Search NASA⌕ Search

SEARCH · Search NASA

Results for “Conditional Point Sampling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing

We present and characterize the galaxy-galaxy lensing signal measured using the first three years of data from the Dark Energy Survey (DES Y3) covering 4132 deg 2 . These galaxy-galaxy measurements are used in the DES Y3 3 × 2 pt cosmological analysis, which combines weak lensing and galaxy clustering information. We use two lens samples: a magnitude-limited sample and the redmagic sample, which span the redshift range ∼ 0.2 – 1 with 10.7 and 2.6 M galaxies, respectively. For the source catalog, we use the metacalibration shape sample, consisting of ≃ 100 M galaxies separated into four tomographic bins. Our galaxy-galaxy lensing estimator is the mean tangential shear, for which we obtain a total SNR of ∼ 148 for maglim ( ∼ 120 for redmagic), and ∼ 67 ( ∼ 55 ) after applying the scale cuts of 6 Mpc / h . Thus we reach percent-level statistical precision, which requires that our modeling and systematic-error control be of comparable accuracy. The tangential shear model used in the 3 × 2 pt cosmological analysis includes lens magnification, a five-parameter intrinsic alignment model, marginalization over a point mass to remove information from small scales and a linear galaxy bias model validated with higher-order terms. We explore the impact of these choices on the tangential shear observable and study the significance of effects not included in our model, such as reduced shear, source magnification, and source clustering. We also test the robustness of our measurements to various observational and systematics effects, such as the impact of observing conditions, lens-source clustering, random-point subtraction, scale-dependent metacalibration responses, point spread function residuals, and B modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sub-pixel high-resolution imaging of high-energy x-rays inspired by sub-wavelength optical imaging

We have developed and demonstrated an image super-resolution method—XR-UNLOC: X-Ray UNsupervised particle LOCalization—for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μ m of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of “nearly-dark” instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community (“droplet analysis”) showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Cesium Removal and Hydraulic Performance Comparisons of CST Ion Exchange Media Batches in Support of the Tank Closure Cesium Removal Project - 20522

Three batches of Crystalline Silicotitanate (CST) ion exchange media have been evaluated for cesium removal efficiency from a Savannah River Site (SRS) High Level Waste (HLW) supernate simulant in support of the Tank Closure Cesium Removal (TCCR) Project, which involves at-tank column waste treatment. Results will be utilized to select the CST media batch to be added to the next TCCR unit columns. Two of the CST media samples were recent production batches and the third was an archived batch studied extensively at SRS nearly two decades ago. The archived CST batch had a significantly smaller average particle diameter than more recent batches. Small-scale (∼23 mL), side-by-side column tests were conducted at 35 deg. C with each of the CST batches using the same simulant at flow rates near 1.2 mL/min (3.0-3.4 CST bed volumes/hr). The cesium ion exchange column performance results were lower than expected for all three CST batches, but the data indicated that 30% more simulant volume and 40% more equivalent CST bed volumes of solution can be processed with the older CST batch prior to reaching the 50% cesium breakthrough point than can be processed with the newer CST batches. Hydraulic evaluations of the CST columns were also conducted in simulant at 24 deg. C to determine the impact of the different particle size distributions and associated bed porosities on frictional pressure drop under dynamic flow conditions. Higher differential pressure drops were observed with the archived CST batch relative to recent production batches, due to the smaller particle size distribution and the packing characteristics of the archived batch. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Dietary uptake of geosmin in rainbow trout ( Oncorhynchus mykiss )

