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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗
NASA NTRSDate not supplied

Additional Characterization of Sonoran Pics in Support of A Stable Multi-Sensor Geostationary Imager Record

The Sonoran Desert is the most utilized Pseudo Invariant Calibration Site (PICS) located in the Americas for post-launch radiometer drift monitoring and sensor pair radiometric scaling. The Sonoran Desert is located near the US Arizona and Mexican border with an elevation of 37 m. The site has small spatial and angular variations; however, soil moisture can cause short- term periodic reflectance fluctuations. The NASA Clouds and the Earth’s Radiant Energy System (CERES) project utilizes the site to validate the GOES East and West imager calibration coefficients derived from inter-calibrating GOES with MODIS. Because the daily local noon angular solar and viewing angles repeat every year over the site, a daily exoatmospheric radiance model (DERM) can be constructed over the lifetime of a well-calibrated GOES sensor. DERM based on a well-calibrated GOES imager can then be used to determine the calibration coefficients of successive GOES imagers to provide a stable multi-sensor GOES imager record. This will ensure that the GOES retrieved clouds and derived broadband fluxes can be used to infer the regional diurnal cycle in between Terra and Aqua CERES measurements to accurately compute the daily mean regional fluxes and clouds over the 20-year CERES SYN1deg product. Although the Sonoran Desert surface reflectance and atmospheric column vary seasonally, the inter-annual variability of the seasonal cycle is small, but it adds noise to the resulting DERM calibration coefficients. We seek to reduce the uncertainty of the DERM approach by improving the clear-sky filtering and correlating the observed interannual reflectance variability with atmospheric parameters, such as precipitable water, ozone concentration, and aerosol optical depth. The additional characterization of the Sonoran Desert site DERM for both the GOES East and West positions should improve the accuracy of the CERES SYN1deg product clouds and fluxes.

Prathana Khakurel↗
DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Mars 2020 Site-Specific Mission Performance Analysis: Part 2. Surface Traversability

The Mars 2020 Rover Mission (M2020) is characterized by long-range traverses between scientific Regions Of Interest (ROIs), as well as the demanding requirement on the distance and time for the inter-ROI traverses. As a result, surface traversability is one of the major driving factors for the landing site selection of M2020. With the newly developed Mars Terrain Traversability analysis Tools (MTTT), we performed traversability analysis of the eight candidate landing sites with an unprecedented granularity. This paper describes the MTTT analysis capabilities, as well as how the MTTT capabilities were used to down-select from eight to three candidate landing sites for further evaluation.

Milkovich, Sarah↗
NASA NTRS2019

Identification of Absorbing Aerosol Types at a Site in the Northern Edge of Indo-Gangetic Plain and a Polluted Valley in the Foothills of the Central Himalayas

Identification of atmospheric aerosol types and characterization of absorbing aerosols, based on AErosol RObotic NETwork (AERONET) data collected during 2013–2014 over two sites in Nepal: Lumbini in the northernmost part of central Indo-Gangetic Plain (IGP) and Kathmandu Valley in foothills of the central Himalayas, have been conducted in the present study. The relationship between four aerosol parameters; Extinction Angstrom Exponent (EAE), Absorption Angstrom Exponent (AAE), Single Scattering Albedo (SSA) and Real Refractive Index (RRI) was analyzed to study the aerosol types. This resulted in the identification of two types of aerosols concerning their origin: biomass burning and urban/industrial mix. Furthermore, to understand the absorbing aerosol types, the relationship between aerosol size parameters; Fine Mode Fraction (FMF) and Angstrom Exponent (AE), and aerosol absorption characteristics; SSA and AAE were investigated. In regards to the absorbing aerosol types, ‘Mostly BC’ was the dominant absorbing aerosol, over both sites, with comparatively negligible contribution from other absorbing aerosol types such as dust. The aerosol subtypes obtained from satellite-borne CALIPSO instrument supported the results derived from the AERONET data. The CALIPSO images also indicated that the aerosols over the foothills of the Himalayas could extend to the height of >5 km above the ground, which could be transported towards the Himalayan and Tibetan Plateau (HTP) region with sensitive ecosystems. The multi-sites based study of long-term records is required to elucidate the nature and trends of aerosols in the HTP region and any perturbation to the atmospheric environment and other environments in this region.

