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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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DOE OSTI2025

Testing gravitational physics by combining DESI DR1 and weak lensing datasets using the E_G estimator

The action of gravitational physics across space-time creates observable signatures in the behaviour of light and matter. We perform combined-probe studies using data from the Baryon Oscillation Spectroscopic Survey (BOSS) and Dark Energy Spectroscopic Instrument survey Data Release 1 (DESI-DR1), in combination with three existing weak lensing surveys, the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper Suprime-Cam Survey (HSC), to test and constrain General Relativity (GR) in the context of the standard model of cosmology (LCDM). We focus on measuring the gravitational estimator statistic, E_G, which describes the relative amplitudes of weak gravitational lensing and galaxy velocities induced by a common set of overdensities. By comparing our amplitude measurements with their predicted scale- and redshift-dependence within the GR+LCDM model, we demonstrate that our results are consistent with the predictions of the Planck cosmology. The redshift span of the DESI dataset allows us to perform these E_G measurements at the highest redshifts achieved to date, z ~ 1.

cosmology↗
DOE OSTI2025

The Effect of a Carbon Fiber Layer Between the Cathode and the Current Collector on Battery Cell Performance

Contact resistance between the cathode active material (CAM) and the Al current collector can be reduced by applying carbon coatings to the Al current collector surface. However, this process requires an additional step of carbon layer coating on the current collector, which increases both manufacturing costs and processing time. In the present work, an interlayer of continuous unsized carbon fibers aligned in one direction (CF interlayer), is introduced between the Al current collector and the NMC811 cathode during cathode deposition on the Al current collector. This single-step approach eliminates the need for the additional carbon layer coating on the current collector. Additionally, this approach removes the use of toxic solvents and insulative polymers used for making the carbon coating. The CF interlayer improves the rate capability at higher C-rates. The CF interlayer lowers the contact resistance between the cathode particles and the current collector while improving the activation energy of charge transfer. The peel test showed that the CF interlayer does not affect the adhesion strength of the cathode layer with the current collector.

25 ENERGY STORAGE↗
DOE OSTI2026

The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMM-LSS Fields

Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom value-added catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z < 1.6, 9713 quasars, and 35,222 stars. The resulting catalogs achieve a redshift purity exceeding 99.4% across all galaxy samples. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.

Ratajczak, J. [Univ. of Utah, Salt Lake City, UT (↗
DOE OSTI2026

Highly Efficient Selection of High-redshift Emission-line Galaxies for Future DESI-like Surveys with Deep Multiband Imaging

Emission-line galaxies (ELGs) are an important tracer of baryon acoustic oscillations (BAOs) and large-scale structure at z > 1. In this work, we investigate the feasibility of using deep wide-area multiband imaging (e.g., from the Rubin Observatory) to efficiently select high-redshift ELGs. Using Hyper Suprime-Cam grizy photometry and COSMOS2020 many-band photometric redshifts, we design simple color cuts guided by a probabilistic random forest classifier to select galaxies at z = 1.1–1.6. We then empirically test and refine these color cuts using two samples of galaxies with deep spectroscopy and broad color coverage obtained with the Dark Energy Spectroscopic Instrument (DESI). Compared to DESI ELGs at z = 1.1–1.6, we achieve a higher redshift-measurement success rate (89% versus 69%), a much higher correct redshift-range success rate (84% versus 34%), and a far higher net surface density yield (1372 deg −2 versus 660 deg −2 ). Combining our sample with current DESI ELGs would increase the net ELG number density by a factor of ∼2.5, moving it out of the shot-noise limited regime and reducing the uncertainties on the BAO scale parameter at z = 1.1–1.6 by a factor of ∼2 at the highest redshifts. We also test selections using shallower photometry and obtain qualitatively similar results.

Salcedo Hernandez, Yoquelbin [University of Pittsb↗
DOE OSTI2026

A Unified Photometric Redshift Calibration for Weak Lensing Surveys Using the Dark Energy Spectroscopic Instrument

The effective redshift distribution n(z) of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining n(z) for weak lensing surveys based on high-quality redshifts and neural-network-based importance weights. Additionally, we present the first unified photometric redshift calibration of the three leading stage-III weak lensing surveys, the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS), with state-of-the-art spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We verify our method using a new, data-driven approach and obtain n(z) constraints with statistical uncertainties of the order of $σ_z$ ~ 0.01 and smaller. Our analysis is largely independent of previous photometric redshift calibrations and, thus, provides an important cross-check in light of recent cosmological tensions. Overall, we find excellent agreement with previously published results on the DES Y3 and HSC Y1 data sets, while there are some differences on the mean redshift with respect to the previously published KiDS-1000 results. We attribute the latter to mismatches in photometric noise properties in the COSMOS field compared to the wider KiDS self-organizing map-gold catalog. At the same time, the new n(z) estimates for KiDS do not significantly change estimates of cosmic structure growth from cosmic shear. Finally, we discuss how our method can be applied to future weak lensing calibrations with DESI data.

