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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A development of grid generation procedure for multicomponent aerodynamic configuration

Two approaches for solving the transonic flow in a multi-block grid were explored. The first approach examines a method involving "zonal decomposition" wherein block boundaries are treated as true boundary surfaces separating interfacing grids. The issues investigated involve techniques for matching solutions at a block boundary. A feasibility study was completed and the results are presented. The second approach involves overlapping grids for differencing across a block boundary near an artificially induced coordinate singularity occurring at a fictitious corner. This approach selects a set of neighboring nodes for the fictitious corner such that the resulting physical cells for a node are topologically the same as any other node on the airfoil surface.

Chen, H. C.↗
NASA NTRS1990

Statistics of associations among IR galaxies

In the course of expanding the search of Kleinmann et. al. (1988) for distant, infrared-luminous objects, the authors noticed (as is often remarked) that a large number of infrared-selected galaxies have close neighbors or show merger characteristics (e.g., tidal tails, distorted disks). Because the sample size is large (567 infrared galaxies and 2182 field galaxies), this sample is ideal for statistically examining the importance of interactions among infrared galaxies. In particular, the authors compare the nearest-neighbor distribution and the two-point correlation function of their sample with that of a control sample of field galaxies.

Gallimore, Jack F.↗
DOE OSTI2023

Evidence for Black Holes in Green Peas from WISE Colors and Variability

We explore the presence of active galactic nuclei (AGNs)/black holes in Green Pea galaxies (GPs), motivated by the presence of high-ionization emission lines such as He ii and [Ne iii] in their optical spectra. In order to identify AGN candidates, we used mid-infrared (MIR) photometric observations from the all-sky Wide-field Infrared Survey Explorer (WISE) mission for a sample of 1004 GPs. Considering only >5σ detections with no contamination from neighboring sources in AllWISE, we select 31 GPs out of 134 as candidate AGNs based on a stringent three-band WISE color diagnostic. Using multi-epoch photometry in W1 and W2 bands based on time-resolved unWISE coadd images, we find two sources exhibiting variability in both the WISE bands among 112 GPs with W1 ≤16 mag and no contamination from neighboring sources in unWISE. These two variable sources were selected as AGNs by the WISE three-band color diagnostic as well. Compared to variable AGN fractions observed among low-mass galaxy samples in previous studies, we find a higher fraction (~1.8%) of MIR variable sources among GPs, which demonstrates the uniqueness and importance of studying these extreme objects. Through this work, we demonstrate that MIR diagnostics are promising tools to select AGNs that may be missed by other selection techniques (including optical emission-line ratios and X-ray emission) in star formation-dominated, low-mass, low-metallicity galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

SNAD transient miner: Finding missed transient events in ZTF DR4 using k-D trees

Here we report the automatic detection of 11 transients (7 possible supernovae and 4 active galactic nuclei candidates) within the Zwicky Transient Facility fourth data release (ZTF DR4), all of them observed in 2018 and absent from public catalogs. Among these, three were not part of the ZTF alert stream. Our transient mining strategy employs 41 physically motivated features extracted from both real light curves and four simulated light curve models (SN Ia, SN II, TDE, SLSN-I). These features are input to a k-D tree algorithm, from which we calculate the 15 nearest neighbors. After pre-processing and selection cuts, our dataset contained approximately a million objects among which we visually inspected the 105 closest neighbors from seven of our brightest, most well-sampled simulations, comprising 89 unique ZTF DR4 sources. Our result illustrates the potential of coherently incorporating domain knowledge and automatic learning algorithms, which is one of the guiding principles directing the SNAD team. It also demonstrates that the ZTF DR is a suitable testing ground for data mining algorithms aiming to prepare for the next generation of astronomical data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

In Situ Characterization of the Effect of Twin-Microstructure Interactions on {$1 0 \bar{1} 2$} Tension and {$1 0\bar {1} 1$} Contraction Twin Nucleation, Growth and Damage in Magnesium