Aerosol types↗
DOE OSTI2026

Rational design of heterogeneous single-site catalysts via surface organometallic chemistry

Single-site heterogeneous catalysts offer an attractive route to unite the molecular precision of homogeneous catalysis with the durability and practical advantages of solids. Surface organometallic chemistry (SOMC) provides a particularly powerful strategy for this purpose by grafting molecular precursors onto tailored surfaces and converting support functionalities into ligand environments for isolated metal centers. As a result, SOMC brings the language and logic of coordination chemistry to heterogeneous catalysis, where the support becomes an integral part of the active site coordination sphere. This Review surveys recent progress in the rational design of SOMC-derived single-site catalysts, with emphasis on synthetic routes, post synthetic transformations, and the deliberate tuning of catalytic behavior through metal-support interactions. Discussions are made on how support identity, hydroxyl topology, acidity, and redox activity shape the geometry, electronic structure, and oxidation state of supported metal sites, as well as how these factors determine activity, selectivity, and stability. We also examine a central limitation of these systems: despite their molecularly informed design, supported single sites often exist as structurally distributed ensembles rather than uniform species, particularly on amorphous supports. This site heterogeneity, along with catalyst dynamics under operating conditions, remains a major barrier to definitive structure-activity relationships. Therefore, emerging approaches that combine advanced characterization, first-principles modeling, ensemble kinetics, and machine learning to resolve active-site structure and guide catalyst development are highlighted. Together, these advances position SOMC as a versatile coordination chemistry framework for the predictive design of heterogeneous catalysts with well-defined molecularly tailored active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Bis(imidazole)-based cysteine labeling tool for metalloprotein assembly

Precise metal-protein coordination by design remains a considerable challenge. Polydentate, high-metal-affinity protein modifications, both chemical and recombinant, can enable metal localization. However, these constructs are often bulky, conformationally and stereochemically ill-defined, or coordinately saturated. Here, we expand the biomolecular metal-coordination toolbox with the irreversible attachment to cysteine of bis(1-methylimidazol-2-yl)ethene (“BMIE”), which generates a compact imidazole-based metal-coordinating ligand. Conjugate additions of small-molecule thiols (thiocresol and N-Boc-Cys) with BMIE confirm general thiol reactivity. The BMIE adducts are shown to complex the divalent metal ions Cu ++ and Zn ++ in bidentate (N 2 ) and tridentate (N 2 S*) coordination geometries. Cysteine-targeted BMIE modification (>90% yield at pH 8.0) of a model protein, the S203C variant of carboxypeptidase G2 (CPG2), measured with ESI-MS, confirms its utility as a site-selective bioconjugation method. ICP-MS analysis confirms mono-metallation of the BMIE-modified CPG2 protein with Zn ++ , Cu ++ , and Co ++ . EPR characterization of the BMIE-modified CPG2 protein reveals the structural details of the site selective 1:1 BMIE-Cu ++ coordination and symmetric tetragonal geometry under physiological conditions and in the presence of various competing and exchangeable ligands (H 2 O/HO – , tris, and phenanthroline). An X-ray protein crystal structure of BMIE-modified CPG2-S203C demonstrates that the BMIE modification is minimally disruptive to the overall protein structure, including the carboxypeptidase active sites, although Zn ++ metalation could not be conclusively discerned at the resolution obtained. The carboxypeptidase catalytic activity of BMIE-modified CPG2-S203C was also assayed and found to be minimally affected. Finally, these features, combined with ease of attachment, define the new BMIE-based ligation as a versatile metalloprotein design tool, and enable future catalytic and structural applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Results from the Deep Convective Clouds-Based Response Versus Scan-Angle Characterization for the MODIS Reflective Solar Bands

The Terra and Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) scan mirror reflectance is a function of the angle of incidence (AOI) and was characterized prior to launch by the instrument vendor. The relative change of the prelaunch response versus scan angle (RVS) is tracked and linearly scaled on-orbit using observations at two AOIs of 11.2° and 50.2° corresponding to the moon view and solar diffuser, respectively. As the missions continue to operate well beyond their design life of six years, the assumption of linear scaling between the two AOIs is known to be inadequate in accurately characterizing the RVS, particularly at short wavelengths. Consequently, an enhanced approach of supplementing the on-board measurements with response trends from desert pseudoinvariant calibration sites (PICS) was formulated in MODIS Collection 6 (C6). An underlying assumption for the continued effectiveness of this approach is the long-term (multiyear) and short-term (month to month) stability of the PICS. Previous work has shown that the deep convective clouds (DCC) can also be used to monitor the onorbit RVS performance with less trend uncertainties compared with desert sites. In this paper, the raw sensor response to the DCC is used to characterize the on-orbit RVS on a band and mirror-side basis. These DCC-based RVS results are compared with those of C6 PICS-based RVS, showing an agreement within 2% observed in most cases. The pros and cons of using a DCC-based RVS approach are also discussed in this paper. Although this reaffirms the efficacy of the C6 PICS-based RVS, the DCC-based RVS approach presents itself as an effective alternative for future considerations. Potential applications of this approach to other instruments, such as Suomi National Polarorbiting Partnership, Joint Polar Satellite Systems, and Visible Infrared Imaging Radiometer Suite, are also discussed.