Geosmin is a primary source of muddy/earthy ‘off-flavors’ in farmed fish, which may render their organoleptic quality unacceptable to consumers. Model systems of geosmin uptake typically comprise exposure to waterborne geosmin that is absorbed via the gills. The present research demonstrates dietary exposure as an alternative route of geosmin uptake in Rainbow Trout (Oncorhynchus mykiss) fillets. Trout (average initial weight of 355 g) were stocked in quadruplicate compartmentalized raceways (N = 4 compartments per treatment, n = 50 fish per compartment) supplied with first-use, flow-through water (4.5 complete turnovers per hour). Fish were fed diets containing 0 (control dose), 0.005 (low dose), 0.05 (medium dose), or 0.5 (high dose) mg geosmin/kg feed at 1% body weight/day for four weeks. Fillets (12 fillets/diet/week plus 12 pre-trial fillet samples) and weekly feed and water samples were analyzed via GC–MS to determine geosmin concentrations. Feeding behavior was documented daily according to a four-point scale. ANOVA with post-hoc Tukey tests and polynomial contrast, regression, correlation, and chi-squared statistical analyses were applied to data (α = 0.05 significance level). Palatability of feed did not hinder consumption of the geosmin-spiked feeds: although fish responded positively to all feeds, the most aggressive feeding behavior was observed among those fed medium and high dose feed. Geosmin was effectively imparted into fillets after one week, and no significant temporal effect was found after four weeks. Mean geosmin concentrations significantly increased in fillets from low (mean of 26 ng/kg geosmin) to medium (202 ng/kg) to high (441 ng/kg) dose feed groups during the trial. Polynomial contrasts and regression modeling validated this significant positive effect of dose on geosmin uptake, with an estimated 166 ng/kg rise in fillet-geosmin for every log 10 increase in feed concentration. Waterborne geosmin levels immediately post-feeding were conditionally independent of concentrations in feed and fillets, therefore dietary uptake was affirmed as the predominant mechanism of absorption in the present experimental system. Finally, based on these findings, geosmin-spiked feeds may be used to induce predictable, repeatable levels of this off-flavor compound in fillets and serve as a model system for further investigation of sensory quality and off-flavor mitigation strategies for farm-raised fish.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An experimental investigation on the characteristics of heat pipes with annular type composite wick structure

Here, an experimental investigation has been conducted on the hydraulic characteristics of annular type wick structures for heat pipes. An experimental facility which can measure porosity, permeability, and effective pore radius of the wick structures in a vacuum condition is established. Nine different types of multi-layered (6 layers in total) composite screen meshes are characterized. Based on the measurement results, a wick structure composed of one layer of 100×100 mesh, three layers of 400×400 mesh, and two layers of 60×60 mesh is determined to have the highest permeability to effective pore radius ratio $(K/r_{eff})$ and was selected as a targeted sample. The wick-to-wall gap effect on the hydraulic characteristics of annular type wick structure is also investigated by measuring the permeability and effective pore radius of the sample wick structure with varying gap widths. The result shows that the permeability increases as the gap increases from 0 mm to 1.2 mm. After a peak at 1.2 mm, the permeability decreases as the gap increases and converges to the value of the case measured without a wall structure. The effective pore radius becomes smaller as the gap increases, making a peak at a gap distance of 1.2 mm. This result implies that there is an optimal point in gap distance which is determined to be 1.2 mm for the selected composite mesh structure. A capillary limitation correlation with a multiplying factor which explains the enhanced performance of the wick due to the gap is suggested. An annular wick type heat pipe is constructed and tested. The capillary limitation of the heat pipe showed good agreement with the suggested correlation.

