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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Precursory Off-Fault Deformation in Restraining and Releasing Step Overs: Insights From Discrete Element Method Models

Accelerating geophysical activity is detected preceding some, but not all, large earthquakes. This observation may indicate that no precursors occur before some earthquakes, or that the instrumentation lacks the required sensitivity. Here, to aid crustal monitoring efforts, we use discrete element method models to identify the locations and styles of deformation that may provide useful information about approaching fault reactivation. We model the reactivation of two healed rough faults in a variety of step over configurations, embedded in a host rock with varying amounts of damage subject to shear velocity loading parallel to the faults. Both the fault geometry and ratio of fault to host rock strength control the amount of off-fault deformation. Consistent with field observations, models with larger steps and more preexisting host rock damage produce higher amounts of off-fault deformation. We assess the size of the continuous regions of high velocities and strains to compare the value of the precursory information of each velocity and strain component. Comparing the three components of the velocity vector suggests that the fault-parallel velocity produces the largest and most temporally continuous regions of elevated velocity. The size of these regions increases toward failure, indicating the usefulness of tracking this component. Comparing the volumetric and shear components of the three-dimensional strain tensor suggests that during most of the interseismic period, the shear strain provides more information about approaching fault slip than the volumetric strain. However, in the days and months preceding fault reactivation, both the shear and volumetric strains provide similarly valuable information.

58 GEOSCIENCES↗
DOE OSTI2023

Production of ice-nucleating particles (INPs) by fast-growing phytoplankton

Sea spray aerosol contains ice-nucleating particles (INPs), which affect the formation and proper ties of clouds. Here, we show that aerosols emitted from fast-growing marine phytoplankton produce effective immersion INPs, which nucleate at temperatures significantly warmer than the atmospheric homogeneous freezing (-38.0 °C) of pure water. Aerosol sampled over phytoplankton cultures grown in a Marine Aerosol Ref erence Tank (MART) induced nucleation and freezing at temperatures as high as -15.0 °C during exponential phytoplankton growth. This was observed in monospecific cultures representative of two major groups of phy toplankton, namely a cyanobacterium (Synechococcus elongatus) and a diatom (Thalassiosira weissflogii). Ice nucleation occurred at colder temperatures (-28.5 °C and below), which were not different from the freezing temperatures of procedural blanks, when the cultures were in the stationary or death phases of growth. Ice nucleation at warmer temperatures was associated with relatively high values of the maximum quantum yield of photosystem II ( Φ PSII ), an indicator of the physiological status of phytoplankton. High values of Φ PSII indicate the presence of cells with efficient photochemistry and greater potential for photosynthesis. For comparison, field measurements in the North Atlantic Ocean showed that high net growth rates of natural phytoplankton assemblages were associated with marine aerosol that acted as effective immersion INPs at relatively warm temperatures. Data were collected over 4 d at a sampling station maintained in the same water mass as the water column stabilized after deep mixing by a storm. Phytoplankton biomass and net phytoplankton growth rate (0.56 d -1 ) were greatest over the 24 h preceding the warmest mean ice nucleation temperature (-25.5 °C). Collectively, our laboratory and field observations indicate that phytoplankton physiological status is a useful predictor of effective INPs and more reliable than biomass or taxonomic affiliation. Ocean regions associated with fast phytoplankton growth, such as the North Atlantic during the annual spring bloom, may be significant sources of atmospheric INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Radiative absorption enhancements by black carbon controlled by particle-to-particle heterogeneity in composition

Black carbon (BC) absorbs solar radiation, leading to a strong but uncertain warming effect on climate. A key challenge in modeling and quantifying BC’s radiative effect on climate is predicting enhancements in light absorption that result from internal mixing between BC and other aerosol components. Modeling and laboratory studies show that BC, when mixed with other aerosol components, absorbs more strongly than pure, uncoated BC; however, some ambient observations suggest more variable and weaker absorption enhancement. We show that the lower-than-expected enhancements in ambient measurements result from a combination of two factors. First, the often used spherical, concentric core-shell approximation generally overestimates the absorption by BC. Second, and more importantly, inadequate consideration of heterogeneity in particle-to-particle composition engenders substantial overestimation in absorption by the total particle population, with greater heterogeneity associated with larger model–measurement differences. We show that accounting for these two effects—variability in per-particle composition and deviations from the core-shell approximation—reconciles absorption enhancement predictions with laboratory and field observations and resolves the apparent discrepancy. Furthermore, our consistent model framework provides a path forward for improving predictions of BC’s radiative effect on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Interpreting accelerated tests on perovskite modules using photooxidation of MAPbI 3 as an example

