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At least 1,045 records · Page 58

Distributed optical fibre sensing in physical oceanography: emergence and future prospects

Distributed optical fibre sensing (DOFS) is a technology that enables continuous, real-time measurements of a range of environmental parameters along the length of a fibre optic cable. In this article, we review the recently emerged applications of DOFS techniques in physical oceanography and offer a perspective on the technology's potential for future growth within the field. The introduction of DOFS to physical oceanography is contextualised with a brief history of the technology, which spun off primarily from the use of seafloor-laid optical fibres for telecommunications purposes. The key components and underpinning physics of a DOFS system are outlined and, on their basis, the suite of variables that are observable with DOFS are discussed. The implementation factors of DOFS, which include trade-offs between measurement accuracy and spatio-temporal resolutions and ranges, are also examined. The physical oceanographic applications of DOFS to date are then illustrated with case examples of four distinct DOFS techniques: distributed temperature sensing (DTS), which can provide ocean temperature observations; distributed static strain sensing (DSS) and distributed acoustic sensing (DAS), which are sensitive to temperature, cable strain and strain-associated variables, such as pressure and ocean velocity; and ultra-long-range observations of ocean currents with optical interferometry. The forthcoming prospects of DOFS in physical oceanography are considered, and are proposed to include new fibre optic-based approaches to sense ocean salinity and measure through the water column. We conclude with reflections on the future role of DOFS within the Global Ocean Observing System, and highlight the opportunities provided by the existing world-wide network of seafloor-laid optical fibres.

Naveira Garabato, Alberto C. [Univ. of Southampton↗

Adaptive spectra-to-exposure conversion using ridge regularized polynomial response models

Real-time gamma spectra-to-exposure conversion in aerial and ground monitoring commonly relies on calibration-derived, detector- or system-specific conversion coefficients that are assumed to generalize across operational environments. In practice, deployment specific differences in spectral composition and transport conditions can introduce systematic bias relative to reference instruments, motivating methods that adapt coefficients using minimal field supervision while explicitly limiting overfitting. In this work, we present a conservative coefficient adaptation framework that updates a baseline polynomial energy-weighting function using ridge-regularized regression, with leave-one-out cross-validation (LOOCV) used to select the regularization strength. The findings support ridge-constrained minimal-supervision adaptation as a practical mechanism to suppress site-specific bias without destabilizing a calibration-derived baseline.

61 RADIATION PROTECTION AND DOSIMETRY↗

AI‐Driven Robot Enables Synthesis‐Property Relation Prediction for Metal Halide Perovskites in Humid Atmosphere

Materials Acceleration Platforms (MAPs) – also known as self-driving laboratories– present a new paradigm for materials science and promise an order of magnitude accelerated materials discovery compared to the traditional trial-and-error approach. Metal halide perovskites (MHPs) are an emerging class of materials for optoelectronic applications but are plagued by irreproducible optoelectronic quality, particularly for films fabricated in a humid atmosphere. Here, in this work, a machine learning (ML)-guided closed-loop platform is developed with a multimodal data fusion approach to predict synthesis–property relations for the optical quality of MHP thin films in relative humidities (RHs) ranging from 5–55%. The efficiency of this approach is confirmed by the fast-dropping learning rate to 2% after experimentally sampling less than 1% of the possible 5,000+ combinations. The prediction of synthesis–property relations is done by optical and imaging characterizations. In situ photoluminescence characterization revealed the origin of thin film quality variation at different RH. These insights provide an avenue for controlling the MHP crystallization by fine-tuning the synthesis parameters and RH for a given chemistry, thus lifting the need for stringent atmosphere control. The MAP enables an accelerated screening and understanding of the synthesis design space, facilitating rational synthesis recipe choice for a wide range of materials.

AI-driven robot↗

Hidden Features: How Subsurface and Landscape Heterogeneity Govern Hydrologic Connectivity and Stream Chemistry in a Montane Watershed

ABSTRACT Hydrologic connectivity is defined as the connection among stores of water within a watershed and controls the flux of water and solutes from the subsurface to the stream. Hydrologic connectivity is difficult to quantify because it is goverened by heterogeniety in subsurface storage and permeability and responds to seasonal changes in precipitation inputs and subsurface moisture conditions. How interannual climate variability impacts hydrologic connectivity, and thus stream flow generation and chemistry, remains unclear. Using a rare, four‐year synoptic stream chemistry dataset, we evaluated shifts in stream chemistry and stream flow source of Coal Creek, a montane, headwater tributary of the Upper Colorado River. We leveraged compositional principal component analysis and end‐member mixing to evaluate how seasonal and interannual variation in subsurface moisture conditions impacts stream chemistry. Overall, three main findings emerged from this work. First, three geochemically distinct end members were identified that constrained stream flow chemistry: reach inflows, and quick and slow flow groundwater contributions. Reach inflows were impacted by historic base and precious metal mine inputs. Bedrock fractures facilitated much of the transport of quick flow groundwater and higher‐storage subsurface features (e.g., alluvial fans) facilitated the transport of slow flow groundwater. Second, the contributions of different end members to the stream changed over the summer. In early summer, stream flow was composed of all three end members, while in late summer, it was composed predominantly of reach inflows and slow flow groundwater. Finally, we observed minimal differences in proportional composition in stream chemistry across all four years, indicating seasonal variability in subsurface moisture and spatial heterogeneity in landscape and geologic features had a greater influence than interannual climate fluctuation on hydrologic connectivity and stream water chemistry. These findings indicate that mechanisms controlling solute transport (e.g., hydrologic connectivity and flow path activation) may be resilient (i.e., able to rebound after perturbations) to predicted increases in climate variability. By establishing a framework for assessing compositional stream chemistry across variable hydrologic and subsurface moisture conditions, our study offers a method to evaluate watershed biogeochemical resilience to variations in hydrometeorological conditions.

