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DOE OSTI2021

Unraveling the intrinsic atomic physics behind x-ray absorption line shifts in warm dense silicon plasmas

Here, we present a novel free-energy density functional theory (DFT)-based methodology for optical property calculations of warm dense matter to cover a wide range of thermodynamic conditions and photon energies including the entire x-ray range. It uses Mermin–Kohn–Sham density functional theory with exchange-correlation (XC) thermal effects taken into account via a fully temperature dependent generalized gradient approximation XC functional. The methodology incorporates a combination of the ab initio molecular dynamics (AIMD) snapshotted Kubo–Greenwood optic data with a single-atom in simulation cell calculations to close the photon energy gap between the L and K edges and extend the K-edge tail toward many-keV photon energies. This gap arises in the standard scheme due to a prohibitively large number of bands required for the Kubo–Greenwood calculations with AIMD snapshots. Kubo–Greenwood data on snapshots provide an accurate description of optic properties at low photon frequencies slightly beyond the L-edge and x-ray absorption near edges structure (XANES) spectra, while data from periodic calculations with single atoms cover the tail regions beyond the edges. To demonstrate its applicability to mid-Z materials where the standard DFT-based approach is not computationally feasible, we have applied it to opacity calculations of warm dense silicon plasmas. These first-principles calculations revealed a very interesting phenomon of red-to-blue shift in K–L (1s → 2p) and K-edge absorptions along both isotherm and isochore, which are absent in most continuum-lowering models of traditional plasma physics. This new physics phenomenon can be attributed to the underlying competition between the screening of deeply bound core electrons and the screening of outer-shell electrons caused by warm-dense-plasma conditions. We further demonstrate that the ratio of 1s → 2p to the K-edge x-ray absorptions can be used to characterize warm-dense-plasma conditions. Eventually, based on our absorption calculations, we have established a first-principles opacity table (FPOT) for silicon in a wide range of material densities and temperatures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

A carbon molecular sieve membrane-based reactive separation process for pre-combustion CO 2 capture

In this study, we discuss a hybrid system combining a membrane reactor (MR) and an adsorptive reactor (AR), with the MR's reject stream serving as the AR's feed. We apply this system for the water gas shift (WGS) reaction for H 2 generation and simultaneous CO 2 capture in the context of the Integrated Gas Combined Cycle (IGCC) process for power generation from coal and biomass. This MR-AR system attains a high conversion exceeding equilibrium, produces a pure H 2 product for power generation, and delivers a high-pressure CO 2 stream ready for sequestration. Specifically, in our study we use carbon molecular sieve membranes (CMSMs) and a commercial sour-shift WGS catalyst. Lab experiments were carried-out to determine the membrane characteristics, and the MR performance under IGCC-relevant conditions, i.e., for temperatures up to 250 °C and pressures up to 25 bar, employing a model coal gasifier syngas. The CMSM and the catalyst have displayed robust and stable performance during a long-term run (~750 h of syngas exposure). We evaluated the MR-AR system in multi-cycle runs and it has demonstrated superior performance to that of a conventional packed-bed reactor, producing a high-purity H 2 product directly useable in a turbine for power generation. We conclude from the study, that the CMSM-based MR-AR system is a good candidate technology for environmentally-benign power generation. We are currently constructing a pilot-scale system for field demonstration of the technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

In-field bioreactors demonstrate dynamic shifts in microbial communities in response to geochemical perturbations