Angal, Amit↗
DOE OSTI2023

Review of Carbon Support Coordination Environments for Single Metal Atom Electrocatalysts (SACS)

This topical review focuses on the distinct role of carbon support coordination environment of single-atom catalysts (SACs) for electrocatalysis. The article begins with an overview of atomic coordination configurations in SACs, including a discussion of the advanced characterization techniques and simulation used for understanding the active sites. A summary of key electrocatalysis applications is then provided. These processes are oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), nitrogen reduction reaction (NRR), and carbon dioxide reduction reaction (CO 2 RR). The review then shifts to modulation of the metal atom-carbon coordination environments, focusing on nitrogen and other non-metal coordination through modulation at the first coordination shell and modulation in the second and higher coordination shells. Representative case studies are provided, starting with the classic four-nitrogen-coordinated single metal atom (M$-$N 4 ) based SACs. Bimetallic coordination models including homo-paired and hetero-paired active sites are also discussed, being categorized as emerging approaches. The theme of the discussions is the correlation between synthesis methods for selective doping, the carbon structure–electron configuration changes associated with the doping, the analytical techniques used to ascertain these changes, and the resultant electrocatalysis performance. In conclusion, critical unanswered questions as well as promising underexplored research directions are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Counter-Intuitive Structural Instability Aroused by Transition Metal Migration in Polyanionic Sodium Ion Host

The structure of polyanionic materials is conventionally known to be free of transition metal migration and structurally stable when storing/releasing sodium ions. Herein, the observation of enhanced cycling stability of a typical polyanionic cathode, Na 3 VCr(PO 4 ) 3 (NVCP) at lower temperature (-15 degrees C vs 30 degrees C), triggers the exploration of its structural origins with a surprising finding that the migratable nature of vanadium in NVCP leads to detrimental structural degradation of the polyanionic host upon cycling. The correlation between long range and short range structural change associated with this atomic migration is established via a strong combination of various in situ/ex situ characterization tools, revealing the essential V-to-Na1 site migration. Such transition metal migration is effectively suppressed when V atoms are pinned to their original position in the lattice by lowering the temperature. More importantly and practically, a room temperature-based deep sodiation strategy is further developed to recover the structure. Overall, this work challenges the long-standing assumption of the stability of the polyanionic framework structure and calls for urgent attention to the structural understanding of the NVCP system as well as strategy development for property enhancement.

25 ENERGY STORAGE↗
DOE OSTI2024

Soil water percolation and nutrient fluxes as a function of topographical, seasonal and soil texture variation in Central Amazonia, Brazil

Abstract Understanding soil water dynamics and transport of nutrients is challenging in tropical rainforests due to the uniqueness of several properties related to soils, vegetation and seasonality that make relating patterns found in temperate environments to tropical sites difficult. We address the need for better edaphic characterization in tropical environments by investigating soil water percolation rates and chemistry across topographic, soil texture and seasonal gradients in a mature tropical rainforest in Central Amazonia, Brazil. We utilized a passive wick flux meter (e.g., drainage lysimeter) to directly measure real‐time percolation fluxes at 60‐cm depth, and to sample a suite of chemical species across plateau, slope and valley topographic positions. We found percolation flux volume and chemical exports generally increase with decreasing elevation and clay content, which was lowest in the valley. Daily percolation flux was observed to be 2.39 ± 0.44 in plateau, 3.01 ± 0.50 in slope and 6.16 ± 0.83 mm in valley. Most solutes were present in small amounts of <1 mg L −1 , such as PO₄ 3− , Fe 2+ /Fe 3+ and Mn 2+ ; however, NO 3 − concentrations were >20 mg L −1 , even exceeding 100 mg L −1 in the valley. Based on additional isotopic analysis, we speculate high NO 3 − concentrations are partially an artefact of root decomposition following installation of the flux meters. The empirical relationships we show among percolation volume and nutrient exports under varying topographies and soil textures can improve Earth System Model performance by better constraining ecohydrological relationships to nutrient fluxes, which can in‐turn better illuminate the important factors that govern their behaviour.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hydrogen adsorption and transport in clay-rich geomaterials: Implications for large-volume underground hydrogen storage