Through in situ electron backscatter diffraction (EBSD) experiments, this paper uncovers dominant damage mechanisms in traditional magnesium alloys exhibiting deformation twinning. The findings emphasize the level of deleterious strain incompatibility induced by twin interaction with other deformation modes and microstructural defects. A double fiber obtained by plane-strain extrusion as a starting texture of AM30 magnesium alloy offered the opportunity to track deformation by EBSD in neighboring grains where some undergo profuse {$1 0\bar {1} 2$} twinning and others do not. For a tensile loading applied along extrusion transverse (ET) direction, those experiencing profuse twinning reveal a major effect of grain boundaries on non-Schmid behavior affecting twin variant selection and growth. Similarly, a neighboring grain, with its $\langle$c$\rangle$-axis oriented nearly perpendicular to tensile loading, showed an abnormally early nucleation of {$1 0\bar {1} 1$} contraction twins (2% strain) while the same {$1 0\bar {1} 1$} twin mode triggering under $\langle$c$\rangle$-axis uniaxial compression have higher value of critical resolved shear stress exceeding the values for pyramidal $\langle$c + a$\rangle$ dislocations. The difference in nucleation behavior of contraction vs. compression {$1 0\bar {1} 1$} twins is attributed to the hydrostatic stresses that promote the required atomic shuffles at the core of twinning disconnections.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
NASA NTRS1988

Imaging spectrometer for high resolution measurements of stratospheric trace constituents in the ultraviolet

A high-resolution spectrometer has been developed for studies of minor constituents in the middle atmosphere at ultraviolet wavelengths. In particular, the instrument is intended for observations of upper stratospheric UV bands. The spectrometer has a slit width of 0.08 A obtained by means of an echelle grating and a cross-disperser grating. The image plane detector is an intensified CCD consisting of a high gain proximity focused image intensifier that is fiber optically coupled to a two-dimensional CCD array. An instantaneous bandwidth of 9.2 A is resolved across 488 pixels at 0.018 A/pixel, permitting simultaneous acquisition of multiple lines of selected OH bands and the neighboring background. The spectrometer and the approach have been successfully demonstrated as a technique for measuring the concentration of OH on two high-altitude balloon flights. This paper reports the instrument design and its achieved performance.

Torr, Marsha R.↗
NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗
DOE OSTI2021

Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst

Electrochemically converting nitrate, a widespread water pollutant, back to valuable ammonia is a green and delocalized route for ammonia synthesis, and can be an appealing and supplementary alternative to the Haber-Bosch process. However, as there are other nitrate reduction pathways present, selectively guiding the reaction pathway towards ammonia is currently challenged by the lack of efficient catalysts. Here we report a selective and active nitrate reduction to ammonia on Fe single atom catalyst, with a maximal ammonia Faradaic efficiency of ~ 75% and a yield rate of up to ~ 20,000 μg h –1 mg cat. –1 (0.46 mmol h –1 cm –2 ). Our Fe single atom catalyst can effectively prevent the N-N coupling step required for N 2 due to the lack of neighboring metal sites, promoting ammonia product selectivity. Density functional theory calculations reveal the reaction mechanisms and the potential limiting steps for nitrate reduction on atomically dispersed Fe sites.

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

Texture Formation in Polycrystalline Thin Films of All‐Inorganic Lead Halide Perovskite

Abstract Controlling grain orientations within polycrystalline all‐inorganic halide perovskite solar cells can help increase conversion efficiencies toward their thermodynamic limits; however, the forces governing texture formation are ambiguous. Using synchrotron X‐ray diffraction, mesostructure formation within polycrystalline CsPbI 2.85 Br 0.15 powders as they cool from a high‐temperature cubic perovskite (α‐phase) is reported. Tetragonal distortions (β‐phase) trigger preferential crystallographic alignment within polycrystalline ensembles, a feature that is suggested here to be coordinated across multiple neighboring grains via interfacial forces that select for certain lattice distortions over others. External anisotropy is then imposed on polycrystalline thin films of orthorhombic (γ‐phase) CsPbI 3‐ x Br x perovskite via substrate clamping, revealing two fundamental uniaxial texture formations; i) I‐rich films possess orthorhombic‐like texture (<100> out‐of‐plane; <010> and <001> in‐plane), while ii) Br‐rich films form tetragonal‐like texture (<110> out‐of‐plane; <110> and <001> in‐plane). In contrast to relatively uninfluential factors like the choice of substrate, film thickness, and annealing temperature, Br incorporation modifies the γ‐CsPbI 3− x Br x crystal structure by reducing the orthorhombic lattice distortion (making it more tetragonal‐like) and governs the formation of the different, energetically favored textures within polycrystalline thin films.