42 ENGINEERING↗
DOE OSTI2022

The miniJPAS survey: A search for extreme emission-line galaxies

Context. Galaxies with extreme emission lines (EELGs) may play a key role in the evolution of the Universe, as well as in our understanding of the star formation process itself. For this reason an accurate determination of their spatial density and fundamental properties in different epochs of the Universe will constitute a unique perspective towards a comprehensive picture of the interplay between star formation and mass assembly in galaxies. In addition to this, EELGs are also interesting in order to explain the reionization of the Universe, since their interstellar medium (ISM) could be leaking ionizing photons, and thus they could be low z, analogous of extreme galaxies at high z . Aims. This paper presents a method to obtain a census of EELGs over a large area of the sky by detecting galaxies with rest-frame equivalent widths ≥300 Å in the emission lines [O II]λλ3727,3729Å, [O III]λ5007Å, and Hα. For this, we aim to use the J-PAS survey, which will image an area of ≈8000 deg 2 with 56 narrow band filters in the optical. As a pilot study, we present a methodology designed to select EELGs on the miniJPAS images, which use the same filter dataset as J-PAS, and thus will be exportable to this larger survey. Methods. We make use of the miniJPAS survey data, conceived as a proof of concept of J-PAS, and covering an area of ≈1 deg 2 . Objects were detected in the r SDSS images and selected by imposing a condition on the flux in a given narrow-band J-PAS filter with respect to the contiguous ones, which is analogous to requiring an observed equivalent width larger than 300 Å in a certain emission line within the filter bandwidth. The selected sources were then classified as galaxies or quasi-stellar objects (QSOs) after a comparison of their miniJPAS fluxes with those of a spectral database of objects known to present strong emission lines. This comparison also provided a redshift for each source, which turned out to be consistent with the spectroscopic redshifts when available (|Δz/(1 + z spec )| ≤ 0.01). Results. The selected candidates were found to show a compact appearance in the optical images, some of them even being classified as point-like sources according to their stellarity index. After discarding sources classified as QSOs, a total of 17 sources turned out to exhibit EW 0 ≥ 300 Å in at least one emission line, thus constituting our final list of EELGs. Our counts are fairly consistent with those of other samples of EELGs in the literature, although there are some differences, which were expected due to biases resulting from different selection criteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Deep-field analytical calibration

The next generation of imaging surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Euclid, and the Nancy Grace Roman Space Telescope, will provide unprecedented constraints on cosmology using weak gravitational lensing. To fully exploit this statistical power, shear measurement methods must achieve sub- per cent accuracy while mitigating systematic biases from noise, the point-spread function (PSF), blending, and shear-dependent detection. The analytical calibration framework (AnaCal) has demonstrated such accuracy but requires adding noise to images, reducing effective depth. We introduce Deep-Field Analytical Calibration (DEEP-FIELD AnaCal), an extension of AnaCal that uses deep-field images to compute shear responses while preserving the statistical power of wide-field data. We validate DEEP-FIELD AnaCal on isolated and blended galaxy image simulations with LSST-like conditions, finding it meets the stringent requirement of multiplicative bias $|m| < 3\times 10^{-3}$ at 99.7 per cent confidence. Compared to standard AnaCal applied to wide-field images, DEEP-FIELD AnaCal increases the effective galaxy number density from 17 to 30 arcmin$^{-2}$ for simulated 10-yr LSST data. With deep fields $10\times$ longer than the wide field, we find pixel noise variance in shear estimation is reduced by 30 per cent and overall uncertainty by $\sim 25~{{\ \rm per\ cent}}$. Finally, using the LSST Deep Drilling Fields strategy, we assess sample variance and find an equivalent calibration uncertainty of $\lesssim 0.3~{{\ \rm per\ cent}}$. These results demonstrate that DEEP-FIELD AnaCal offers a promising path to achieve the required shear calibration for upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services

Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions that lead to significant inefficiency in the long term, vehicles should be allocated to requests by optimizing a non-myopic utility function or by batching requests together and optimizing a myopic utility function. While the former approach is typically offline, the latter can be performed online. We point out two major issues with such approaches when applied to paratransit services in practice. First, it is difficult to batch paratransit requests together as they are temporally sparse. Second, the environment in which transit agencies operate changes dynamically (e.g., traffic conditions can change over time), causing the estimates that are learned offline to become stale. To address these challenges, we propose a fully online approach to solve the dynamic vehicle routing problem (DVRP) with time windows and stochastic trip requests that is robust to changing environmental dynamics by construction. We focus on scenarios where requests are relatively sparse—our problem is motivated by applications to paratransit services. We formulate DVRP as a Markov decision process and use Monte Carlo tree search to evaluate actions for any given state. Accounting for stochastic requests while optimizing a non-myopic utility function is computationally challenging; indeed, the action space for such a problem is intractably large in practice. To tackle the large action space, we leverage the structure of the problem to design heuristics that can sample promising actions for the tree search. Our experiments using real-world data from our partner agency show that the proposed approach outperforms existing state-of-the-art approaches both in terms of performance and robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗
DOE OSTI2021