Depleted oil and gas reservoirs, characterized by impermeable clay-rich caprocks, are promising sites for large-scale underground hydrogen storage (UHS), which is a key strategy to support hydrogen-based energy systems. However, experimental data on hydrogen storage in clay-rich geomaterials remain scarce. In this work, we experimentally investigated hydrogen adsorption and migration in clay-rich geomaterials in the presence of nitrogen and water under controlled temperatures. Experimental observations showed that hydrogen was adsorbed in dry illite. A dual-porosity transport model was developed to interpret hydrogen transport between large-pore and small-pore domains in illite. The large-pore domain is the space between clay particles (i.e., inter-particle space), whereas the small-pore domain is the nanoscale pore space between clay mineral layers (i.e., inter-layer or intra-particle space). In contrast, nitrogen showed no evidence of adsorption in dry illite because it cannot move into the small-pore domain due to the relatively large kinetic diameter, referred to as the molecular sieving effect. Here, we found that 0.7–1.3 nm is the length scale regulating this molecular sieving effect, matching the interlayer spacing in illite, suggesting that nitrogen is a promising cushion gas in UHS, which aims to maintain adequate pressure in the reservoir for economic operations. In wetted illite, hydrogen was not adsorbed into the interlayer space due to the occupation of adsorption sites by interlayer water, which highlights the critical role of the clay hydration state in controlling hydrogen-clay interactions. Additionally, hydrogen adsorption experiments on crushed shale indicated that the shale surface possessed adsorption sites more favorable for hydrogen than for nitrogen. Through these experiments, we provide new insights into hydrogen storage mechanisms in clay-rich geomaterials and offer valuable laboratory data for evaluating the performance of large-scale UHS systems.

Adsorption↗
DOE OSTI2025

Facile Solvent-Free Synthesis of Manganese Nickel-Layered Double Hydroxide for Sustainable Water-Splitting Applications

The quest for efficient and sustainable water-splitting electrocatalysts has led to the development of a novel bifunctional material, manganese nickel-layered double hydroxide (MnNi-LDH), which demonstrates promising performance for both the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Although manganese-based materials are less explored than other transition metals, they offer significant potential owing to their widespread availability, affordability, and customizable electronic characteristics. MnNi-LDH exhibits a nanosheet morphology and a layered structure, which collectively provide numerous accessible active sites and facilitate efficient charge transfer and mass transport. Characterization using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy, and transmission electron microscopy reveals the structural and compositional properties of MnNi-LDH. The oxidation states of Mn and Ni, as determined by XPS, play a crucial role in improving the catalytic activity. Notably, MnNi-LDH demonstrates low overpotentials of 187 mV for OER and 225 mV for HER at 10 mA/cm 2 current density comparable to conventional catalysts. Long-term stability tests show minimal degradation in cell performance over 50 h, with a current density drop of only 0.6153% per hour for the OER and 0.37% per hour for the HER. Further, these findings highlight the potential of MnNi-LDH as a promising and environmentally friendly bifunctional electrocatalyst for water splitting, contributing to the advancement of renewable energy sources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Node-Accessible Zirconium MOFs