Steele, Julian A.↗
NASA NTRS2007

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Scattered data interpolation is a problem of interest in numerous areas such as electronic imaging, smooth surface modeling, and computational geometry. Our motivation arises from applications in geology and mining, which often involve large scattered data sets and a demand for high accuracy. The method of choice is ordinary kriging. This is because it is a best unbiased estimator. Unfortunately, this interpolant is computationally very expensive to compute exactly. For n scattered data points, computing the value of a single interpolant involves solving a dense linear system of size roughly n x n. This is infeasible for large n. In practice, kriging is solved approximately by local approaches that are based on considering only a relatively small'number of points that lie close to the query point. There are many problems with this local approach, however. The first is that determining the proper neighborhood size is tricky, and is usually solved by ad hoc methods such as selecting a fixed number of nearest neighbors or all the points lying within a fixed radius. Such fixed neighborhood sizes may not work well for all query points, depending on local density of the point distribution. Local methods also suffer from the problem that the resulting interpolant is not continuous. Meyer showed that while kriging produces smooth continues surfaces, it has zero order continuity along its borders. Thus, at interface boundaries where the neighborhood changes, the interpolant behaves discontinuously. Therefore, it is important to consider and solve the global system for each interpolant. However, solving such large dense systems for each query point is impractical. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. The problems arise from the fact that the covariance functions that are used in kriging have global support. Our implementations combine, utilize, and enhance a number of different approaches that have been introduced in literature for solving large linear systems for interpolation of scattered data points. For very large systems, exact methods such as Gaussian elimination are impractical since they require 0(n(exp 3)) time and 0(n(exp 2)) storage. As Billings et al. suggested, we use an iterative approach. In particular, we use the SYMMLQ method, for solving the large but sparse ordinary kriging systems that result from tapering. The main technical issue that need to be overcome in our algorithmic solution is that the points' covariance matrix for kriging should be symmetric positive definite. The goal of tapering is to obtain a sparse approximate representation of the covariance matrix while maintaining its positive definiteness. Furrer et al. used tapering to obtain a sparse linear system of the form Ax = b, where A is the tapered symmetric positive definite covariance matrix. Thus, Cholesky factorization could be used to solve their linear systems. They implemented an efficient sparse Cholesky decomposition method. They also showed if these tapers are used for a limited class of covariance models, the solution of the system converges to the solution of the original system. Matrix A in the ordinary kriging system, while symmetric, is not positive definite. Thus, their approach is not applicable to the ordinary kriging system. Therefore, we use tapering only to obtain a sparse linear system. Then, we use SYMMLQ to solve the ordinary kriging system. We show that solving large kriging systems becomes practical via tapering and iterative methods, and results in lower estimation errors compared to traditional local approaches, and significant memory savings compared to the original global system. We also developed a more efficient variant of the sparse SYMMLQ method for large ordinary kriging systems. This approach adaptively finds the correct local neighborhood for each query point in the interpolation process.

Memarsadeghi, Nargess↗
DOE OSTI2022

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗
DOE OSTI2023

Dihydroxyterephthalate—A Trojan Horse PET Counit for Facile Chemical Recycling

Abstract Here, low‐energy poly(ethylene terephthalate) (PET) chemical recycling in water: PET copolymers with diethyl 2,5‐dihydroxyterephthalate (DHTE) undergo selective hydrolysis at DHTE sites, autocatalyzed by neighboring group participation, is demonstrated. Liberated oligomeric subchains further hydrolyze until only small molecules remain. Poly(ethylene terephthalate‐ stat ‐2,5‐dihydroxyterephthalate) copolymers were synthesized via melt polycondensation and then hydrolyzed in 150–200 °C water with 0–1 wt% ZnCl 2 , or alternatively in simulated sea water. Degradation progress follows pseudo‐first order kinetics. With increasing DHTE loading, the rate constant increases monotonically while the thermal activation barrier decreases. The depolymerization products are ethylene glycol, terephthalic acid, 2,5‐dihydroxyterephthalic acid, and bis(2‐hydroxyethyl) terephthalate dimer, which could be used to regenerate virgin polymer. Composition‐optimized copolymers show a decrease of nearly 50% in the Arrhenius activation energy, suggesting a 6‐order reduction in depolymerization time under ambient conditions compared to that of PET homopolymer. This study provides new insight to the design of polymers for end‐of‐life while maintaining key properties like service temperature and mechanical properties. Moreover, this chemical recycling procedure is more environmentally friendly compared to traditional approaches since water is the only needed material, which is green, sustainable, and cheap.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Wind-Driven Erosion and Exposure Potential at Mars 2020 Rover Candidate-Landing Sites