Subsurface microbial communities mediate the transformation and fate of redox sensitive materials including organic matter, metals and radionuclides. Few studies have explored how changing geochemical conditions influence the composition of groundwater microbial communities over time. We temporally monitored alterations in abiotic forces on microbial community structure using 1L in-field bioreactors receiving background and contaminated groundwater at the Oak Ridge Reservation, TN. Planktonic and biofilm microbial communities were initialized with background water for 4 days to establish communities in triplicate control reactors and triplicate test reactors and then fed filtered water for 14 days. On day 18, three reactors were switched to receive filtered groundwater from a contaminated well, enriched in total dissolved solids relative to the background site, particularly chloride, nitrate, uranium, and sulfate. Biological and geochemical data were collected throughout the experiment, including planktonic and biofilm DNA for 16S rRNA amplicon sequencing, cell counts, total protein, anions, cations, trace metals, organic acids, bicarbonate, pH, Eh, DO, and conductivity. We observed significant shifts in both planktonic and biofilm microbial communities receiving contaminated water. This included a loss of rare taxa, especially amongst members of the Bacteroidetes, Acidobacteria, Chloroflexi, and Betaproteobacteria, but enrichment in the Fe- and nitrate- reducing Ferribacterium and parasitic Bdellovibrio. These shifted communities were more similar to the contaminated well community, suggesting that geochemical forces substantially influence microbial community diversity and structure. These influences can only be captured through such comprehensive temporal studies, which also enable more robust and accurate predictive models to be developed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Equation of state for He bubbles in W and model of He bubble growth and bursting near W{100} surfaces derived from molecular dynamics simulations

Abstract Molecular dynamics (MD) simulations are performed to derive an equation of state (EOS) for helium (He) bubbles in tungsten (W) and to study the growth of He bubbles under a W(100) surface until they burst. We study the growth as a function of the initial nucleation depth of the bubbles. During growth, successive loop-punching events are observed, accompanied by shifts in the depth of the bubble towards the surface. Subsequently, the MD data are used to derive models that describe the conditions that cause the loop punching and bursting events. Simulations have been performed at 500, 933, 1500, 2000, and 2500 K to fit the parameters in the models. To compute the pressure in the bubble at the loop punching and bursting events from the models, we derive an EOS for He bubbles in tungsten with an accompanying volume model to compute the bubble volume for a given number of vacancies ( $$N_\text {V}$$ N V ), He atoms ( $$N_\text {He}$$ N He ), and temperature ( T ). To derive the bubble EOS, we firstly derive the EOS for a free He gas. The derived free-gas EOS can accurately predict all MD data included in the analysis (which span up to 54 GPa at 2500 K). Subsequently, the bubble EOS is derived based on the free-gas EOS by correcting the gas density to account for the interaction between He and W atoms. The EOS for the bubbles is fitted to data from MD simulations of He bubbles in bulk W that span a wide range of gas density and sizes up to about 3 nm in diameter. The pressure of subsurface bubbles at the loop punching events as calculated using the bubble-EOS and the volume model agrees well with the pressure obtained directly from the MD simulations. In the loop punching model, for bubbles consisting of $$N_\text {V}$$ N V vacancies and $$N_\text {He}$$ N He helium atoms, the $$N_\text {He}/N_\text {V}$$ N He / N V ratio that causes the event, the resulting increase in $$N_\text {V}$$ N V , and the associated shift of the bubble depth are formulated as a function of $$N_\text {V}$$ N V and T . In the bursting model, a bubble must simultaneously reach a certain depth and $$N_\text {He}/N_\text {V}$$ N He / N V ratio in order to burst. The burst depth and $$N_\text {He}/N_\text {V}$$ N He / N V are also modeled as a function of $$N_\text {V}$$ N V and T . The majority of the loop punching events occur at bubble pressures between 20 and 60 GPa, depending on the bubble size and temperature. The larger the bubble and the higher the temperature, the lower the bubble pressure. Furthermore, our results indicate that at a higher temperature, a bubble can burst from a deeper region.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Diel Transcriptional Oscillations of a Plastid Antiporter Reflect Increased Resilience of Thalassiosira pseudonana in Elevated CO 2