Solar panels (modules) based on metal halide perovskites are following a fast track to commercialization. Unlike more established solar cell materials, there are not yet decades-long field observations to increase consumer confidence. The "physics and chemistry of failure" approach is used in other industries and estimates product degradation based on laboratory accelerated tests integrated with an understanding of degradation mechanisms. This work uses that approach to quantify the relationship between accelerated tests and projected product behavior for metal halide perovskite modules. Degradation involving photooxidation of methylammonium lead iodide is used to illustrate the method. Acceleration factors in common accelerated tests are found to be low. Conclusions emphasize that the accelerated tests on photovoltaics should not be interpreted as equivalent across module types or as a green light for commercialization unless supported by the appropriate field data or physics and chemistry of failure analysis.

14 SOLAR ENERGY↗
DOE OSTI2026

Widespread windthrow in Southeast Asian tropical forests verified by satellite observations

Windthrow, defined as abrupt tree mortality caused by intense winds, is well documented in the Neotropics but remains largely unverified in Asian tropical forests. Using Landsat 8 imagery for the period 2020-2022 and established spectral (shortwave-infrared, near-infrared, and red band composites) and morphological criteria (fan-shaped geometry and sharp boundaries), this study verified the presence of windthrow across Sumatra, Borneo, and New Guinea and produced the first georeferenced inventory of 60 events in the region. Event sizes were right-skewed, with many small gaps and few large (>200 ha) disturbances. Orientations were anisotropic, with concentrations of windthrow events pointing west to northwest-to-north and eastward, both aligning with known pathways of organized convection in the Maritime Continent of Southeast Asia. Detection was conservatively biased low by cloud cover, long revisit intervals, and the exclusion of land-use areas. This study provides a verified baseline that enables reproducible mapping with higher resolution sensors and field observations to quantify windthrow frequency, severity, and ecological significance.

Asia’s tropical forests↗
DOE OSTI2023

Imaging the Future Threats of the Sand Dunes Along the Northwestern Coast of Nile Delta Using SAR

Although the Sand dunes screen the coastal cities from the sand dunes hazards and their infrastructures from rising sea levels and storms, they might threaten and hide the surrounding developmental projects. Thus, imaging these coastal dunes' internal anatomy and dynamics are crucial to protect the environment. In this study, the Optical and Synthetic Aperture Radar (SAR) images were processed and integrated with field observations and surveys to extract information about the past, current, and future behavior of coastal dunes in the Nile Delta-Northwest sector. A conventional change detection method using the supervised Landsat-8 images for the years 2015 and 2017 were generated to show a rapid change in the sand dune cover, where the high-resolution images of Google Earth were used to digitize the dune crests and measure its encroachment rate, which has been reached about 4 m/year with the NW–SE direction. The full-polarimetric ALOS/PALSAR-2 images from the years 2015 and 2017 show very low coherence for the sand dunes, which means these dunes are dynamic, where the changes in both power and phase imbalances of different dune fields during the investigated years (2015 and 2017) show high differences in values, which reached 40 dB and 0.06°, respectively. Finally, the extracted radar facies from the field survey show two successive groups of coastal sand dunes show a decline in the heavy minerals content to a level that might threaten the properties at the shoreline due to sea level rise and wave storms if mitigation actions are not taken place soon.

Ramadan, Rabab↗
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗
DOE OSTI2020

A Tidal Hydrodynamic Model for Cook Inlet, Alaska, to Support Tidal Energy Resource Characterization