Aeolian processes have likely been the predominant geomorphic agent for most of Mars’ history and have the potential to produce relatively young exposure ages for geologic units. Thus, identifying local evidence for aeolian erosion is highly relevant to the selection of landing sites for future missions, such as the Mars 2020 Rover mission that aims to explore astrobiologically relevant ancient environments. Here we investigate wind-driven activity at eight Mars 2020 candidate-landing sites to constrain erosion potential at these locations. To demonstrate our methods, we found that contemporary dune-derived abrasion rates were in agreement with rover-derived exhumation rates at Gale crater and could be employed elsewhere. The Holden crater candidate site was interpreted to have low contemporary erosion rates, based on the presence of a thick sand coverage of static ripples. Active ripples at the Eberswalde and southwest Melas sites may account for local erosion and the dearth of small craters. Moderate-flux regional dunes near Mawrth Vallis were deemed unrepresentative of the candidate site, which is interpreted to currently be experiencing low levels of erosion. The Nili Fossae site displayed the most unambiguous evidence for local sand transport and erosion, likely yielding relatively young exposure ages. The down selected Jezero crater and northeast Syrtis sites had high-flux neighboring dunes and exhibited substantial evidence for sediment pathways across their ellipses. Both sites had relatively high estimated abrasion rates, which would yield young exposure ages. The down selected Columbia Hills site lacked evidence for sand movement, and contemporary local erosion rates are estimated to be relatively low.

Matthew Chojnacki↗
DOE OSTI2023

Nanowire implosion under laser amplified spontaneous emission pedestal irradiation

Nanowire array targets exhibit high optical absorption when interacting with short, intense laser pulses. This leads to an increased yield in the production of accelerated particles for a variety of applications. However, these interactions are sensitive to the laser prepulse and could be significantly affected. Here, we show that an array of aligned nanowires is imploded when irradiated by an Amplified Spontaneous Emission pedestal of a 1 PW laser with an intensity on the order of 10 11 W cm –2 . Using radiation hydrodynamics simulations, we demonstrate that the electron density profile is radially compressed at the tip by the rocket-like propulsion of the ablated plasma. The mass density compression increases up to 2.9x when a more dense nanowire array is used. This is due to the ablation pressure from the neighboring nanowires. These findings offer valuable information for selecting an appropriate target design for experiments aimed at enhancing production of accelerated particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Ultrafast signatures of spin and orbital order in antiferromagnetic α-Sr2CrO4

Abstract The antiferromagnetic Mott insulator α -Sr 2 CrO 4 possesses multiple spin and orbital ordered phases, but their unique interplay is still relatively unexplored. Here, we used femtosecond optical spectroscopy to study ultrafast spin and orbital ordering dynamics in α -Sr 2 CrO 4 through their non-equilibrium response to photoexcitation. By varying the pump photon energy, we selectively drove inter-site spin hopping between neighboring Cr t 2 g orbitals and charge transfer-type transitions between oxygen 2 p and Cr e g orbitals. The resulting transient reflectivity dynamics revealed temperature-dependent anomalies across the Néel temperature for spin ordering as well as the transition temperatures linked to different types of orbital order. Our results reveal distinct relaxation timescales for spin and orbital orders in α -Sr 2 CrO 4 and provide experimental evidence for the phase transition at T O , possibly related to antiferro-type orbital ordering.

36 MATERIALS SCIENCE↗
NASA NTRS1976

A LANDSAT digital image rectification system

DIRS is a digital image rectification system for the geometric correction of LANDSAT multispectral scanner digital image data. DIRS removes spatial distortions from the data and brings it into conformance with the Universal Transverse Mercator (UTM) map projection. Scene data in the form of landmarks are used to drive the geometric correction algorithms. Two dimensional least squares polynominal and spacecraft attitude modeling techniques for geometric mapping are provided. Entire scenes or selected quadrilaterals may be rectified. Resampling through nearest neighbor or cubic convolution at user designated intervals is available. The output products are in the form of digital tape in band interleaved, single band or CCT format in a rotated UTM projection. The system was designed and implemented on large scale IBM 360 computers.

Vanwie, P.↗