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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
DOE OSTI2024

The SRG/eROSITA All-Sky Survey: Dark Energy Survey year 3 weak gravitational lensing by eRASS1 selected galaxy clusters

Context. Number counts of galaxy clusters across redshift are a powerful cosmological probe if a precise and accurate reconstruction of the underlying mass distribution is performed – a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing (WL) by clusters has become the method of choice for this measurement. Aims. We measured and validated the WL signature in the shape of galaxies observed in the first three years of the Dark Energy Survey (DES Y3) caused by galaxy clusters and groups selected in the first all-sky survey performed by SRG (Spectrum Roentgen Gamma)/eROSITA (eRASS1). These data were then used to determine the scaling between the X-ray photon count rate of the clusters and their halo mass and redshift. Methods. We empirically determined the degree of cluster member contamination in our background source sample. The individual cluster shear profiles were then analyzed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we performed mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allowed us to establish that hydrodynamical modeling uncertainties at low lens redshifts (z < 0.6) are the dominant systematic limitation. At high lens redshift, the uncertainties of the sources’ photometric redshift calibration dominate. Results. With regard to the X-ray count rate to halo mass relation, we determined its amplitude, its mass trend, the redshift evolution of the mass trend, the deviation from self-similar redshift evolution, and the intrinsic scatter around this relation. Conclusions. The mass calibration analysis performed here sets the stage for a joint analysis with the number counts of eRASS1 clusters to constrain a host of cosmological parameters. We demonstrate that WL mass calibration of galaxy clusters can be performed successfully with source galaxies whose calibration was performed primarily for cosmic shear experiments, opening the way for the cluster cosmological exploitation of future optical and NIR surveys like Euclid and LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Final Report on Characterization of Irradiated Sensors and Coupling Adhesive Bonds

This report summarizes characterization via scanning/transmission electron microscopy of the microstructures of the unirradiated and irradiated piezoelectric ultrasonic sensor/aluminum substrate assemblies using four commercially available inorganic coupling adhesives to bond two types of piezoelectric crystals to the substrates. The sample assemblies were irradiated in the PULSTAR reactor at NC State University and ultrasonic data was collected in-situ. ORNL LAMDA Laboratory capabilities were utilized to perform pre- and post-irradiation examination of the sensor assemblies. This document summarizes the PIE performed at the ORNL LAMDA laboratory. The results of the PIE described in this report are consistent with the ultrasonic data collected during irradiation – in particular, high temperature epoxy adhesive seemed to provide the best coupling as compared to the refractory ceramic adhesives. It was determined that the quality of the sensor-adhesive-substrates governed the ultrasonic performance of the sensors. It was also apparent that irradiation did not significantly affect bond quality, which is also supported by the ultrasonic data collected during irradiation. A more comprehensive DOE NSUF Final Report including details of materials selection, sample fabrication, initial ultrasonic testing, irradiation and in-situ ultrasonic testing, positron annihilation lifetime spectroscopy and doppler broadening spectroscopy performed at EPRI and NC State University will be published at the conclusion of the project.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AutoTandemML: Active Learning Enhanced Tandem Neural Networks for Inverse Design Problems

Inverse design in science and engineering involves determining optimal design parameters that achieve desired performance outcomes, a process often hindered by the complexity and high dimensionality of design spaces, leading to significant computational costs. To tackle this challenge, we propose a novel hybrid approach that combines active learning with Tandem Neural Networks to enhance the efficiency and effectiveness of solving inverse design problems. Active learning allows to selectively sample the most informative data points, reducing the required dataset size without compromising accuracy. We investigate this approach using three benchmark problems: airfoil inverse design, photonic surface inverse design, and scalar boundary condition reconstruction in diffusion partial differential equations. We demonstrate that integrating active learning with Tandem Neural Networks outperforms standard approaches across the benchmark suite, achieving better accuracy with fewer training samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bioelectrochemical crossbar architecture screening platform for extracellular electron transfer

Electroactive microbes can serve as living components in bioelectronic devices, where their unique ability to transfer electrons enables applications in sensing, energy conversion, and synthesis, but they remain challenging to engineer because the bioelectrochemical systems (BESs) used for characterization are low throughput. Here, we present a bioelectrochemical crossbar architecture screening platform (BiCASP) that uses stacked and orthogonally arrayed electrodes to enable individual sample selection for characterization in arrayed formats. This device reports on the current generated by electroactive bacteria on the minute timescale, decreasing the time for data acquisition by several orders of magnitude compared to conventional BESs. This device increases the throughput of screening engineered biological components in cells, identifying mutants of the membrane protein wire MtrA in Shewanella oneidensis that retain the ability to support extracellular electron transfer (EET). BiCASP may be integrated with bioelectronics that need directed evolution of electroactive proteins.