High-stability, zirconium-based metal–organic frameworks are attractive as heterogeneous catalysts and as model supports for uniform arrays of subsequently constructed heterogeneous catalysts—for example, MOF-node-grafted metal–oxy and metal–sulfur clusters. For hexa-Zr(IV)-MOFs characterized by nodes that are less than 12-connected, sites not used for linkers are ideally occupied by reactive and displaceable OH/H 2 O pairs. Here, the desired pairs are ideal for grafting the aforementioned catalytic clusters, while aqua-ligand lability renders them effective for exposing highly Lewis-acidic Zr(IV) sites (catalytic sites) to candidate reactants. New single-crystal X-ray studies of an eight-connected Zr-MOF, NU-1000, reveal that conventional activation fully removes modulator ligands, but replaces them with three node-blocking formate ligands (from solvent decomposition) and only one OH/H 2 O pair, not four—a largely overlooked complication that now appears to be general for Zr-MOFs. Here we describe an alternative activation protocol that effectively removes modulators, avoids formate, and installs the full complement of terminal OH/H 2 O pairs. It does so via an unusual isolatable intermediate featuring eight aqua ligands and four non-ligated chlorides—again as supported by single-crystal X-ray data. We find that complete replacement of node-blocking modulators/formate with the originally envisioned OH/OH 2 pairs has striking consequences; here we touch upon just three. First, elimination of unrecognized formate renders aqua ligands much more thermally labile, enabling open Zr(IV) sites to be obtained at lower temperature. Second, in the absence of formate, which otherwise links and locks pairs of node Zr(IV) ions, reversible removal of aqua ligands engenders reversible contraction of MOF meso- and micropores, as evidenced by X-ray diffraction. Third, formate replacement with OH/OH 2 pairs renders NU-1000 ca.10× more active for catalytic hydrolytic degradation of a representative simulant of G-type chemical warfare agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Application of machine learning to discover new intermetallic catalysts for the hydrogen evolution and the oxygen reduction reactions

The adsorption energies for hydrogen, oxygen, and hydroxyl were calculated by means of density functional theory on the lowest energy surface of 24 pure metals and 332 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B taking into account the effect of biaxial elastic strains. This information was used to train two random forest regression models, one for the hydrogen adsorption and another for the oxygen and hydroxyl adsorption, based on 9 descriptors that characterized the geometrical and chemical features of the adsorption site as well as the applied strain. All the descriptors for each compound in the models could be obtained from physico-chemical databases. The random forest models were used to predict the adsorption energy for hydrogen, oxygen, and hydroxyl of ≈2700 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B made of metallic elements, excluding those that were environmentally hazardous, radioactive, or toxic. This information was used to search for potential good catalysts for the HER and ORR from the criteria that their adsorption energy for H and O/OH, respectively, should be close to that of Pt. Further, this investigation shows that the suitably trained machine learning models can predict adsorption energies with an accuracy not far away from density functional theory calculations with minimum computational cost from descriptors that are readily available in physico-chemical databases for any compound. Moreover, the strategy presented in this paper can be easily extended to other compounds and catalytic reactions, and is expected to foster the use of ML methods in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Constraints on neutrino emission from nearby galaxies using the 2MASS redshift survey and IceCube

The distribution of galaxies within the local universe is characterized by anisotropic features. Observatories searching for the production sites of astrophysical neutrinos can take advantage of these features to establish directional correlations between a neutrino dataset and overdensities in the galaxy distribution in the sky. The results of two correlation searches between a seven-year time-integrated neutrino dataset from the IceCube Neutrino Observatory, and the 2MASS Redshift Survey (2MRS) catalog are presented here. The first analysis searches for neutrinos produced via interactions between diffuse intergalactic Ultra-High Energy Cosmic Rays (UHECRs) and the matter contained within galaxies. The second analysis searches for low-luminosity sources within the local universe, which would produce subthreshold multiplets in the IceCube dataset that directionally correlate with galaxy distribution. No significant correlations were observed in either analyses. Herein, constraints are presented on the flux of neutrinos originating within the local universe through diffuse intergalactic UHECR interactions, as well as on the density of standard candle sources of neutrinos at low luminosities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Performance of a phonon-mediated kinetic inductance detector at the NEXUS cryogenic facility

Microcalorimeters that leverage microwave kinetic inductance detectors to read out phonon signals in the particle-absorbing target, referred to as kinetic inductance phonon-mediated (KIPM) detectors, offer an attractive detector architecture to probe dark matter (DM) down to the fermionic thermal relic mass limit. A prototype KIPM detector featuring a single aluminum resonator patterned onto a 1-gram silicon substrate was operated in the Northwestern EXerimental Underground Site (NEXUS) low-background facility at Fermilab for characterization and evaluation of this detector architecture’s efficacy for a DM search. An energy calibration was performed by exposing the bare substrate to a pulsed source of 470-nm photons, resulting in a baseline resolution on the energy absorbed by the phonon sensor of 2.1 ± 0.2 eV, a factor of two better than the current state of the art, enabled by quasiparticle lifetimes extending up to 6.5 ms. However, due to the subpercent phonon collection efficiency, the resolution on energy deposited in the substrate is limited to σ E = 318 ± 29 eV. We further model both the signal pulse shape as a function of device temperature to extract quasiparticle lifetimes, and the observed noise spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