Cook Inlet in Alaska has been identified as a prime site in the U.S. for potential tidal energy development, because of its enormous tidal power potential that accounts for nearly one-third of the national total. As one important step to facilitate tidal energy development, a tidal hydrodynamic model based on the unstructured-grid, finite-volume community ocean model (FVCOM) was developed for Cook Inlet to characterize the tidal stream energy resource. The model has a grid resolution that varies from about 1000 m at the open boundary to 100–300 m inside the Inlet. Extensive model validation was achieved by comparing model predictions with field observations for tidal elevation and velocity at various locations in Cook Inlet. The error statistics confirmed the model performs reasonably well in capturing the tidal dynamics in the system, e.g., R2 > 0.98 for tidal elevation and generally > 0.9 for velocity. Model results suggest that tides in Cook Inlet evolve from progressive waves at the entrance to standing waves at the upper Inlet, and that semi-diurnal tidal constituents are amplified more rapidly than diurnal constituents. The model output was used to identify hotspots that have high energy potential and warrant additional velocity and turbulence measurements such as East Foreland, where averaged power density exceeds 5 kw/m2. Lastly, a tidal energy extraction simulation was conducted for a hypothetical turbine farm configuration at the Forelands cross section to evaluate tidal energy extraction and resulting changes in far-field hydrodynamics.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2025

Annual carbon dioxide flux over seasonal sea ice in the Canadian Arctic

Continuous measurements of carbon dioxide (CO 2 ) flux were collected from a 10 m eddy covariance tower in a coastal-marine environment in the Canadian Arctic Archipelago over the course of a 17-month period. The extended length of data collection resulted in a unique dataset that includes measurements from two spring melt and summer seasons and one autumn freeze-up. These field observations were used to verify findings from previous theoretical and laboratory experiments investigating air-sea gas exchange in connection with sea ice. The results corroborated previous findings showing that thick ice cover under winter conditions acts as a barrier to gas exchange. In the spring, CO 2 fluxes were downward (uptake) in both the presence of melt ponds and during ice break-up. However, diurnal cycles were present throughout the early spring melt period, corresponding to the opposing influences of freezing and melting at the ice surface. Fluxes measured during melt periods confirmed previous laboratory tank measurements that showed a gas transfer coefficient of melting ice of 0.4 mol m −2 d −1 atm −1 . Open water CO 2 fluxes showed outgassing in early summer and uptake in mid-to-late summer, tied closely to trends in surface water temperature and its effect on the partial pressure of CO 2 in the water. The autumn period of the field campaign represents the first eddy covariance CO 2 fluxes measured over naturally forming sea ice. Our measurements showed mean upward fluxes (outgassing) of 1.1±1.5 mmol m −2 d −1 associated with the freezing of ice – the same order of magnitude found by previous laboratory tank experiments. However, peak flux periods during ice formation had measured fluxes that were a factor of 3 higher than the tank experiments, suggesting the importance of natural conditions (e.g., wind) on air-ice gas exchange. Conducting an Arctic-wide extrapolation we estimate CO 2 outgassing from the freezing period to be a counterbalance equivalent to 5 to 15 % of the magnitude of the estimated Arctic CO 2 sink. Overall, there was no evidence of dramatically enhanced gas exchange in marginal ice conditions as proposed by previous studies. Although the different seasons showed active CO 2 exchange, there was a balance between upward and downward fluxes at this specific location, resulting in a small net CO 2 uptake over the annual cycle of −0.3 g C m −2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A strainmeter array as the fulcrum of novel observatory sites along the Alto Tiberina Near Fault Observatory

Fault slip is a complex natural phenomenon involving multiple spatiotemporal scales from seconds to days to weeks. To understand the physical and chemical processes responsible for the full fault slip spectrum, a multidisciplinary approach is highly recommended. The Near Fault Observatories (NFOs) aim at providing high-precision and spatiotemporally dense multidisciplinary near-fault data, enabling the generation of new original observations and innovative scientific products. The Alto Tiberina Near Fault Observatory is a permanent monitoring infrastructure established around the Alto Tiberina fault (ATF), a 60 km long low-angle normal fault (mean dip 20°), located along a sector of the Northern Apennines (central Italy) undergoing an extension at a rate of about 3 mm yr –1 . The presence of repeating earthquakes on the ATF and a steep gradient in crustal velocities measured across the ATF by GNSS stations suggest large and deep (5–12 km) portions of the ATF undergoing aseismic creep. Both laboratory and theoretical studies indicate that any given patch of a fault can creep, nucleate slow earthquakes, and host large earthquakes, as also documented in nature for certain ruptures (e.g., Iquique in 2014, Tōhoku in 2011, and Parkfield in 2004). Nonetheless, how a fault patch switches from one mode of slip to another, as well as the interaction between creep, slow slip, and regular earthquakes, is still poorly documented by near-field observation. With the strainmeter array along the Alto Tiberina fault system (STAR) project, we build a series of six geophysical observatory sites consisting of 80–160 m deep vertical boreholes instrumented with strainmeters and seismometers as well as meteorological and GNSS antennas and additional seismometers at the surface. By covering the portions of the ATF that exhibits repeated earthquakes at shallow depth (above 4 km) with these new observatory sites, we aim to collect unique open-access data to answer fundamental questions about the relationship between creep, slow slip, dynamic earthquake rupture, and tectonic faulting.