Shewanella↗
DOE OSTI2024

Leveraging Calibration Transfer Techniques for Remote Monitoring of Samarium and Europium in LiCl Using Laser-Induced Florescence Spectroscopy for Radioisotope Production Applications

Radioisotope production relies on complex chemical processes that must be performed in radiological hot cells or glove boxes because of the radioactive and otherwise hazardous materials being used. In these situations, optical sensors can provide real-time monitoring to users, which is unobtainable by more traditional methods. This study explores the use of calibration transfer methods to train a model on one instrument and date and then transfer it to another instrument of the same or different configuration on a different date. By performing laser-induced fluorescence measurements of Eu(III) and Sm(III) in 10 M LiCl over the course of 6 months using two disparate spectrometers and two different training sets, a strategy for calibrating and deploying models for online monitoring was established. Three transfer techniques were compared: direct standardization (DS), piecewise direct standardization (PDS), and external parameter orthogonalization (EPO). DS and PDS outperformed EPO for day-to-day transfers, and EPO was not effective for instrument-to-instrument transfers. Transferring the initial date’s full factorial model provided better prediction performance compared with retraining models the day of measurements using a D-optimal designed calibration set. For both day-to-day and instrument-to-instrument transfers, five Kennard–Stone selected samples were sufficient. Based on this choice, the initial-date, high-resolution spectrometer model was transferred to a lower-resolution, compact spectrometer 6 months later to monitor a simulated, real-time demonstration. Here, the combined predictions of the DS and PDS transferred models were able to accurately track the anticipated concentration profiles, maintaining root-mean-square error of prediction values below 10 ppm.

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

Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.

atomic force microscopy↗
DOE OSTI2026

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning

Residual-based adaptive strategies are widely used in scientific machine learning yet remain largely heuristic. We introduce a variational framework that formalizes these methods through convex transformations of the residual, where different transformations correspond to distinct objective functionals. For instance, exponential weights target uniform error minimization, while linear weights recover quadratic error minimization. This perspective reveals adaptive weighting as a means of selecting sampling distributions that optimize a primal objective, directly linking discretization choices to error metrics. This principled approach yields three key benefits: it enables systematic design of adaptive schemes, reduces discretization error by lowering estimator variance, and enhances learning dynamics by improving gradient signal-to-noise ratio. Extending the framework to operator learning, we demonstrate substantial performance gains across diverse optimizers and architectures. Our results provide a theoretical perspective for residual-based adaptivity and establish a foundation for principled discretization and training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Electrochemical carbon deposition from CO 2 in molten carbonates: substrate-dependent growth

Electrochemical carbon deposition from molten carbonate salts using inert electrodes and no additional catalyst is systematically examined. At sufficiently cathodic potentials, carbon formation occurs within 30 min and transitions from substrate-dependent nucleation to carbon-on-carbon growth. Although deposits formed on either mild-steel or graphite cathodes exhibit comparable thicknesses and salt contents, their macrostructures differ, reflecting differences in early-stage growth rates and surface chemistry. Characterization by ICP-OES, Raman spectroscopy, SEM/EDS, synchrotron powder X-ray diffraction, and C K-edge X-ray absorption near edge structure reveals that the as-deposited carbon is predominantly disordered sp 2 -bonded material. However, post-treatment reveals latent turbostratic ordering in select samples, indicating that short-range order is established during deposition but is obscured by an entrained electrolyte and kinetically formed amorphous phases. No anode-derived contamination is detected, and carbon grown on graphite cathodes shows minimal metallic impurities. These results clarify the role of cathode surface chemistry and provide pathways for controlling electrode-derived impurity incorporation and carbon structure in catalyst-free molten carbonate systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Controlled molecule injector for cold, dense, and pure molecular beams at the European x-ray free-electron laser

A permanently available molecular-beam injection setup for controlled molecules (COMO) was installed and commissioned at the small quantum systems (SQS) instrument at the European x-ray free-electron laser (EuXFEL). A b-type electrostatic deflector allows for pure state-, size-, and isomer-selected samples of polar molecules and clusters. The source provides a rotationally cold (T ≈ 1 K) and dense (ρ ≈ 10 8 cm −3 ) molecular beam with pulse durations up to 100 µs generated by a new version of the Even-Lavie valve. Here, a performance overview of the COMO setup is presented along with characterization experiments performed both with an optical laser at the Center for Free-Electron-Laser Science and with x rays at EuXFEL under burst-mode operation. COMO was designed to be attached to different instruments at the EuXFEL, in particular, the SQS and single particles, clusters, and biomolecules (SPB) instruments. This advanced controlled-molecules injection setup enables x-ray free-electron laser studies using highly defined samples with soft and hard x-ray FEL radiation for applications ranging from atomic, molecular, and cluster physics to elementary processes in chemistry and biology.

