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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impacts of directed evolution and soil management legacy on the maize rhizobiome

Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Fabrication of GRCop-84 Rocket Thrust Chambers

GRCop-84, a copper alloy, Cu-8 at% Cr-4 at% Nb developed at NASA Glenn Research Center for regeneratively cooled rocket engine liners has excellent combinations of elevated temperature strength, creep resistance, thermal conductivity and low cycle fatigue. GRCop-84 is produced from prealloyed atomized powder and has been fabricated into plate, sheet and tube forms as well as near net shapes. Fabrication processes to produce demonstration rocket combustion chambers will be presented and includes powder production, extruding, rolling, forming, friction stir welding, and metal spinning. GRCop-84 has excellent workability and can be readily fabricated into complex components using conventional powder and wrought metallurgy processes. Rolling was examined in detail for process sensitivity at various levels of total reduction, rolling speed and rolling temperature representing extremes of commercial processing conditions. Results indicate that process conditions can range over reasonable levels without any negative impact to properties.

Loewenthal, William S.↗
DOE OSTI2020

Modeling the processes of soil moisture in regulating microbial and carbon-nitrogen cycling

Soil carbon (C) and nitrogen (N) cycles and their complex responses to hydro-climatic forcing have gained increasing attention. While the temperature effects have been intensively studied, soil moisture response functions (SMRFs) are not well documented for various microbial and enzymatic processes due to the difficulties in directly measuring and differentiating the moisture effects on various processes. In this work we extended our C-only Microbial-ENzyme Decomposition (MEND) model to the C-N coupled MEND model with flexible element stoichiometry. Our model calibration showed good agreement between simulated and observed C:N ratios in soil organic matter and microbial biomass, as well as the ammonium and nitrate concentrations. We show that the selection of SMRFs for specific biogeochemical processes could result in significant differences in model simulated microbial and C-N processes. In particular, it is essential to account for the soil moisture effects on microbial dormancy and resuscitation, as the changes in microbial physiology under favorable or stressful conditions will exert strong controls on soil C and N dynamics. We also advocate the utilization of dynamic (time-variant) data (e.g., litter input, N deposition, soil temperature and moisture), instead of time-invariant data, to drive model simulations and analyses. Dynamic forcing data (particularly dynamic soil moisture) better represent the real-world climate and environmental conditions, which could facilitate more realistic modeling and understanding of soil C and nutrient cycling in a changing world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep learning of experimental electrochemistry for battery cathodes across diverse compositions

Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. Here, we present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.

25 ENERGY STORAGE↗
DOE OSTI2022

Xanthophyll-cycle based model of the rapid photoprotection of Nannochloropsis in response to regular and irregular light/dark sequences

We explore the photoprotection dynamics of Nannochloropsis oceanica using time-correlated single photon counting under regular and irregular actinic light sequences. The varying light sequences mimic natural conditions, allowing us to probe the real-time response of non-photochemical quenching (NPQ) pathways. Durations of fluctuating light exposure during a fixed total experimental time and prior light exposure of the algae are both found to have a profound effect on NPQ. These observations are rationalized with a quantitative model based on the xanthophyll cycle and the protonation of LHCX1. The model is able to accurately describe the dynamics of non-photochemical quenching across a variety of light sequences. The combined model and observations suggest that the accumulation of a quenching complex, likely zeaxanthin bound to a protonated LHCX1, is responsible for the gradual rise in NPQ. Additionally, the model makes specific predictions for the light sequence dependence of xanthophyll concentrations that are in reasonable agreement with independent chromatography measurements taken during a specific light/dark sequence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

Mid- and far-infrared spectroscopic studies of the influence of temperature, ultraviolet photolysis and ion irradiation on cosmic-type ices

Infrared (IR) studies of laboratory ices can provide information on the evolution of cosmic-type ices as a function of different simulated space environments involving thermal, ultraviolet (UV), or ion processing. Laboratory radiation experiments can lead to the formation of complex organic molecules. However, because of our lack of knowledge about UV photon and ion fluxes, and exposure lifetimes, it is not certain how well our simulations represent space conditions. Appropriate laboratory experiments are also limited by the absence of knowledge about the composition, density, and temperature of ices in different regions of space. Our current understanding of expected doses due to UV photons and cosmic rays is summarized here, along with an inventory of condensed-phase molecules identified on outer solar system surfaces, comets and interstellar grains. Far-IR spectra of thermally cycled H2O are discussed since these results reflect the dramatic difference between the amorphous and crystalline phases of H2O ice, the most dominant condensed-phase molecule in cosmic ices. A comparison of mid-IR spectra of products in proton-irradiated and UV-photolyzed ices shows that few differences are observed for these two forms of processing for the simple binary mixtures studied to date. IR identification of radiation products and experiments to determine production rates of new molecules in ices during processing are discussed. A new technique for measuring intrinsic IR band strengths of several unstable molecules is presented. An example of our laboratory results applied to Europa observations is included.