Acidification of the ocean due to high atmospheric CO 2 levels may increase the resilience of diatoms causing dramatic shifts in abiotic and biotic cycles with lasting implications on marine ecosystems. Here, we report a potential bioindicator of a shift in the resilience of a coastal and centric model diatom Thalassiosira pseudonana under elevated CO 2 . Specifically, we have discovered, through EGFP-tagging, a plastid membrane localized putative Na + (K + )/H + antiporter that is significantly upregulated at >800 ppm CO 2 , with a potentially important role in maintaining pH homeostasis. Notably, transcript abundance of this antiporter gene was relatively low and constant over the diel cycle under contemporary CO 2 conditions. In future acidified oceanic conditions, dramatic oscillation with >10-fold change between nighttime (high) and daytime (low) transcript abundances of the antiporter was associated with increased resilience of T. pseudonana. By analyzing metatranscriptomic data from the Tara Oceans project, we demonstrate that phylogenetically diverse diatoms express homologs of this antiporter across the globe. We propose that the differential between night- and daytime transcript levels of the antiporter could serve as a bioindicator of a shift in the resilience of diatoms in response to high CO 2 conditions in marine environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Emulating climate extreme indices

We use simple pattern scaling and time-shift to emulate changes in a set of climate extreme indices under future scenarios, and evaluate the emulators' accuracy. We propose a metric for the error in emulation in the context of initial condition ensembles, to specifically characterize the role of internal variability in the emulation performance. Our metric separates systematic emulation errors from unavoidable discrepancies between emulated and target values due to internal variability. We compute the metricis at grid-point scale, and we show geographically resolved results, or aggregate them at global scale. We demonstrate the use of our error metric in the emulation of a suite of temperature and precipitation extreme indices. We test and compare simple pattern scaling and time-shift using a range of trajectories spanning targets inspired by the Paris agreement -- warming to 1.5C and 2.0C from the pre-industrial baseline -- and two of the longer-established trajectories, RCP4.5 and RCP8.5. With this suite of scenarios we can test the effects on the performance of the size of the temperature gap between emulation origin and target. We find that for most indices emulation the dominant source of discrepancy is internal variability. For at least one index, however, counting exceedances of a high temperature threshold, significant portions of the globally aggregated discrepancy and its regional pattern originate from the systematic emulation error. This error exceeds internal variability of both the target and the emulated quantities in large coherent regions at low latitudes, and the explanation can be found in the differential behavior of temperature distributions across latitudes. The metric also highlights a fundamental difference in the two methods related to the simulation of internal variability, which is dampened significantly by simple pattern scaling. This aspect is of consequence when using these methods for specific applications, where preserving variability for uncertainty quantification is deemed important. With this study we offer our metric as a diagnostic tool, facilitating the formulation of scientific hypotheses on the reasons for the error. In the meantime, we show that for many impact relevant indices by now traditional emulation techniques can be accurate within the variations unavoidably introduced by internal variability, establishing the fundamental condition for using their emulation in impact modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Rising Water Levels and Vegetation Shifts Drive Substantial Reductions in Methane Emissions and Carbon Dioxide Uptake in a Great Lakes Coastal Freshwater Wetland

ABSTRACT Coastal freshwater wetlands are critical ecosystems for both local and global carbon cycles, sequestering substantial carbon while also emitting methane (CH 4 ) due to anoxic conditions. Estuarine freshwater wetlands face unique challenges from fluctuating water levels, which influence water quality, vegetation, and carbon cycling. However, the response of CH 4 fluxes and their drivers to altered hydrology and vegetation remains unclear, hindering mechanistic modeling. To address these knowledge gaps, we studied an estuarine freshwater wetland in the Great Lakes region, where rising water levels led to a vegetation shift from emergent Typha dominance in 2015–2016 to floating‐leaved species in 2020–2022. Using eddy covariance flux measurements during the peak growing season (June–September) of both periods, we observed a 60% decrease in CH 4 emissions, from 81 ± 4 g C m −2 in 2015–2016 to 31 ± 3 g C m −2 in 2020–2022. This decline was driven by two main factors: (1) higher water levels, which suppressed ebullitive fluxes via increased hydrostatic pressure and extended CH 4 residence time, enhancing oxidation potential in the water column; and (2) reduced CH 4 conductance through plants. Net carbon dioxide (CO 2 ) uptake decreased by 90%, from −267 ± 26 g C m −2 in 2015–2016 to −27 ± 49 g C m −2 in 2020–2022. Additionally, diel CH 4 flux patterns shifted, with a distinct morning peak observed in 2015–2016 but absent in 2020–2022, suggesting changes in plant‐mediated transport and a potential decoupling from photosynthesis. The dominant factors influencing CH 4 fluxes shifted from water temperature and gross primary productivity in 2015–2016 to atmospheric pressure in 2020–2022, suggesting an increased role of ebullition as a primary transport pathway. Our results demonstrate that changes in water levels and vegetation can substantially alter CH 4 and CO 2 fluxes in coastal freshwater wetlands, underscoring the critical role of hydrological shifts in driving carbon dynamics in these ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Glassy carbon formation from pyrolysis of polymeric coatings on fiber-optic sensors