58 GEOSCIENCES↗
DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗
DOE OSTI2020

Coupled Thermo–Hydro–Mechanical Modeling of Hydro-Shearing Stimulation in an Enhanced Geothermal System in the Raft River Geothermal Field, USA

The Raft River Enhanced Geothermal System (EGS) demonstration project aims to improve the geothermal production by enhancing the reservoir permeability via shear stimulation in well RRG-9. In this paper, we performed a series of 3D thermo– hydro–mechanical (THM) simulations to investigate the influence of hydraulic and thermal effects on the development of this EGS. The model includes synthetic fracture populations based on borehole televiewer images and in-situ stress measurements from well RRG-9. Fracture permeability evolution is determined using an empirical permeability law developed from laboratory experiments. The model was calibrated by comparing the hydraulic response to field observations, including wellhead pressure, injection rate, and well injectivity. Particularly, we analyzed the enhancement of reservoir permeability and the spatial extent of the stimulation zone for the given injection schedule. Our results indicate that the permeability enhancement of fractured geothermal reservoir is caused by the combined effects of injection-induced cooling and fluid pressure increase. The decrease of temperature plays a dominant role in reactivation of natural fractures under the hydro-shearing mechanism, while the higher injection pressure promotes shear failure and enlarges the stimulation zone. Finally, for the specified extensional stress state, the model favors greatest permeability enhancement along the maximum horizontal principal stress, a moderate vertical enhancement, and a smaller gain along the minimum horizontal principal stress.

58 GEOSCIENCES↗
DOE OSTI2024

Cultural Shifts in High Energy Physics Collaboration from the Cold War to the Present: A Historical and Philosophical Perspective

Here, this article employs empirical history and the philosophy of science to study cultural convergences and divergences in international collaborations in high energy physics. We examine two cases: (1) E-36, an experiment on small angle proton-proton scattering conducted during the Cold War at the National Accelerator Laboratory (NAL) in the USA by Soviet and US scientists and (2) an ongoing collaborative experiment, NICA, at the Joint Institute for Nuclear Research (JINR, Dubna), which is a project devoted to heavy-ion physics. The JINR, particularly its Laboratory of High Energy Physics (formerly the “Laboratory of High Energies”) is the main mediating actor between these two cases (i.e., E-36 and NICA), as the majority of Soviet participants in E-36 were representatives of the Institute. Using empirical data collected through archival searches, field observations conducted at JINR in 2018–2019, and in-depth interviews, we tell a story of cultural differences in high energy physics by applying the concepts of ‘trading zones’ (P. Galison) and the translation of interests in actor-networks (B. Latour, M. Callon and others). We analyze three types of cultural diversity (specialization, nationality, and generational) in light of the implications of temporal context and the dichotomy between East and West, showing the roles cultural diversity plays in scientific collaboration (which is an integral part of as well as obstacle to scientific research that can nevertheless provide learning opportunities). Our study aims to demonstrate how disunity and diversity may function in scientific research and how high energy physics collaborations can remain productive despite sometimes deep divergences, including those between East and West.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Observations of particle number size distributions and new particle formation in six Indian locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21% of the days) and is the least common in October–November (post-monsoon, about 7% of the days). Considering the NPF events in all locations, the particle formation rate (J SDS ) varied by more than 2 orders of magnitude (0.001–0.6 cm –3 s –1 ) and the growth rate between the smallest detectable size and 25nm (GR SDS-25nm ) by about 3 orders of magnitude (0.2–17.2nm h –1 ). We found that J SDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GR SDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10 3 cm –3 per event and 1.2 × 10 3 cm –3 per event for 50 and 100nm, respectively) as compared to mountain background sites (2.7 × 10 3 cm –3 per event and 1.0 × 10 3 cm –3 per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Use of Stable Mercury Isotopes to Assess Mercury and Methylmercury Transformation and Transport across Critical Interfaces from the Molecular to the Watershed Scale (Final Report)