He, Lanhai↗
DOE OSTI2025

Metal-organic chemical vapor deposition of MgGeN2 films on GaN and sapphire

MgGeN2 films were synthesized using metal-organic chemical vapor deposition on GaN/c-sapphire templates and c-plane sapphire substrates. Energy-dispersive x-ray spectroscopy was used to estimate the cation composition ratios. To mitigate magnesium evaporation, the films were grown at pyrometer temperature 745 °C with a wafer rotation speed of 1000 rpm. Growth rates were determined by fitting energy-dispersive x-ray spectroscopy spectra to film thicknesses using NIST DTSA-II software. The thickness estimates determined by this method were consistent with scanning transmission electron microscopy measurements done for selected samples. Scanning electron microscopy images revealed faceted surfaces indicative of a tendency toward three-dimensional growth. X-ray diffraction spectra confirmed that the films were highly crystalline and exhibited preferential orientation in alignment with the substrate. Atomic force microscopy measurements show that film thicknesses are consistent across samples grown on both GaN templates and sapphire substrates, with typical roughnesses around 10 nm. Transmittance spectra of films grown on double-side-polished sapphire substrates yielded band gaps of 4.28 ± 0.06 eV for samples exhibiting close-to-ideal stoichiometry. Comparison of the measured spectra with ab initio calculations are in good agreement both near the bandgap and at higher energies where excitation is into higher-lying bands. These findings provide insight into the growth and characterization of MgGeN2, contributing to the development of this material for potential applications in optoelectronics and power electronics.

Hu, Chenxi (ORCID:0000000236299660)↗
DOE OSTI2024

The clustering of Lyman Alpha Emitting galaxies at 𝗓=2–3

Here, we measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z = 2.45 and 3.1 in 9 sq. deg. centered on the COSMOS field with median Lyα fluxes of ≈ 10 -16 erg s -1 cm -2 . Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r 0 = 3.0 ± 0.2 h -1 Mpc. Within our fiducial cosmology these correspond to 3D number densities of ≈ 10 -3 h 3 Mpc -3 and, from our mock catalogs, biases of 1.7 and 2.0 at z= 2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (≤ 8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Host galaxies of ultra-strong Mg ii absorbers at z ∼ 0.7

ABSTRACT We report spectroscopic identification of the host galaxies of 18 ultra-strong Mg ii systems (USMg ii) at 0.6 ≤ z ≤ 0.8. We created the largest sample by merging these with 20 host galaxies from our previous survey within 0.4 ≤ z ≤ 0.6. Using this sample, we confirm that the measured impact parameters ($\rm 6.3\leqslant D[kpc] \leqslant 120$ with a median of 19 kpc) are much larger than expected, and the USMg ii host galaxies do not follow the canonical $\rm {\it W}_{2796}-{\it D}$ anticorrelation. We show that the presence and significance of this anticorrelation may depend on the sample selection. The $\rm {\it W}_{2796}-{\it D}$ anticorrelation seen for the general Mg ii absorbers show a mild evolution at low $\rm W_{2796}$ end over the redshift range 0.4 ≤ z ≤ 1.5 with an increase of the impact parameters. Compared to the host galaxies of normal Mg ii absorbers, USMg ii host galaxies are brighter and more massive for a given impact parameter. While the USMg ii systems preferentially pick star-forming galaxies, they exhibit slightly lower ongoing star-forming rates compared to main sequence galaxies with the same stellar mass, suggesting a transition from star-forming to quiescent states. For a limiting magnitude of mr < 23.6, at least 29 per cent of the USMg ii host galaxies are isolated, and the width of the Mg ii absorption in these cases may originate from gas flows (infall/outflow) in isolated haloes of massive star forming but not starbursting galaxies. We associate more than one galaxy with the absorber in $\ge 21~{{\ \rm per\ cent}}$ cases, where interactions may cause wide velocity spread.