Johnson, Keira [College of Earth, Ocean, and Atmos↗

The Zooplankton International Geospatial dataset: A global repository of spatiotemporal freshwater zooplankton community composition data from lakes and reservoirs to support ecological research

Zooplankton transfer substantial energy in aquatic food webs and are used as indicators of environmental change. Syntheses of zooplankton community dynamics globally require datasets that span a wide range of environmental gradients; however, these datasets are limited due to methodological differences across programs, taxonomic inconsistencies, and a lack of standardized metadata. To reconcile these challenges, we created the Zooplankton International Geospatial (ZIG) dataset, which includes original zooplankton, water physical and chemical variables, and lake morphometric data from 311 inland lakes and reservoirs. ZIG includes waterbodies ranging in size from 0.005 to 82,100 km2 and spanning broad latitudinal (−47.26 to 64.90) and longitudinal ranges (−165.04 to 176.53). Temporal coverage for individual waterbodies ranges between 1 and 60 yr with sampling frequency ranging from annually to weekly. With its extensive coverage and content, we consider ZIG to be a cornerstone for future investigations of global scale lake biodiversity change.

Figary, Stephanie [Cornell University, Ithaca, NY]↗

Impacts of climate and disturbance on nutrient fluxes and stoichiometry in mixed-conifer forests

Elucidating climatic impacts on stream nutrient export and stoichiometry will improve the understanding of forest carbon (C) storage in a warmer world. We constructed C, nitrogen (N), and phosphorus (P) budgets in four watersheds within a rain-snow transition site and another four within a higher-elevation, snow-dominated site, in California’s mixed-conifer zone. We used these two sites in a space-for-time substitution to assess the potential effects of warming on nutrient cycles in currently snow-dominated areas that will become more rain-dominated. During a non-drought period (water year (WY) 2004 – 2011), mean annual stream exports of C and N in particulate forms at the transition site were double that at the snow-dominated site, suggesting that sediment-associated nutrient losses may increase with warming. The transition site had 12% lower N but double the P content in mineral horizons, lower N:P mass ratios in organic horizons, and lower stream export of dissolved inorganic N than the snow-dominated site. Furthermore, these differences suggest that montane forests may receive lower supply of N relative to P with warming. In addition, given strong interests in forest thinning to increase drought resiliency, we examined changes in stream nutrient export after thinning and during a major drought period (WY 2013 – 2015). Stream exports of C, N, and P were similar between unthinned and thinned watersheds during drought, suggesting negligible thinning impacts on stream nutrient export during excessively dry periods. Taken together, our results suggest that as the climate warms, California’s montane forests may lose more nutrients through erosion and receive less N input than P.

54 ENVIRONMENTAL SCIENCES↗

The Median Isn’t the Message: soil nutrient hot spots have a disproportionate influence on biogeochemical structure across years, seasons, and depths

Abstract Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO 3 − and Na + . Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for PO 4 3− NH 4 + , and NO 3 − , and were more transient for Ca 2+ , Mg 2+ , and Na + . Sampling year (annual precipitation ranged from 558 to 1223 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO 4 3− , NH 4 + , NO 3 − , and Na + , with HSs forming more often after fall rains than after spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56–88% of PO 4 3− , NH 4 + , and NO 3 − resin fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models. Graphical abstract