This project titled “Use of Stable Mercury Isotopes to Assess Mercury and Methylmercury Transformation and Transport across Critical Interfaces from the Molecular to the Watershed Scale” represents a collaborative effort between the University of Michigan (Jason Demers, PI) and Oak Ridge National Laboratory (Scott Brooks, co-I). Much has been learned about mercury (Hg) cycling in stream ecosystems, and East Fork Poplar Creek (EFPC) in particular, through decades of previous research. Nevertheless, some of the most fundamental questions regarding the sources of bioavailable Hg and its transformation to toxic methylmercury (MeHg) have remained unanswered. These fundamental questions include: (1) what are the sources and biogeochemical processes that lead to the input of dissolved Hg to stream water across critical subsurface interfaces within stream ecosystems, and EFPC in particular? and (2) what are the sources and biogeochemical processes that control the production and fate of bioaccumulative MeHg within stream ecosystems, and in EFPC in particular? To address these fundamental questions, our project aimed to couple laboratory experiments and field observations, both utilizing natural abundance Hg stable isotope techniques, to identify the processes responsible for generating mobile, bioavailable dissolved Hg from recalcitrant legacy sources within critical subsurface zones (e.g., streambed hyporheic zone, riparian floodplain subsurface). We used the isotopic signature of this bioavailable dissolved Hg to track its mobilization across these critical interfaces in order to link diffuse subsurface sources of dissolved Hg with increases in surface water dissolved Hg flux measured at the watershed scale. Additionally, our research aimed to determine the isotopic composition of MeHg within these same critical subsurface zones. We directly assessed the isotopic composition of MeHg within biota in order to gain insight into which subsurface sources of inorganic Hg and toxic MeHg are available for bioaccumulation within the EFPC ecosystem. Net fluxes of dissolved Hg along the flow path of EFPC were shown to vary spatially and temporally. In the Upper EFPC, within the Y12 boundary, stream water flux of dissolved Hg consistently decreased between the outfall and the downstream boundary of Y12 (57% ± 29%, 1SD). Within the Upper EFPC, an assessment of Hg isotopic composition suggested that losses were strongly reaction-driven, although isotopic diagnostics did not conform to any known processes. Downstream of Y12, in the upper reach of the Lower EFPC, dissolved Hg fluxes tended to increase during the dormant season (net gain of 11-120%), and decrease during the growing season (net loss of 23% +/- 18%, 1SD). In the downstream-most reach of Lower EFPC, dissolved Hg fluxes increased by 12-108% in 9 out of 10 monthly assessments. Overall, diffuse fluxes from the non-Y12 watershed accounted for 34% (+/- 17%, 1SD) of all dissolved Hg exported during base flow. Within Lower EFPC, an assessment of Hg isotopic composition was consistent with the contribution of diffuse Hg inputs from high-concentration hotspots within riparian floodplains and streambed hyporheic pore water. To investigate remobilization of recalcitrant Hg from legacy sediment sources, we developed procedures that coupled isotopic analysis with sequential extractions of streambed sediment. We found that the proportion of weakly-bound Hg within EFPC streambed sediment was relatively small, but could still account for a large proportion of the annual flux of dissolved Hg from EFPC. These sequential extractions also showed that this weakly-bound Hg fraction could be replenished from the much larger fraction of recalcitrant Hg in sediment. The isotopic composition of these weakly-bound and remobilized recalcitrant Hg fractions within the sediment was consistent with high-concentration dissolved Hg hotspots within hyporheic pore water. Thus, this research provided novel evidence that legacy mercury sources within streambed sediment could provide an ongoing contribution of dissolved Hg to surface waters. Finally, we developed new methods for the direct determination of the MeHg isotopic composition of organisms, which allowed a more direct evaluation of inorganic Hg and MeHg sources accumulating in the food web. We found that fish and aquatic invertebrates in both EFPC and a regional background site obtained inorganic Hg and MeHg from multiple isotopically distinct sources, including sediment, suspended particulates, and periphyton. Photodemethylation was found to be an important reaction influencing MeHg dynamics at both sites. However, the balance of microbial methylation and demethylation processes differed between the two streams, with fractionation resulting from methylation and demethylation processes being relatively in balance within the regional background site, whereas microbial methylation appeared to be dominant over microbial demethylation within the EFPC ecosystem. Broadly, the application of Hg isotopic analysis in this study led to numerous novel insights regarding the biogeochemical cycling of Hg in stream ecosystems. This research project promoted the development of two new approaches, including the coupling of sequential extractions with Hg isotopic analysis to assess remobilization of recalcitrant Hg within sediments, and a new method for the isotopic analysis of MeHg isolated from environmental samples. Both of these efforts represent advances in capacity for the field of mercury isotopic analysis and environmental assessment. Overall, this study demonstrates that the application of Hg stable isotope techniques continues to provide new insights into the biogeochemical cycling of Hg in complex aquatic environments, both within the EFPC and beyond.