Deploying fiber-optic sensors in nuclear reactors requires a detailed understanding of radiation effects on the fiber materials and the transmitted signals. Previous work has shown large wavelength shifts in the reflected spectra obtained from polymer-coated fiber-optic temperature sensors exposed to high neutron fluences. The sensor drift resulting from these wavelength shifts cannot be explained by radiation effects on fused silica glass. These shifts are hypothesized to be caused by the conversion of the polymeric fiber coating to a glassy carbon via radiolysis and/or pyrolysis and subsequent radiation-induced compaction. Here, thermal degradation of these polymeric coatings was studied to provide insight into the potential origins of the sensor drift phenomenon. Acrylate- and polyimide-coated fibers were heated under various temperatures (250–1300 °C) and environments (oxidative and inert), and the resulting coating products were characterized via mass-loss data, scanning electron microscope imaging, and Raman spectroscopy. Results suggest that the polymer decomposition product of both coating types, at least under inert conditions, is indeed a glassy carbon. Analytical models that account for radiation-induced glassy carbon coating compaction show significant compressive fiber strains and predicted wavelength shifts that agree well with experimental measurements, providing additional evidence that supports the hypothesized origins of the sensor drift.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions

Large, high-severity wildfires in many regions across the globe have increased concerns about their impacts on carbon cycling in watersheds. Altered sources of carbon and changes in catchment hydrology after wildfire can lead to shifts in dissolved organic carbon (DOC) concentrations in streams, which can have negative impacts on aquatic ecosystem health and downstream drinking-water treatment. Despite its importance, post-fire DOC responses remain relatively unconstrained in the literature, and we lack critical knowledge of how burn severity, landscape elements, and climate interact to affect DOC concentrations. To improve our understanding of the impact of burn severity on DOC concentrations, we measured DOC at 129 sites across a stream network extending upstream, within, and downstream of a large, high-severity wildfire in Oregon, USA. We collected samples across the study sub-basin during four distinct seasonal wetness conditions. We used our high-spatial-resolution data to develop spatial stream network (SSN) models to predict DOC across the stream network and to improve our understanding of the controls on DOC concentrations. Spatially, we found no obvious wildfire signal – instead, we observed a pattern of increasing DOC concentrations from the high-elevation headwaters to the sub-basin outlet, while the mainstem maintained consistently low DOC concentrations. This suggests that effects from large wildfires may be “averaged” out at higher stream orders and larger spatial scales. When we grouped DOC concentrations by burn severity group, we observed a significant decrease in the variability of DOC concentrations in the moderate and high burn severity sub-catchments. However, our SSN models were able to predict decreases in DOC concentrations with increases in burn severity across the stream network. Decreases in DOC concentrations were also highly variable across seasonal wetness conditions, with the greatest (–1.40 to –1.64 mg L –1 ) decrease occurring in the high-severity group during the wetting season. Additionally, our models indicated that in all seasons, baseflow index was more influential in predicting DOC concentrations than burn severity was, indicating that groundwater discharge can obscure the impacts of wildfire in a stream network. Overall, our results suggested that landscape characteristics can regulate the DOC response to wildfire. Moreover, our results also indicated that the seasonal timing of sampling can influence the observed response of DOC concentrations to wildfire.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction

