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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning

Many physical processes in science and engineering are naturally represented by operators between infinite-dimensional function spaces. The problem of operator learning, in this context, seeks to extract these physical processes from empirical data, which is challenging due to the infinite or high dimensionality of data. An integral component in addressing this challenge is model reduction, which reduces both the data dimensionality and problem size. In this paper, we utilize low-dimensional nonlinear structures in model reduction by investigating Auto-Encoder-based Neural Network (AENet). AENet first learns the latent variables of the input data and then learns the transformation from these latent variables to corresponding output data. Our numerical experiments validate the ability of AENet to accurately learn the solution operator of nonlinear partial differential equations. Furthermore, we establish a mathematical and statistical estimation theory that analyzes the generalization error of AENet. Finally, our theoretical framework shows that the sample complexity of training AENet is intricately tied to the intrinsic dimension of the modeled process, while also demonstrating the robustness of AENet to noise.

Auto-encoder↗
DOE OSTI2025

Joint cosmic density reconstruction from photometric and spectroscopic samples

ABSTRACT We reconstruct the dark matter density field from spatially overlapping spectroscopic and photometric redshift catalogues through a field-level forward modelling approach. Instead of directly inferring the underlying density field, we find the best-fitting initial Gaussian fluctuations that will evolve into the observed cosmic volume. To account for the substantial uncertainty of photometric redshifts we employ a differentiable continuous Poisson process. As an initial test, we construct a mock based on the upcoming Prime Focus Spectrograph combined with photometric sample modelled on the Subaru Hyper Suprime-Cam. Depending on the statistic of interest, we find improvements in cosmic structure classification equivalent to 50–100 per cent more spectroscopic targets by combining relatively sparse spectroscopic with dense photometric samples.

Horowitz, B.↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2026

D$e^+e^-$ffusion: Capturing the Beam-Beam Physics of $e^+e^-$ Collisions with Diffusion Models

Beam-induced backgrounds at high-luminosity $e^+e^-$ colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulations with dedicated Monte Carlo (MC) event generators. Reliable detector and machine-detector interface studies necessitate event samples that are several orders of magnitude larger than what is practically attainable with existing MC. To alleviate this bottleneck, we present D$e^+e^-$ffusion, a denoising diffusion probabilistic model that operates as a permutation-equivariant, set-valued surrogate for fast IPC simulation. Trained on a small GuineaPig++ sample, D$e^+e^-$ffusion faithfully reproduces the marginal and joint kinematic, angular, and positional distributions of all three IPC production processes. In addition, we assess the fidelity at the detector level by propagating both Geant4 and D$e^+e^-$ffusion events through a Geant4 simulation of the CLD vertex detector and by training a transformer-based two-sample classifier; the classifier achieves an area under the ROC curve of $0.553 \pm 0.016$. The trained model generates events nearly four orders of magnitude faster than Geant4, paving the way for a fast-simulation surrogate for FCC-ee design studies.

Chahine, Antonio [Imperial Coll., London]↗
DOE OSTI2025

Utilization of the LS-APGD microplasma/orbitrap-FTMS booster system for detection and isotopic analysis of neodymium nanoparticles

Detection and isotopic analysis of particle populations has seen rapid growth across several application areas, including environmental analysis, nuclear forensics, and food safety. The ability to characterize the particles' unique elemental and isotopic fingerprints could provide information related to formation, processing history, and transport. Regarding nuclear forensics, isotopic analysis of particles derived from diverse materials is often used as a tool to trace the origin and processing history. Mass spectrometric-based techniques currently used for particle population analysis often suffer from limited mass resolution, particularly when dealing with real-world samples that are affected by isobaric and polyatomic interferences from the matrix. To address these analytical challenges, we propose a novel method utilizing the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an ultrahigh resolution Orbitrap mass spectrometer, further enhanced with the FTMS X2T Booster data acquisition and processing unit. The FTMS Booster enables acquisition of extended transient times of up to 3 s, significantly improving mass resolution, thereby reducing or even eliminating the need for prior separation of isobaric or polyatomic interferences. Additionally, the detection of low-abundance isotopes was improved by increasing the signal-to-noise (S/N) ratio. As proof of concept, this study demonstrates the feasibility of the LS-APGD/Orbitrap-FTMS X2T Booster platform for direct analysis using a suspension of well-characterized ∼120 nm neodymium particles. The quality of the isotope ratios values obtained from a few hundred particles were in good agreement with those obtained from homogeneous ionic solutions. These results highlight the potential of the LS-APGD/Orbitrap platform for rapid, accurate, and interference-resilient isotope ratio analysis of particle populations without the need for dissolution and subsequent chemical separations, offering significant advantages for nuclear forensics, safeguards, and environmental applications. The effort here also points to further paths forward, hopefully towards single particle (SP) analysis using microplasma ionization and the ultrahigh resolving power of the Orbitrap mass analyzer.