Lange, J. U. [American Univ., Washington, DC (Unit↗
DOE OSTI2026

Joint Analysis of Small-scale Galaxy Clustering and Galaxy–Galaxy Lensing from BOSS Galaxies

We present a joint analysis of galaxy clustering and galaxy–galaxy lensing measurements from BOSS galaxies using a simulation-based emulation method combined with a halo occupation distribution model. Our emulators are constructed with the Aemulus ν simulations, a suite of wνCDM N-body simulations with massive neutrinos as independent particle species. We combine small-scale analysis of clustering from 0.1 to 60.2 h −1 Mpc and lensing from 1.7 to 60.2 h −1 Mpc to perform cosmological constraints. We split the BOSS galaxies into three redshift bins to measure their clustering and employ galaxies from Dark Energy Camera Legacy Survey and Hyper Suprime-Cam as source galaxies to measure lensing separately. We find that the addition of lensing significantly improves the constraining power on $S_8 = σ_8(Ω_m/0.3)^{0.5}$, with a weak improvement for fσ 8 . Our results of fσ 8 indicate tensions of around 1σ−4σ below the results of the cosmic microwave background observations of Planck. For S 8 , our results are also lower than Planck, and the tension can be mitigated when considering possible systematics in lensing measurement. As a by-product, our analysis prefers a nonzero neutrino mass but without strong significance, with the constraining power dominated by the clustering. Given the accuracy and precision of our model and the observational data, it is anticipated that larger and higher-quality spectroscopic data sets will improve the constraints on this fundamental property in the near future.

Gao, Wenhao [Shanghai Jiao Tong University (China)↗
DOE OSTI2026

ELVES-Dwarf. I. Satellite Systems of Eight Isolated Dwarf Galaxies in the Local Volume

The satellite populations of Milky Way (MW)–mass systems have been extensively studied, significantly advancing our understanding of galaxy formation and dark matter physics. In contrast, the satellites of lower-mass dwarf galaxies remain largely unexplored, despite hierarchical structure formation predicting that dwarf galaxies should host their own satellites. We present the first results of the ELVES-Dwarf survey, which aims to statistically characterize the satellite populations of isolated dwarf galaxies in the Local Volume (4 < D < 10 Mpc). We identify satellite candidates in integrated light using Legacy Surveys data and achieve completeness down to M g ≈ −9 mag. We then confirm the association of satellite candidates with host galaxies using surface-brightness fluctuation distances measured from Hyper Suprime-Cam data. We surveyed eight isolated dwarf galaxies with stellar masses ranging from sub-Small Magellanic Cloud to Large Magellanic Cloud scales $(10^{7.8} < M^{\textrm{host}}_{\star} < 10^{9.5} M_⊙)$, and confirmed six satellites with stellar masses between 10 5.6 and 10 8 M ⊙ . Most confirmed satellites are star-forming, in contrast to the primarily quiescent satellites observed around MW-mass hosts. By comparing observed satellite abundances and stellar mass functions with theoretical predictions, we find no evidence of a “missing satellite problem” in the dwarf galaxy regime.

Li, Jiaxuan 嘉轩李 [Princeton University, NJ (United ↗
DOE OSTI2026

Quiescent Host Galaxies of Extended Quasars Revealed by Spectrophotometric Decomposition