Astronomy & Astrophysics↗
DOE OSTI2026

Dark Energy Survey Year 3: Blue shear

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. Here, using the Dark Energy Survey Year 3 shape catalog, we expect less impact from IA when we limit the sample to blue, star-forming galaxies. The cosmological parameter constraints from this BLUE cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the Ω m and 𝑆 8 better agree with the observations from Planck on the cosmic microwave background. Mitigating IA with sample selection in DES, rather than flexible model choices, can reduce uncertainty in 𝑆 8 by a factor of 1.5.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measurement of Two-Point Energy Correlators within Jets in 𝑝 + 𝑝 Collisions at $\sqrt{𝑠}$ = 200 GeV

Hard-scattered partons ejected from high-energy proton-proton collisions undergo parton shower and hadronization, resulting in collimated collections of particles that are clustered into jets. A substructure observable that highlights the transition between the perturbative and nonperturbative regimes of jet evolution in terms of the angle between two particles is the two-point energy correlator (EEC). In this Letter, the first measurement of the EEC at RHIC is presented, using data taken from 200 GeV 𝑝 + 𝑝 collisions by the STAR experiment. The EEC is measured both for all the pairs of particles in jets and separately for pairs with like and opposite electric charges. These measurements demonstrate that the transition between perturbative and nonperturbative effects occurs within an angular region that is consistent with expectations of a universal hadronization regime that scales with jet momentum for a given initiator flavor. Additionally, a deviation from Monte Carlo predictions at small angles in the charge-selected sample could result from mechanics of hadronization not fully captured by current models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Composition Quantification of SiGeSn Alloys Through Time-of-Flight Secondary Ion Mass Spectrometry: Calibration Methodologies and Validation With Atom Probe Tomography

Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) is a powerful technique for elemental compositional analysis and depth profiling of materials. However, it encounters the problem of matrix effects that hinder its application. In this work, we introduce a pioneering ToF-SIMS calibration method tailored for SixGeySnz ternary alloys. SixGe1-x and Ge1-zSnz binary alloys with known compositions are used as calibration reference samples. Through a systematic SIMS quantification study of SiGe and GeSn binary alloys, we unveil a linear correlation between secondary ion intensity ratio and composition ratio for both SiGe and GeSn binary alloys, effectively mitigating the matrix effects. Extracted relative sensitivity factor (RSF) value from SixGe1-x (0.07 < x < 0.83) and Ge1-zSnz (0.066 < z < 0.183) binary alloys are subsequently applied to those of SixGeySnz (0.011 < x < 0.113, 0.863 < y < 0.935 and 0.023 < z < 0.103) ternary alloys for elemental compositions quantification. These values are cross-checked by Atom Probe Tomography (APT) analysis, an indication of the great accuracy and reliability of as-developed ToF-SIMS calibration process. Furthermore, the proposed method and its reference sample selection strategy in this work provide a low-cost as well as simple-to-follow calibration route for SiGeSn composition analysis, thus driving the development of next-generation multifunctional SiGeSn-related semiconductor devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PE1 Site Characterization: Data Documentation on Geologic and Hydrologic Lab Testing

This data documentation report describes geologic and hydrologic laboratory analysis and data collected in support of site characterization of the Physical Experiment 1 (PE1) testbed, Aqueduct Mesa, Nevada. The documentation includes a summary of laboratory tests performed, discussion of sample selection for assessing heterogeneity of various testbed properties, methods, and results per data type.

58 GEOSCIENCES↗
DOE OSTI2025

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

Sediment from 44 core samples collected from Resource Conservation and Recovery Act (RCRA) boreholes drilled in the 200 East and 200 West areas of the Hanford Site were characterized for physical and hydraulic properties (Table S.1). Characterization data included gravimetric water contents and matric potentials, grain-size distributions, saturated hydraulic conductivity, water retention characteristics, and unsaturated hydraulic conductivity. These properties provide site-specific data and parameters that can be used in subsurface flow and contaminant transport models to assess the transport and fate of contaminants in the vadose zone and underlying aquifer systems. The analyzed core samples come from specific areas and depth intervals at the Hanford Site that were targeted for sampling to address data gaps identified by site contractors (Khaleel 2020). X-ray computed tomography (XCT) was used to evaluate the general textural characteristics of the samples and to determine which samples to use for further physical and hydraulic property characterization. Subsequent sample selection was determined by consensus after review of the XCT images by Pacific Northwest National Laboratory, Central Plateau Cleanup Company, and INTERA staff.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