FTMS X2T booster↗
DOE OSTI2024

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 15, 22, and 26 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS) to ensure acceptance of their vitrified high-level waste (HLW) into the Civilian Radioactive Waste Management System. Production Records must document the constituents of the MST/SS material in the PRFT from each salt batch (StB) processed at SWPF. Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 15, 22, and 26, which corresponds to material from the processing of StB4, StB5, and StB7, respectively, are reported herein. The unwashed dried solids of the PRFT batches were found to be 86-87% MST. Additionally, the total sulfur values are well below the assumed 982 mg of sulfate/kg of PRFT slurry used in Material Tracking Program calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Investigation of Undissolved Solids from Salt Waste Processing Facility (SWPF) Salt Batches Collected via Filtration

SRNL researchers performed six experiments wherein 0.1 μm-grade stainless steel filters were used to filter samples pulled from salt batches 6, 9B, and 11B, without the addition of monosodium titanate. Three of these experiments were performed to collect filterable solids from each salt batch and characterize trapped solids via scanning electron microscopy. The remaining three experiments were performed to collect and then dissolve the same solids using 3.5 M nitric acid (similar to that employed in the Salt Waste Processing Facility) for characterization via Inductively-coupled plasma atomic emission spectroscopy.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

WHONDRS Surface Water and Sediment Geochemistry and Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon (v2)

This dataset supports a broader study developing conceptual models for river corridor critical zone processes across spatial scales and was generated in collaboration with the HJ Andrews River Corridor Critical Zone Workshop in 2025. The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen) from 48 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Some of the sites have been impacted by the Holiday Farm Fire and the Lookout Fire in 2020 and 2023, respectively. Related data were collected as part of the workshop and will be published separately in collaboration with other workshop attendees and available at http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. Related genomic data can be found on the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1503030 (see critical details section below for more information). Additional related data collected in 2016 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377027 and http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1-2019 (Ward et al., 2019). This data package was originally published in March 2026. It was updated in August 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos, (2) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, (3) a data checks report, (4) a folder of sample data, (5) file-level metadata, (6) data dictionary, (7) field metadata, (8) readme, (9) international generic sample number (IGSN) mapping file; and (10) field protocol. The sample data subfolder contains surface water and sediment (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages, (2) total dissolved nitrogen data and averages, (3) methods codes, (4) FTICR-MS methods; and (5) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the CoreMS processed data and seven subfolders, thee containing .xml files for each sample type (sediment, surface water and blank samples), three containing the sediment CoreMS output files for each sample type (sediment, surface water and blank samples), and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, .json, .jpg, or .jpeg.

Biogeochemistry↗
DOE OSTI2024

Process parameter translation strategies for variable directed energy deposition spot size using 316L, copper, and Inconel 625

Directed energy deposition (DED) is a form of additive manufacturing available across a variety of laser spot diameter values, often referred to as spot sizes. However, there is no method to easily transfer process parameters across discrete spot sizes, leading to DED process parameters that are equipment specific and not widely applicable. In this study, a strategy is proposed and investigated for five spot sizes that keep the areal energy density constant while varying power, feed rate, and powder flow during the deposition of 316L stainless steel. An assessment of trends in hardness and microstructure is possible due to the novel production of components of a single material across several spot sizes using a single nozzle on a single DED system. The proposed strategy was used to nullify the hardness drop during functional grading of Inconel 625 and pure copper, enabling fabrication of multi-material sample that does not compromise desirable properties. This application shows the value in establishing more efficient process parameter development and understanding spot size influences on geometric and material property flexibility, to enable a more diverse powder-based DED design space and to increase the industry adoption of DED systems.