Deep learning models have shown promise in reservoir inflow prediction, yet their performance often deteriorates when applied to different reservoirs due to distributional differences, referred to as the domain shift problem. Domain generalization (DG) solutions aim to address this issue by extracting domain-invariant representations that mitigate errors in unseen domains. However, in hydrological settings, each reservoir exhibits unique inflow patterns, while some metadata beyond observations like spatial information exerts indirect but significant influence. This mismatch limits the applicability of conventional DG techniques to many-domain hydrological systems. To overcome these challenges, we propose HydroDCM, a scalable DG framework for cross-reservoir inflow forecasting. Spatial metadata of reservoirs is used to construct pseudo-domain labels that guide adversarial learning of invariant temporal features. During inference, HydroDCM adapts these features through light-weight conditioning layers informed by the target reservoir’s metadata, reconciling DG’s invariance with location-specific adaptation. Experiment results on 30 real-world reservoirs in the Upper Colorado River Basin demonstrate that our method substantially outperforms state-of-the-art DG baselines under many-domain conditions and remains computationally efficient.

Hu, Pengfei [ORNL] (ORCID:0009000367130950)↗

DOE OSTI2022

Model predictive control for active insulation in building envelopes

Active insulation systems (AISs) refer to building envelopes with insulation materials that can change their thermal conductivity and are coupled with thermal mass to reduce building energy consumption and peak power. In this research, a novel optimal control approach is proposed to evaluate the maximum theoretical energy and cost-saving potential of AISs. A time-varying model predictive control (TV-MPC) controller was used to optimally select the AIS mode and simultaneously determine the operation of the heating, ventilation and air conditioning (HVAC) system so that the maximum saving potential of the entire system can be realized. To comprehensively evaluate the power shifting flexibility of AISs, two optimization objectives—minimizing weekly electric energy consumption and minimizing weekly electricity cost—were considered. The summer season simulation results show that under the first objective, more than 50% electric and thermal energy was saved when the upper boundary of the indoor air temperature was set to 25 °C. Furthermore under the second optimization objective, 38% of the cost was saved. It can be expected that the developed approach can be easily applied to multiple types of AISs with different mechanisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Cyber-Attack Detection for Active Neutral Point Clamped (ANPC) Photovoltaic (PV) Converter using Kalman Filter

With the upgrading of communication technology, cyber threats to power converters are increasing. In this paper, a model-based cyber-attack detection methodology is proposed for the interleaved Active neutral point clamped (ANPC) Photovoltaic (PV) converter. The proposed methodology identifies cyber-attacks using two estimations based on the Kalman filter and the state-space model of the ANPC PV converter. The residual between the two estimations is analyzed from a statistical perspective. Based on the Cumulative Sum (CUSUM) Control Chart, the standard errors shift of the residual is used to identify cyber-attacks. Besides, to validate the feasibility of the proposed methodology, several conditions are considered in the simulation, including white noise in the sensor, irradiance variation, and cyber-attacks in the PV converter. Furthermore, the simulation result demonstrates the proposed method can identify cyber-attacks in the ANPC PV converter.

14 SOLAR ENERGY↗

DOE OSTI2021

Exploring the Effects of Emplacement Conditions on Explosion P/S Ratios across Local to Regional Distances

High-frequency (~> 2 Hz) seismic P/S amplitude ratios are well-established as a discriminant to distinguish between natural earthquakes and underground explosions at regional distances (~200–1500 km). As research shifts toward identifying lower-yield events, work has begun to investigate the potential of this discriminant for use at local distances (<200 km), in which initial results raise questions about its effectiveness. Here, we utilize data from several chemical explosion experiment series at the Nevada National Security Site in southern Nevada in the United States to study explosion Pg/Lg ratios across the range of local to regional distances. Additionall, the experiments are conducted over differing emplacement conditions, with contrasting geologies and a variety of yields and depths of burial, including surface explosions. We first establish the similarities of Pg/Lg ratios from chemical explosions to those from historic nuclear tests and conclude that, as previous data have suggested, chemical explosion ratios are good proxies for nuclear tests. We then examine Pg/Lg ratios from the new experiment series as functions of distance, yield, depth of burial, and scaled depth of burial (SDOB). At far-local and regional distances, we observe consistently higher ratios from hard-rock explosions compared to ones in a weaker dry alluvium medium, consistent with prior regional distance results. No other trends with yield, depth of burial, or SDOB are strongly evident. Scatter in the observed ratios is very high, particularly at the shortest event-to-station distances, suggesting that small-scale path effects play a significant role. On average, the local distance explosion Pg/Lg ratios show remarkable consistency across all the variations in emplacement. Explosion source models will need to reproduce these results.