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

JAMES BUTTLE REVIEW: Interflow, subsurface stormflow and throughflow: A synthesis of field work and modelling

Interflow, throughflow and subsurface stormflow are interchangeable terms that refer to the lateral subsurface flow above a restricting layer of lower hydraulic conductivity that occurs during and following storm events. Interflow (used here) is a more dominant process in steeper catchments with high infiltration capacity soils overlying a more impermeable soil or geologic layer. Interflow as a runoff process was first recognised in the early 1900s, yet hydrologists still struggle to predict its occurrence, persistence, importance, interaction with other streamflow generation processes, and potential to connect to valleys and streams during and following storms. We review the history of interflow research and address some of the challenges in understanding its role in runoff production. We argue that characterising the controls on interflow initiation and occurrence relies on detailed field observations of subsurface properties, which exist only in limited experimental settings. This data shortcoming contributes to our inability to predict interflow or determine its contribution to streamflow more broadly. There remain many opportunities to advance our understanding of interflow that include both modelling and experimental or observational approaches in hydrology.

hillslope hydrology↗
DOE OSTI2025

UV + Damp Heat Induced Power Losses in Fielded Utility N-Type Si PV Modules

A recent trend in commercial PV modules is a transition to n-type silicon cells, including passivated emitter rear totally diffused (n-PERT), tunnel oxide passivated contact (TOPCon), and silicon heterojunction (SHJ). There is evidence via lab studies that some of these cells are more susceptible to UV induced degradation (UVID), yet there is a lack of confirmation that such degradation occurs in the field. Current IEC standards designed to screen for early module failures require only minimal UV exposure (15 kWh/m2 280-400 nm, ~2-3 months equivalent outdoor exposure). Here, we investigate fielded n-PERT silicon (Si) modules from a commercial utility that show power losses of ~2%/year. We present a comprehensive picture of the physics and chemistry of degradation supported by both module and cell electronic characterization (EL, PL, IV, EQE, and DLIT) and materials-level morphological and chemical analysis (SEM, EDS, XPS, FTIR, and HPLC). All sampled site modules show short circuit current (Isc) and open circuit voltage (Voc) losses when compared to unfielded spares, with the most severely degraded also having losses in fill factor (FF). We identify two different degradation modes contributing to overall power loss: (1) external quantum efficiency (EQE) measurements show losses in the blue range of the spectra, indicative of cell surface recombination losses, and (2) variations in high series resistance (Rs) at the cell level that are correlated with compositional differences in cell metallization. Using unfielded spares, we were able to reproduce Voc, Isc, and EQE losses via a minimum UV stress of 67.5 kWh/m2 (280-400 nm), 4.5x the exposure currently required in IEC 61215-2 (MQT 10). Degradation continued with additional UV dosage equivalent to the fielded modules (405 kWh/m2 total), with power loss leveling out at an average of 6.1%. Subsequent 1000 h of 85% RH/85degrees C damp heat testing showed that cells exposed to UV underwent additional severe series resistance degradation, even those without the susceptible paste composition seen in the field, whereas non-UV exposed cells saw little change. We attribute this to higher concentrations of acetic acid generated on the UV exposed area of the module, leading to degradation of the gridline/cell interface and high Rs. This study is unique in that it reproduces field observed utility scale UVID with an accelerated test and supports the need for standards development for longer UV exposure combined with other stress factors to catch materials interplay within a module package.

14 SOLAR ENERGY↗