussed, and asymptotic expressions for the radial and poloidal motion of the blob-filaments are obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Rapid subsurface analysis of frequency-domain thermoreflectance images with K-means clustering

K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μm of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μm length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.

36 MATERIALS SCIENCE↗