316L↗
DOE OSTI2024

Efficient learning of accurate surrogates for simulations of complex systems

Machine learning methods are increasingly deployed to construct surrogate models for complex physical systems at a reduced computational cost. However, the predictive capability of these surrogates degrades in the presence of noisy, sparse or dynamic data. Here, we introduce an online learning method empowered by optimizer-driven sampling that has two advantages over current approaches: it ensures that all local extrema (including endpoints) of the model response surface are included in the training data, and it employs a continuous validation and update process in which surrogates undergo retraining when their performance falls below a validity threshold. We find, using benchmark functions, that optimizer-directed sampling generally outperforms traditional sampling methods in terms of accuracy around local extrema even when the scoring metric is biased towards assessing overall accuracy. Finally, the application to dense nuclear matter demonstrates that highly accurate surrogates for a nuclear equation-of-state model can be reliably autogenerated from expensive calculations using few model evaluations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Transformational faulting in Mn 2 GeO 4 from olivine to wadsleyite structure: Implications for physical mechanism of deep-focus earthquakes

High-pressure and temperature deformation experiments interfaced with acoustic emission (AE) monitoring have been conducted to study transformational faulting in Mn 2 GeO 4 olivine, which transforms to the β phase, isostructural to wadsleyite. Metastable Mn 2 GeO 4 olivine exhibits a marked embrittlement behavior at temperatures between 800 and 1100 K, emitting numerous AEs. At each temperature, brittle deformation is characterized by a two-stage process: (1) a “preparation” stage with numerous diffusedly located low-magnitude AEs and large b values (>2), and (2) a failure stage where larger-magnitude AEs form a planar distribution with b values about 1. Microstructure analysis reveals extensive kink band development in olivine grains in the recovered samples. Kink band boundaries (KBBs), with a typical thickness of ∼100 nm, are filled with a nanometric β-Mn 2 GeO 4 “gouge”. A dense array of secondary shear localizations is often present within the kink bands, suggesting significant shear deformation therein. The combined observations suggest that faulting in metastable Mn 2 GeO 4 olivine is a self-similar process, from grain-scale to the sample-scale. Both observed embrittlement behavior and the microstructure of metastable Mn 2 GeO 4 olivine are essentially identical to those in Mg 2 GeO 4 olivine we have reported previously, indicating that the physical mechanism of faulting in metastable olivine is insensitive to the specific crystallographic structure of the high-pressure phase. The low b values (about 1) observed in the faulting process in our experiments are similar to those of deep focus earthquakes in cold subduction zones. Our observed mechanism explains deep focus seismicity in cold metastable mantle wedges, provided that the self-similarity assumption holds to geological scales.

58 GEOSCIENCES↗
DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗
DOE OSTI2026

Semi-Dynamic Leach Testing of Densified Silicon-based Iodine Waste Forms

Iodine waste forms (IWF) require a conceptual corrosion release model (CCRM) to provide iodine (I) release rates for performance modeling nuclear waste disposal repositories. To develop a CCRM, an understanding of the corrosion mechanisms of the IWF are required along with data from consistent test methods to parameterize the model. The present study has advanced both areas by providing and assessing the corrosion resistance of IWF types based on their processing history in minor variations of semi-dynamic leach tests. The test included a series of semi-dynamic leach tests using monolithic IWFs in deionized water (leachant). Several experiments were conducted under alternate test conditions with changes to temperature, leachant replacement, leachant pH, leachant volume, masking, and surface finish to elucidate if varying these conditions impacted IWF corrosion behavior. Tests were conducted on two classes of IWFs: (1) I-bearing silver-mordenite (AgZ) materials processed by hot isostatic pressing (HIP) at different temperatures, pressures, sizes, and times; and (2) I-bearing silver-functionalized silica aerogels (SFA) processed by either HIP or spark plasma sintering (SPS). The corrosion susceptibility of AgZ samples was influenced by HIP temperature and pressure. The SPS SFAs retained I far better than HIP SFAs. Additional findings in this study include: (1) The iodine dissolution rate decreased with decreasing temperature, (2) a common ion effect may occur and slow dissolution of the host phase if the leachant is not regularly replaced, (3) pH controls the dissolution rate, and (4) the iodine dissolution rate slows with extended test time (up to 224 days). Based on this work, these parameters should thus be represented when developing a CCRM.