Millisecond timescale reactions observed via X-ray spectroscopy in a 3D microfabricated fused silica mixer

Determination of electronic structures during chemical reactions remains challenging in studies which involve reactions in the millisecond timescale, toxic chemicals, and/or anaerobic conditions. Here, a three-dimensionally (3D) microfabricated microfluidic mixer platform that is compatible with time-resolved X-ray absorption and emission spectroscopy (XAS and XES, respectively) is presented. This platform, to initiate reactions and study their progression, mixes a high flow rate (0.50–1.5 ml min –1 ) sheath stream with a low-flow-rate (5–90 µl min –1 ) sample stream within a monolithic fused silica chip. The chip geometry enables hydro­dynamic focusing of the sample stream in 3D and sample widths as small as 5 µm. The chip is also connected to a polyimide capillary downstream to enable sample stream deceleration, expansion, and X-ray detection. In this capillary, sample widths of 50 µm are demonstrated. Further, convection–diffusion-reaction models of the mixer are presented. The models are experimentally validated using confocal epifluorescence microscopy and XAS/XES measurements of a ferricyanide and ascorbic acid reaction. The models additionally enable prediction of the residence time and residence time uncertainty of reactive species as well as mixing times. Residence times (from initiation of mixing to the point of X-ray detection) during sample stream expansion as small as 2.1 ± 0.3 ms are also demonstrated. Importantly, an exploration of the mixer operational space reveals a theoretical minimum mixing time of 0.91 ms. The proposed platform is applicable to the determination of the electronic structure of conventionally inaccessible reaction intermediates.

3D microfabrication↗
DOE OSTI2024

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2022

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5–50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Evidence for anti-synergism between ion-assisted etching and in-plasma photoassisted etching of silicon in a high-density chlorine plasma

Etching of p-Si in 60 mTorr 10%Cl2/90%Ar Faraday-shielded inductively coupled high density plasmas was investigated under both ionassisted etching (IAE) and photoassisted etching (PAE) conditions. Real-time etching rates and after-etching Si surface chemical compositions were obtained by laser interferometry and vacuum-transfer x-ray photoelectron spectroscopy (XPS), respectively. Precisely controlled ion energy distributions (IEDs) were generated by applying pulsed negative DC bias on the conductive sample stage. Above a 36 eV threshold at a total flow rate of 250 SCCM, the IAE rate increased with the square root of the ion energy. In contrast to the DC bias, etching under RF bias did not exhibit a threshold ion energy because of the wide IED. XPS spectra revealed that the surface layer under PAE conditions had a significantly lower chlorine content, composed of only SiCl. Under IAE conditions, however, silicon dangling bonds (Si•), SiCl 2 , and SiCl 3 were found on the surface, in addition to SiCl, with a relative abundance of SiCl > SiCl 2 , and SiCl 3 . The absence of higher chlorides and Si• under PAE conditions suggested that vacuum ultraviolet photons and above threshold-energy ions interact with the surface very differently. By varying the duty cycle of the pulsed DC bias, it was found that the IAE rate scaled with the energetic ion dose, but only for low duty cycles. For higher duty cycles, the apparent IAE yield fell off with an increasing Cl coverage on the surface, as the duty cycle went up, which pointed to a negative synergy (antisynergism) between PAE and IAE as the explanation. This antisynergism was further supported by the observed decrease of the total etching rate with an increasing period of the pulsed DC bias. A plausible mechanism is that increasing the pulsing period causes more near-surface damage, creating more recombination centers that lead to a higher loss rate of electron-hole pairs through recombination, thereby reducing the PAE rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Self-re-adhering alkali-activated cement composite and its ability to mitigate corrosion of carbon steel in 300 °C hydrothermal environment