Spectrophotometry, Infrared/methods↗
NASA NTRS2026

Radiation-Conditioned Ti–hBN Coatings for Space Mechanisms: Bridging Tribology and Irradiation Effects from Laboratory to Low-Earth Orbit

The longevity of tribological components in extraterrestrial environments is challenged by abrasive regolith, extreme temperatures, and ionizing radiation. This study evaluates the performance of vacuum plasma sprayed (VPS) Ti-2vol.% hexagonal boron nitride (hBN) coatings applied to joint mechanisms such as rod and slot, ball and socket, and hinge assemblies, fabricated from Al6061 and Ti6Al4V for planetary structures. Coated and uncoated samples were tested under vacuum with lunar regolith simulant (JSC-1A), followed by environmental exposures including electron radiation and thermal cycling. Results show that coated samples consistently outperformed uncoated counterparts across all configurations. Wear depth in coated components was reduced by over 80%, as confirmed by 3D profilometry and surface imaging. SEM analysis revealed severe abrasion and localized plastic deformation in uncoated surfaces, while coated samples retained structural integrity due to synergy of hard protective phases formed during deposition and retained hBN providing solid lubrication in the sliding surface. Coated and exposed samples exhibited smoother actuation profiles and reduced friction, indicating a beneficial "conditioning" effect from environmental exposure. The coatings-maintained performance even on complex geometries with minimal delamination. These findings demonstrate the potential of VPS Ti-hBN coatings to extend the operational life of lunar mechanisms, bridging laboratory-scale tribology with flight-relevant mechanical applications.

tribology↗
DOE OSTI2021

Bacterial response to spatial gradients of algal-derived nutrients in a porous microplate

Abstract Photosynthetic microalgae are responsible for 50% of the global atmospheric CO2 fixation into organic matter and hold potential as a renewable bioenergy source. Their metabolic interactions with the surrounding microbial community (the algal microbiome) play critical roles in carbon cycling, but due to methodological limitations, it has been challenging to examine how community development is influenced by spatial proximity to their algal host. Here we introduce a copolymer-based porous microplate to co-culture algae and bacteria, where metabolites are constantly exchanged between the microorganisms while maintaining physical separation. In the microplate, we found that the diatom Phaeodactylum tricornutum accumulated to cell abundances ~20 fold higher than under normal batch conditions due to constant replenishment of nutrients through the porous structure. We also demonstrate that algal-associated bacteria, both single isolates and complex communities, responded to inorganic nutrients away from their host as well as organic nutrients originating from the algae in a spatially predictable manner. These experimental findings coupled with a mathematical model suggest that host proximity and algal culture growth phase impact bacterial community development in a taxon-specific manner through organic and inorganic nutrient availability. Our novel system presents a useful tool to investigate universal metabolic interactions between microbes in aquatic ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Flexible control techniques for a lunar base

The fundamental elements found in every terrestrial control system can be employed in all lunar applications. These elements include sensors which measure physical properties, controllers which acquire sensor data and calculate a control response, and actuators which apply the control output to the process. The unique characteristics of the lunar environment will certainly require the development of new control system technology. However, weightlessness, harsh atmospheric conditions, temperature extremes, and radiation hazards will most significantly impact the design of sensors and actuators. The controller and associated control algorithms, which are the most complex element of any control system, can be derived in their entirety from existing technology. Lunar process control applications -- ranging from small-scale research projects to full-scale processing plants -- will benefit greatly from the controller advances being developed today. In particular, new software technology aimed at commercial process monitoring and control applications will almost completely eliminate the need for custom programs and the lengthy development and testing cycle they require. The applicability of existing industrial software to lunar applications has other significant advantages in addition to cost and quality. This software is designed to run on standard hardware platforms and takes advantage of existing LAN and telecommunications technology. Further, in order to exploit the existing commercial market, the software is being designed to be implemented by users of all skill levels -- typically users who are familiar with their process, but not necessarily with software or control theory. This means that specialized technical support personnel will not need to be on-hand, and the associated costs are eliminated. Finally, the latest industrial software designed for the commercial market is extremely flexible, in order to fit the requirements of many types of processing applications with little or no customization. This means that lunar process control projects will not be delayed by unforeseen problems or last minute process modifications. The software will include all of the tools needed to adapt to virtually any changes. In contrast to other space programs which required the development of tremendous amounts of custom software, lunar-based processing facilities will benefit from the use of existing software technology which is being proven in commercial applications on Earth.

Kraus, Thomas W.↗
NASA NTRS2006

Fabrication of GRCop-84 Rocket Thrust Chambers

GRCop-84, a copper alloy, Cu-8 at% Cr-4 at% Nb developed at NASA Glenn Research Center for regenerative1y cooled rocket engine liners has excellent combinations of elevated temperature strength, creep resistance, thermal conductivity and low cycle fatigue. GRCop-84 is produced from pre-alloyed atomized powder and has been fabricated into plate, sheet and tube forms as well as near net shapes. Fabrication processes to produce demonstration rocket combustion chambers will be presented and includes powder production, extruding, rolling, forming, friction stir welding, and metal spinning. GRCop-84 has excellent workability and can be readily fabricated into complex components using conventional powder and wrought metallurgy processes. Rolling was examined in detail for process sensitivity at various levels of total reduction, rolling speed and rolling temperature representing extremes of commercial processing conditions. Results indicate that process conditions can range over reasonable levels without any negative impact to properties.