54 ENVIRONMENTAL SCIENCES↗

Risk of Mortality in Family Members of Men Seeking Fertility Assessment

Objective: To assess mortality in family members of men seeking fertility assessment. Subfertility serves as a biomarker for overall somatic health, and poor semen quality is associated with increased risk of hospitalization and mortality from chronic conditions. However, it is unclear if these risks extend to family members of men with low sperm count. Design: Retrospective cohort study. Subjects: Family members, up to third-degree relatives, of men in the Subfertility, Health and Assisted Reproduction and the Environment cohort who underwent a semen analysis as part of a fertility assessment 1996–2017. Relatives of men with a recorded total sperm count who lived in Utah for ≥1 year 1904–2017 were included in the analysis (N = 22,280 families). Exposure: Individuals were classified by family membership. Families were classified as relatives of azoospermic (0M), oligozoospermic (<39M), or normozoospermic (≥39M) men. The average total sperm count of the proband (male relative) with fertility assessment was also included as a continuous exposure measure. Main Outcome Measures: The main outcomes were all-cause and cause-specific mortality risk by sex, age, and degree of relation: first-, second-, and third-degree. Cox proportional hazard models were used to test the association between fertility classification and mortality, controlling for sex, race/ethnicity, and birth year. Results: A total of 666,437 relatives of men with fertility assessment (N deaths = 183,974) were included in the analysis. Relative to normozoospermia families, all-cause mortality risk increased in oligozoospermia families (hazard ratio [HR] oligozoospermia , 1.03; 95% confidence interval [CI], 1.01–1.05). Close relatives, first- (HR oligozoospermia , 1.17; 95% CI, 1.07–1.28) and second-degree relatives (HR azoospermia , 1.11; 95% CI, 1.04–1.20; HR oligozoospermia , 1.05; 95% CI,1.01–1.09), of azoospermic and oligozoospermic men had the highest all-cause and cause-specific mortality risk, including death attributed to cardiovascular disease or congenital birth conditions. Conclusion: Our results suggest that familial all-cause and cause-specific mortality risk differ by fertility phenotype. Families of azoospermic and oligozoospermic men showed significantly increased risk, particularly for close relatives. This study provides further evidence that shared genetic and/or environmental factors could influence both fertility and somatic health.

Male fertility↗

Modulation of thermal conductivity of iron-doped ß-Ga2O3 by helium-ion irradiation

This study examines the impact of helium-ion irradiation on the thermal conductivity of ß-Ga2O3. A laser-based spatial domain thermoreflectance technique is used to investigate thermal conductivity map for both un-irradiated and irradiated ß-Ga2O3, which are then validated against simulation results derived from density functional theory-based phonon transport simulations. Since helium bubble evolution was ob- served at the nanoscale using transmission electron microscopy, the simulation study was carried out on eight distinct helium-induced sites in ß-Ga2O3. Our findings indicate a reduction in thermal conductivity for the irradiated samples. Experimental results show a significant reduction in thermal conductivity in irradiated samples, with de- creases of approximately 25% along the [100] direction and 40% along [001] directions. Phonon transport simulations closely replicate these findings, particularly when helium occupying interstitial sites, predicting reductions of ˜53% along [100] and ˜50% along [001] directions. This work underscores the role of irradiation-induced microstructural changes in the heat transport properties of ß-Ga2O3 which is crucial for its application in sensor devices in extreme environments.

36 - MATERIALS SCIENCE↗

Precious metal oxygen-evolving anodes for electrolytic reduction of metal oxides in molten LiCl-Li 2 O electrolyte

Understanding the electrochemical stability of oxygen-evolving anode materials in molten salt electrolytes is essential to enable decarbonized electrolytic reduction of metal oxides (e.g., used nuclear oxide fuels). Here, this work investigated three precious metals (Ir, Ru, and Pt) as oxygen-evolving anodes in molten LiCl-Li 2 O (99.0-1.0 wt%) at 650 °C. For consistent measurements, this work employed a three-electrode cell comprised of a two-phase Li-Bi (65-35 at%) reference electrode and a NiO counter electrode. Anodic polarization behavior of each anode was investigated via cyclic voltammetry (CV) and chronoamperometry. The onset potential for oxygen evolution was observed at E > 2.9 V (vs. Li/Li + ) for the Ir and Ru anodes and anodic current density was as high as 1.0 A cm -2 at 3.23 V. The dimensional stability of each anode was evaluated from long-term electrolysis experiments (10.0-32.1 h) at 3.23 V. Rapid consumption of the Pt anode was observed after the application of 26,453 C cm -2 with a reduction in diameter of about 15.8% due to the formation of a non-protective Li 2 PtO 3 compound. The formation of this compound was also observed during CV measurements as additional anodic waves at potentials more negative than that of oxygen evolution. In contrast, both the Ir and Ru anodes exhibited excellent dimensional stability with a reduction in diameter or thickness of less than 1.5% even after applying greater charge density of ~41,100 C cm -2 , demonstrating superior stability during oxygen evolution in the LiCl-Li 2 O electrolyte.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analytical workflow dependence of experimental observables for uranium chemistries

In this work, we investigated how the sequencing of laboratory analytical methods used for chemical and morphological characterization influences analytical findings for particulate materials relevant to the nuclear fuel cycle, including UO2, U3O8, studtite (UO2O2·4H2O), and β-UO3, in the context of nuclear forensic analysis. Particles of each chemistry obtained from consistent production batches were exposed to Raman spectroscopy and scanning electron microscopy in varying orders to elucidate how the order in which the techniques are applied influences morphological and chemical observations as a function of particle size. The results indicate that particles from all four chemistries exposed to high-resolution electron imaging before Raman spectral analysis demonstrate optical vibrational spectral changes that reduce accurate interpretation of the underlying chemistry via Raman spectral analysis. We hypothesize that these changes are due to the thermal load of the electron beam imparted to the sample being unable to be dissipated by materials with poor thermal conduction properties. Results from this study will aid in determining best practices for forensic analysis procedures to reduce uncertainty in chemical determination of unknown particulate samples.

Manns, Rebecca [University of Nevada, Las Vegas]↗