Previous works of low-redshift quasar host galaxies have focused on compact quasars and found that their host galaxies are mainly star-forming galaxies. Here, we present a study of host galaxies for quasars with extended morphologies in ground-based optical images. We select a sample of more than 1000 type 1 quasars at redshift 0.1 < z < 1 that are classified as extended objects by the Dark Energy Spectroscopic Instrument (DESI). Combining high-resolution spectra from DESI and high-quality images from Subaru Hyper Suprime-Cam, we develop a spectrophotometric decomposition technique to iteratively decompose each quasar into an active galactic nucleus (AGN) component and its host galaxy. The technique can effectively break the degeneracy between the AGN and host components and capture the host spectral features. Our results show that the host galaxies of most quasars have low star formation rates (SFRs) and low specific SFRs, indicating that they are quiescent galaxies. Many of them exhibit prominent post-starburst features with the existence of significant old stellar populations. These properties are quite different from the nature of compact quasars with star-forming host galaxies. In addition, the relation between the black hole mass and stellar mass for our sample is broadly consistent with the canonical local relations. This work is complementary to the previous studies and suggests that the host galaxies of low-redshift quasars are more diverse than was thought.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DESI-DR1 $3 \times 2$-pt analysis: consistent cosmology across weak lensing surveys

We present a joint cosmological analysis of projected galaxy clustering observations from the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1), and overlapping weak gravitational lensing observations from three datasets: the Kilo-Degree Survey (KiDS-1000), the Dark Energy Survey (DES-Y3), and the Hyper-Suprime-Cam Survey (HSC-Y3). This combination of large-scale structure probes allows us to measure a set of $3 \times 2$-pt correlation functions, breaking the degeneracies between parameters in cosmological fits to individual observables. We obtain mutually-consistent constraints on the parameter $S_8 = σ_8 \sqrt{Ω_{\rm m}/0.3} = 0.786^{+0.022}_{-0.019}$ from the combination of DESI-DR1 and DES-Y3, $S_8 = 0.760^{+0.020}_{-0.018}$ from KiDS-1000, and $S_8 = 0.771^{+0.026}_{-0.027}$ from HSC-Y3. These parameter determinations are consistent with fits to the Planck Cosmic Microwave Background dataset, albeit with $1.5-2σ$ lower values in the $S_8-Ω_{\rm m}$ plane. We perform our analysis with a unified pipeline tailored to the requirements of each cosmic shear survey, which self-consistently determines cosmological and astrophysical parameters. We generate an analytical covariance matrix for the correlation data including all cross-covariances between probes, and we design a new blinding procedure to safeguard our analysis against confirmation bias, whilst leaving goodness-of-fit statistics unchanged. Our study is part of a suite of papers that present joint cosmological analyses of DESI-DR1 and weak gravitational lensing datasets.

Porredon, A. [Madrid, CIEMAT; Edinburgh U., Inst. ↗
DOE OSTI2025

Cosmological Constraints from Full-Scale Clustering and Galaxy-Galaxy Lensing with DESI DR1

We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy-galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. We analyze four samples drawn from the Bright Galaxy Survey (BGS) and the Luminous Red Galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing measurements from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to $0.4 \, h^{-1} \, \mathrm{Mpc}$ for clustering and $2.5 \, h^{-1} \, \mathrm{Mpc}$ for lensing, leading to stringent constraints on $S_8 = σ_8 \sqrt{Ω_\mathrm{m} / 0.3}$ and $Ω_\mathrm{m}$ when fixing other cosmological parameters to those preferred by the CMB. We find $S_8 = 0.794 \pm 0.023$ and $Ω_\mathrm{m} = 0.295 \pm 0.012$ when using lensing measurements from DES and KiDS. Similarly, for HSC, we find $S_8 = 0.793 \pm 0.017$ and $Ω_\mathrm{m} = 0.303 \pm 0.010$ when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of non-linear scales.

Lange, Johannes U. [American U.] (ORCID:0000000224↗
DOE OSTI2025

Clustering redshift distribution calibration of weak lensing surveys using the DESI-DR1 spectroscopic dataset

We estimate the source redshift distribution of current weak lensing surveys by applying the clustering-based redshift calibration technique, using the galaxy redshift sample provided by the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1). We cross-correlate the Bright Galaxy Survey (BGS), Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) from DESI, within the redshift range $0.1 < z < 1.6$, with overlapping tomographic source samples from the Dark Energy Survey (DES), Kilo-Degree Survey (KiDS), and Hyper Suprime-Cam (HSC) survey. Using realistic mock catalogues, we test the stability of the clustering-redshift signal to fitting scale, reference-sample choice, and the evolution of source galaxy bias, and we explicitly model and marginalise over magnification contributions, which become non-negligible at $z \gtrsim 1$ due to the depth of the DESI ELG sample. We then compare the resulting bias-weighted redshift distributions to those calibrated using self-organising map (SOM) techniques, finding agreement within uncertainties for all surveys and tomographic bins. Our results demonstrate that clustering redshifts enabled by DESI's unprecedented spectroscopic sample provides a robust, complementary, and independent constraint capable of reducing one of the dominant systematic uncertainties in weak lensing cosmology.