Loewenthal, William↗
DOE OSTI2026

Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗
DOE OSTI2023

NOTCH EFFECT ON CREEP-FATIGUE BEHAVIOR OF ALLOY 617 AT ELEVATED TEMPERATURE

High-temperature reactor structural components are often under the complex multiaxial creep-fatigue (CF) loading conditions throughout the lifetime because of geometric and/or metallurgical discontinuities and complex loading paths. To assess the multiaxial CF deformation behavior and to evaluate the CF design rules in the ASME BPVC Section III, Division 5, Subsection HB, Subpart B, experimental and numerical studies are performed on Alloy 617 at 950°C using notch specimen geometries under CF loading in this study.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-driven modeling of municipal water system responses to hydroclimate extremes

Sustainable western US municipal water system (MWS) management depends on quantifying the impacts of supply and demand dynamics on system infrastructure reliability and vulnerability. Systems modeling can replicate the interactions but extensive parameterization, high complexity, and long development cycles present barriers to widespread adoption. To address these challenges, we develop the Machine Learning Water Systems Model (ML-WSM) – a novel application of data-driven modeling for MWS management. We apply the ML-WSM framework to the Salt Lake City, Utah water system, where we benchmark prediction performance on the seasonal response of reservoir levels, groundwater withdrawal, and imported water requests to climate anomalies at a daily resolution against an existing systems model. The ML-WSM accurately predicts the seasonal dynamics of all components; especially during supply-limiting conditions (KGE > 0.88, PBias < ±3%). Extreme wet conditions challenged model skill but the ML-WSM communicated the appropriate seasonal trends and relationships to component thresholds (e.g., reservoir dead pool). The model correctly classified nearly all instances of vulnerability (83%) and peak severity (100%), encouraging its use as a guidance tool that complements systems models for evaluating the influences of climate on MWS performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1995

P-polarized reflectance spectroscopy: A high sensitive real-time monitoring technique to study surface kinetics under steady state epitaxial deposition conditions

This paper describes the results of real-time optical monitoring of epitaxial growth processes by p-polarized reflectance spectroscopy (PRS) using a single wavelength application under pulsed chemical beam epitaxy (PCBE) condition. The high surface sensitivity of PRS allows the monitoring of submonolayer precursors coverage on the surface as shown for GaP homoepitaxy and GaP on Si heteroepitaxy as examples. In the case of heteroepitaxy, the growth rate and optical properties are revealed by PRS using interference oscillations as they occur during growth. Super-imposed on these interference oscillations, the PRS signal exhibits a fine structure caused by the periodic alteration of the surface chemistry by the pulsed supply of chemical precursors. This fine structure is modeled under conditions where the surface chemistry cycles between phosphorus supersaturated and phosphorus depleted surfaces. The mathematical model describes the fine structure using a surface layer that increases during the tertiarybutyl phosphine (TBP) supply and decreases during and after the triethylgallium (TEG) pulse, which increases the growing GaP film thickness. The imaginary part of the dielectric function of the surface layer is revealed from the turning points in the fine structure, where the optical response to the first precursor pulse in the cycle sequence changes sign. The amplitude of the fine structure is determined by the surface layer thickness and the complex dielectric functions for the surface layer with the underlying bulk film. Surface kinetic data can be obtained by analyzing the rise and decay transients of the fine structure.

Dietz, Nikolaus↗
DOE OSTI2024

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Seasonal drivers of dissolved oxygen across a tidal creek–marsh interface revealed by machine learning

Abstract Dissolved oxygen (DO) is a key biogeochemical control in coastal systems, and its concentration and drivers vary markedly through time and space. This makes it difficult to accurately represent coastal DO and associated biogeochemical processes in models, limiting our ability to predict how these systems will respond to global change. We obtained high‐frequency (5‐min) in situ measurements of DO collected at three locations across the interface of a tidal creek and coastal marsh in the Pacific Northwest, USA. Random Forest machine learning models quantified the importance of three categories of environmental drivers (Aquatic, Climatic, and Terrestrial) of DO variability across the creek–marsh interface. We selected two 4‐month datasets representing Summer and Winter seasonal periods to test two hypotheses on the dominant drivers of DO at the coastal interface. We found that the Terrestrial driver—characterized by long periods of anaerobic conditions and episodic pulses in DO after floods—was most important during the Winter, whereas the Aquatic driver—characterized by variability over tidal, diel, and lunar cycles—was most important during the Summer. We explored how future climate change scenarios could alter the drivers of DO variability using a cumulative sums driver–response framework. Our results suggest that under climate change, Aquatic and Climatic drivers may increase in importance during the Summer, potentially linked to changing metabolic regimes and sea level, with Terrestrial driver importance potentially increasing during the Winter. Our approach highlights useful methods for understanding the spatiotemporal complexity of oxygen across coastal interfaces and quantifying the relative importance of distinct environmental drivers.

54 ENVIRONMENTAL SCIENCES↗