corrosion↗
DOE OSTI2025

Kinetics of short-range order formation in GeSn alloy: MBE vs CVD

Recently, short-range order (SRO) has attracted significant attention, challenging the conventional view of the atomic positions in alloys being random. Furthermore, the presence of SRO has been predicted to have profound effects on the electronic and topological properties of group-IV alloys, offering a different direction in designing group-IV materials for photoelectronic and quantum devices. However, due to the limited understanding of the formation mechanisms, developing effective methods to manipulate SRO in epitaxy is still challenging. To address this, we propose a mechanism for the GeSn alloy, revealing that surface diffusion plays a key role in SRO formation. Building on this mechanism, we show that the distinct surface conditions in MBE and CVD lead to the formation of SRO with enhanced Sn–Sn pairing in MBE-grown samples, while CVD-grown samples remain random alloys. Furthermore, our findings provide an initial understanding of the kinetic process of SRO formation, providing guidance for the design of experiments to manipulate SRO.

Alloys↗
DOE OSTI2024

Characterization and Optimization of Skipper CCDs for the SOAR Integral Field Spectrograph

We present results from the characterization and optimization of Skipper charge-coupled devices (CCDs) for use in a focal plane prototype for the Southern Astrophysical Research Integral Field Spectrograph (SIFS). We tested eight Skipper CCDs and selected six for SIFS based on performance results. The Skipper CCDs are 6k × 1k, 15 μm pixels, thick, fully depleted, p-channel devices that have been thinned to ~250 μm, backside processed, and treated with an anti-reflective coating. We demonstrate a single-sample readout noise of <4.3 e - rms pixel -1 in all amplifiers. We optimize the readout sequence timing to achieve a readout noise of 0.5 e - rms pixel -1 after 74 non-destructive measurements, which can be accomplished in a region covering 5% of the detector area in a readout time of <4 minutes. We demonstrate single-photon-counting in all 24 amplifiers (four amplifiers per detector) with a readnoise of σ N ~ 0.18 e - rms pixel -1 after N samp = 400 samples, and we constrain the degree of nonlinearity to be ≲1% at low signal levels (0 e - to 50 e - ). Clock-induced charge (CIC) remains an important issue when the Skipper CCD is configured to provide a large full-well capacity. We achieve a CIC rate of <1.45 × 10 -3 e - pixel -1 frame -1 for a full-well capacity of ~900 e - , which increases to a CIC rate of ~3 e - pixel -1 frame -1 for full-well capacities ~40,000-65,000 e - . We also perform conventional CCD characterization measurements such as charge transfer inefficiency (3.44 × 10 -7 on average), dark current (~2 × 10 -4 e - pixel -1 s -1 ), photon transfer curves, cosmetic defects (<0.45% “bad” pixels), and charge diffusion (point-spread function < 7.5 μm) to verify that these properties are consistent with expectations from conventional p-channel CCDs used for astronomy. Furthermore, we provide the first measurements of the brighter-fatter effect and absolute quantum efficiency (≳80% between 450 and 980 nm; ≳90% between 600 and 900 nm) using Skipper CCDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

West Valley Demonstration Project (WVDP) Annual Site Environmental Report (ASER) for Calendar Year 2024

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2024. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2024 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

54 ENVIRONMENTAL SCIENCES↗