Ruggeri, R. [Queensland U.]↗
DOE OSTI2025

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests

Combined survey analyses of galaxy clustering and weak gravitational lensing (3x2-pt studies) will allow new and accurate tests of the standard cosmological model. However, careful validation is necessary to ensure that these cosmological constraints are not biased by uncertainties associated with the modelling of astrophysical or systematic effects. In this study we validate the combined 3x2-pt analysis of the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) spectroscopic galaxy clustering and overlapping weak lensing datasets from the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper-Suprime-Cam Survey (HSC). By propagating the modelling uncertainties associated with the non-linear matter power spectrum, non-linear galaxy bias and baryon feedback, we design scale cuts to ensure that measurements of the matter density and the amplitude of the matter power spectrum are biased by less than 30% of the statistical error. We also test the internal consistency of the data and weak lensing systematics by performing new measurements of the lensing shear ratio. We demonstrate that the DESI-DR1 shear ratios can be successfully fit by the same model used to describe cosmic shear correlations, and analyse the additional information that can be extracted about the source redshift distributions and intrinsic alignment parameters. This study serves as crucial preparation for the upcoming cosmological parameter analysis of these datasets.

Emas, N. [Swinburne U., Ctr. Astrophys. Supercompu↗
DOE OSTI2026

Alpha-Imaging Detector System Development for Large Area Monitoring

Effective management and disposal of legacy nuclear waste are essential for ensuring safe work environments and minimizing environmental impacts. Monitoring airborne actinide contamination is particularly critical due to the high internal dose potential of alpha-emitting radionuclides. Traditional continuous air monitoring systems (CAMs) used in the industry are limited in the volume of air they can sample, potentially leading to inaccurate radiation detection over large areas. For example, in 2018, elevated levels of airborne Plutonium-239 were detected beyond the controlled areas of the Hanford Plutonium Finishing Plant, highlighting the potential risks to both plant workers and nearby residents. To address these challenges, high-efficiency particulate absorbing (HEPA) air purifiers can enhance air flow by up to 1.5 orders of magnitude, thereby increasing monitoring efficiency and providing a cost-effective solution for large-area surveillance. To quantify the activities of alpha-emitting radionuclides on HEPA filters, the Savannah River National Laboratory is developing an advanced alpha-imaging detection system. This system includes scintillating materials combined with a digital scientific camera. A significant concern in operating such a large-area airborne monitoring system is the handling of HEPA filters, which may be contaminated with radioactive particles. To mitigate these hazards, it is crucial to ensure that any contamination is securely fixed onto the filters. Efforts have been made to optimize the sensitivity of scintillator-epoxy composites and apply them to HEPA filters. These materials were characterized using fluoroscence spectroscopy. These techniques confirmed the purity of the raw materials, the dispersion of scintillators in the epoxy matrix, and the stability of their optical and structural properties post-modification. The optimal scintillator-epoxy composite was selected for use on alpha-spiked HEPA filters to evaluate the efficiency of the sprayer. HEPA filters, embedded with alpha particles collected by an air purifier deployed in an airborne radiation area, have been tested to assess detection efficiency. Future work will focus on employing multiple imaging sensors simultaneously to enhance sensitivity across different regions of the HEPA filter.

Pham, Phuong [Savannah River National Laboratory (↗
DOE OSTI2024

Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction

The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities.” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

Atmosphere↗
DOE OSTI2025

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2025

Improved representation of black carbon mixing structures suggests stronger direct radiative heating

Black carbon significantly influences the Earth system because of its strong solar radiation absorption. However, its direct radiative effect remains poorly understood in current climate models, partly because current climate models oversimplify the diverse structures formed when black carbon mixes with other atmospheric components. Here we show that incorporating more realistic, multi-mixing-structure representations of black carbon increases the direct radiative effect. We find that aged black carbon particles, with thicker coatings and higher embedded fractions, enhance the direct radiative effect more efficiently. Using machine learning alongside the Community Earth System Model, we show that the direct radiative effect at the top of the atmosphere in regions with heavy black carbon pollution is 31.6% greater when multi-mixing structures are considered. These findings highlight the importance of modeling complex mixing structures of particle-resolved black carbon to accurately capture their warming impacts on global atmosphere, particularly in highly polluted regions.

54 ENVIRONMENTAL SCIENCES↗