58 GEOSCIENCES↗

DOE OSTI2022

Phosphate Availability Modulates Root Exudate Composition and Rhizosphere Microbial Community in a Teosinte and a Modern Maize Cultivar

Domestication and breeding have affected interactions between plants and their microbiomes in ways that are only beginning to be understood but may have important implications for recruitment of rhizosphere microorganisms, particularly under stress conditions. We investigated the responses of a modern maize (Zea mays subsp. mays) cultivar and its wild relative, teosinte (Z. mays subsp. parviglumis), to different phosphate availabilities. We appraised responses of the plant-microbial holobiont to phosphate stresses by profiling root exudate metabolomes, and microbial communities in the root endosphere and rhizosphere. We also performed plate assays to quantify phosphate-solubilizing microorganisms from the rhizosphere. Although root exudate metabolite profiles were distinct between the teosinte and modern maize under high phosphate, both plants shifted exudate compositions in response to phosphate stress toward a common metabolite profile. Root and rhizosphere microbial communities also responded significantly to both plant type and the phosphate availability. A subset of bacterial and fungal taxa were differentially abundant under the different phosphate conditions, with each of the three conditions favoring different taxa. Both teosinte and maize rhizospheres harbored phosphate-solubilizing microorganisms under all growth conditions. These results suggest that the root exudation response to phosphate stress was conserved through the domestication of maize from teosinte, shifting exudation levels of specific metabolites. Although microbial communities also shifted, plate-based assays did not detect selective recruitment of phosphate solubilizers in response to phosphate availability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D

With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Lake sediment heatwaves under global warming

Lake sediment heatwaves, driven by rising global temperatures, pose emerging threats to freshwater ecosystems by altering sediment thermal regimes and intensifying sediment biogeochemical processes. Here we present a global-scale assessment of lake sediment heatwaves, examining their historical patterns and projecting future trends under various climate scenarios in 41,499 representative lakes worldwide. Using daily simulated lake sediment temperatures from 1981 to 2010 and future (2071-2100) projections under three Shared Socioeconomic Pathways (SSP126, SSP370, SSP585), we investigate lake sediment heatwave characteristics, including their duration, intensity, frequency, and seasonal timing, worldwide. Our results show that lake sediment heatwaves are generally more persistent and frequent than lake surface heatwaves, with sediment heatwaves in pelagic regions experiencing a significant lag relative to surface conditions. Under future climate scenarios, sediment heatwaves are projected to intensify, with their duration and frequency increasing substantially, particularly under SSP585. These shifts could exacerbate the production of greenhouse gases like methane and increase sediment respiration rates in lakes. This study highlights the need to account for sediment heatwaves in freshwater ecosystem management and climate adaptation strategies to mitigate future impacts.

Limnology↗

DOE OSTI2021

Direct current microplasma formation around microstructure arrays

We demonstrate the formation and transition behaviors of a microplasma around microstructure arrays at different gas pressures via two-dimensional particle-in-cell/Monte Carlo collision simulations. It is found that the microdischarge occurs outside the cathode microcavities at the lowest pressure and starts penetrating the microcavities with a curved sheath edge as the pressure increases. At higher pressure, coupled periodic microhollow cathode discharges (MHCDs) are formed inside the microcavities. Further increasing the gas pressure results in the disappearance of the MHCDs, and the dominant discharge shifts outside of the microcavity, locating above the protrusion tips. The effect of the space charge shielding on the discharge and the conditions for MHCD formation are discussed. The macroscopic discharge parameter scalings with the gas pressure and the electron kinetics are also examined. The results are helpful for deeply understanding the microplasma formation with nonplanar electrodes, which inform the scaling, design, and optimization of microplasma array devices across a wide range of pressure regimes in practical applications.

42 ENGINEERING↗