Cement-steel interface is a weak point of cement sheath integrity under the environments of high-temperature geothermal wells. This paper presents carbon steel (CS) adherence behaviors of 300 °C-autoclaved alkali-activated Calcium-Aluminate-Cement (CAC)/fly ash F (FAF) (Thermal Shock Resistant Cement, TSRC), granulated blast furnace slag (GBFS)/SiO 2 , and Ordinary Portland Cement (OPC)/SiO 2 blends. The composites’ ability to preserve the bond under the conditions of thermal shock (TS) and strong acid attack (pH 0.6 H 2 SO 4 /brine at 90 °C) as well as their ability to recover the damaged bond and provide steel corrosion protection after additional short-time 5-day curing at 300 °C were evaluated. GBFS/SiO 2 sheath underwent catastrophic failure in the first TS cycle; OPC/SiO 2 lost 78 % and TSRC 51 % of the bond strength in 6 cycles. Only TSRC-CS bond survived 30 days of strong acid exposure; OPC/SiO 2 bond failed after 18 days and GBFS/SiO 2 after 20 days. Addition of micro-glass fibers (MGF) to TSRC further improved its bond strength and CS corrosion protection. Samples of TSRC-CS cured for 30 days at 300 °C before the bond damage recovered 49 % of the damaged bond strength after additional short-time curing. The CS protected by the re-adhered TSRC showed low corrosion rate of 0.13 mm/year (TSRC-MGF), 0.2 mm/year (TSRC) vs. 0.64 mm/year for OPC/SiO 2 protected CS.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Lattice response to ambient self-irradiation of δ-phase 239 Pu-Ga alloys exposed to cryogenic temperatures

Self-irradiation in plutonium is a continuous process that introduces radiation damage ranging from point defects to nanoscale radiation damage as well as decay daughter product impurities that require to be accommodated by the host material. These changes are affecting the structure and properties of the material by lattice swelling, mechanical strengthening, and other alterations. X-ray diffraction and dilatometry studies have shown that the room temperature self-irradiation of δ-phase Pu-Ga alloys (2 and 7 at%Ga) results in swelling of the lattice that saturates after 0.1–0.2 displacement per atom (dpa) of accumulated lattice damage. Here, for a better understanding of these self- irradiation processes, defect accumulation and damage evolution, this time-of-flight neutron diffraction study investigates the impact of ambient self-irradiation effects on the structural evolution of δ-phase 239 Pu-Ga alloys exposed to cryogenic temperatures (<120 K), associated with a varied history of storage time and thermal treatments. Two key behaviors were observed in the lattice evolution after exposure to cryogenic temperatures with respect to room-temperature accumulated self-irradiation damage. Samples with no self- irradiation damage accumulation under ambient conditions showed swelling of the lattice at the end of the measurement, while samples that accumulated significant self-irradiation damage under ambient conditions showed only a partial recovery of the lattice parameter value upon completion of the measurements (cooling followed by heating back to room temperature). Possible causes of the behavior are proposed, and their associated effects are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CROCUS High-Frequency Measurements of CO₂, H₂O, Wind, and Temperature at University of Illinois Chicago

As of April 9, 2026: this dataset is currently being versioned to include data up to March 31, 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. Raw atmospheric measurements collected at the University of Illinois Chicago (UIC) as part of the Community Research on Climate and Urban Science (CROCUS) project. The data includes high-frequency measurements of carbon dioxide (CO₂) concentration, water vapor (H₂O) concentration, wind speed (U, V, W components), temperature, and atmospheric pressure. These raw data are recorded by the LI-7500DS Open Path CO₂/H₂O Analyzer and a sonic anemometer at a 10 Hz acquisition frequency, providing the necessary inputs for calculating fluxes of CO₂, H₂O, heat, and momentum. In addition to gas concentration measurements, the dataset includes diagnostic information from the instruments, including absorptance, sample and reference signals, and diagnostic values. The data were collected to study urban atmospheric conditions and contribute to flux calculations for urban climate research. These measurements form the basis for calculating 30-minute average fluxes of key atmospheric variables using the eddy covariance method. This dataset provides critical raw input data for researchers interested in atmospheric fluxes, urban air quality, and the interaction between the urban environment and atmospheric processes. The data is part of the U.S. Department of Energy’s Biological and Environmental Research (BER) program, under the CROCUS Urban Integrated Field Laboratory (UIFL) project.

54 ENVIRONMENTAL SCIENCES↗