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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A comparative study of mechanical and chemical durability of non-wetting superhydrophobic and lubricant-infused surfaces

Fabrication of bioinspired non-wetting superhydrophobic surfaces (SHS) and lubricant-infused surfaces (LIS) has been studied extensively on a variety of materials. In contrast, durability of the surfaces exposed to harsh mechanical and chemical environments has been the subject of little attention. This study considers the mechanical and chemical durability of SHS and LIS copper surfaces fabricated via facile electrodeposition and chemical etching methods. The as-fabricated surfaces demonstrate excellent non-wetting characteristics with water contact angle of 160° and sliding angle below 5°. The surfaces are subject to mechanical wear through scratch test and water jet impingement at 15 psi and 20 psi as well as accelerated corrosion following the ASTM-E407 standard. The performance of the electrodeposited and etched non-wetting surfaces is systematically assessed in terms of contact and sliding angles and corrosion rate in a simulated marine environment. All surfaces are shown to be robust to mechanical wear after scratch test, with excellent stability of contact and sliding angles, and up to two orders of magnitude reduced corrosion rate compared to bare copper surface. SHS retained steadfast non-wetting characteristics under high-pressure water jet tests compared to the other surfaces while LIS, regardless of texturing method, showed one to two orders of magnitude reduced corrosion rate compared to bare copper surface throughout water jet impingement and chemical durability tests. The study presents for the first time a systematic comparison of durability of SHS and LIS through a common set of fabrication and testing protocol and helps identify appropriate non-wetting surfaces and fabrication methods based on the use environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nanoscale Mg-Depleted Layers Slow Carbonation of Forsterite (Mg 2 SiO 4 ) When Water Is Limited

Passivation of silicate surfaces by accumulated reaction products is an obstacle to efficient CO 2 mineralization. In this study, we investigate a unique passivation effect during the carbonation of the basalt mineral forsterite (Mg 2 SiO 4 ) in humid supercritical CO 2 (50 °C, 90 bar). Using in situ high-pressure infrared spectroscopy, we demonstrate that dissolution of forsterite into a thin water film slows significantly after reaction for ˜24 h, even under far-from-equilibrium conditions. Further, 29 Si magic angle spinning nuclear magnetic resonance spectroscopy detects a highly polymerized amorphous silica at this stage. On the basis of transmission electron microscopy and energy dispersive X-ray spectroscopy, we show that the silica is present as a Mg-depleted layer that is just 2–3 nm thick on the reacted forsterite particles. The decrease in the level of forsterite dissolution in the presence of an extraordinarily thin Mg-depleted layer can be strongly linked to properties of the thin fluid film at the surface, highlighting the importance of water during mineral carbonation. This study furthers our understanding of silicate mineral carbonation under select low-water, humidified fluid conditions relevant to basaltic geologic reservoirs, recovery of critical elements by carbonation of mafic ores, and sequestration of atmospheric CO 2 by enhanced rock weathering.

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

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Roles of Oil–Water Interfaces in Forming Ultrasmall CaSO 4 Nanoparticles

In natural and engineered environmental systems, calcium sulfate (CaSO 4 ) nucleation commonly occurs at dynamic liquid–liquid interfaces. Although CaSO 4 is one of the most common minerals in oil spills and oil–water separation, the mechanisms driving its nucleation at these liquid–liquid interfaces remain poorly understood. Here, in this study, using in situ small-angle X-ray scattering (SAXS), we examined CaSO 4 nucleation at oil–water interfaces and found that within 60 minutes of reaction, short rod-shaped nanoparticles (with a radius of gyration (R g ) of 17.2 ± 2.7 nm and a length of 38.2 ± 5.8 nm) had formed preferentially at the interfaces. Wide-angle X-ray scattering (WAXS) analysis identified these nanoparticles as gypsum (CaSO 4 ·2H 2 O). In addition, spherial nanoparticles measuring 4.1 nm in diameter were observed at oil–water interfaces, where surface-enhanced Raman spectroscopy (SERS) revealed an elevated pH compared to the bulk solution. The negatively charged oil–water interfaces preferentially adsorb calcium ions, collectively promoting CaSO 4 formation there. CaSO 4 particle formation at the oil–water interface follows a nonclassical nucleation (N-CNT) pathway by forming ultrasmall amorphous spherical particles which then aggregate to form intermediate nanoparticles, subsequently growing into nanorod-shaped gypsum. These findings of this study provide insights into mineral scaling during membrane separation and can inform more efficient oil transport in energy recovery systems.

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

Pistia stratiotes L. Biochar for Sorptive Removal of Aqueous Inorganic Nitrogen

Biochar has proven effective in the remediation of excess nitrogen from soil and water. Excess nitrogen from agricultural fields ends up in aquatic systems and leads to reduced water quality and the proliferation of invasive species. This study aimed to assess the efficiency of chemically surface-modified biochar produced from invasive Pistia stratiotes L. for the adsorption of inorganic nitrogen (NH4+ and NO3−). Biochar structure was investigated using scanning electron microscopy, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, and inductively coupled plasma mass spectrometry. The results from adsorption experiments indicate that NH4+ removal was optimal (0.8–1.3 mg N g−1) at near-neutral pH levels (6.0–7.5), while NO3− removal was optimal (0.4–0.8 mg N g−1) under acidic pH conditions (4.8–6.5) using the modified biochar. These findings highlight the significance of solution pH, biochar morphology, and surface chemistry in influencing the adsorption of NH4+ and NO3−. However, further studies are necessary to assess the potential oxidative transformation of NH4+ to NO3− by biochar, which might have contributed to the reduction in NH4+ in the aqueous phase.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Shifts in Evapotranspiration Components During Heatwaves Alter Surface Cooling

Heatwave events significantly alter ecosystem water and energy balance and are often accompanied by extreme surface temperatures. Understanding how surface temperatures during such events are regulated by soil evaporation (E) and vegetation transpiration (T) remains limited due to challenges in partitioning total evapotranspiration (ET). Here, high-frequency turbulence methods are used to partition observed ET at 32 National Ecological Observatory Network sites across the contiguous United States. Heatwaves were defined as at least three consecutive days with daily maximum air temperature exceeding the site-specific 90th percentile of the 2019–2021 record. Across 268 identified events, the T/ET ratio decreased by 32% ± 16% relative to the non-heatwave baseline of 0.65, with greater reductions at lower biomass sites. The T/ET ratio was typically suppressed below non-heatwave conditions during the early and middle stages of the heatwave (first two-thirds of event duration), but was on average higher than non-heatwave baseline levels during late stages (final third) due to extremely low soil evaporation. Of the studied heatwaves, 71% of these had surface temperatures above 38°C in their late stage; however, heatwaves sustaining higher evaporation fluxes (upper tertile of observed fluxes) during the late stage were associated with relative surface temperature anomalies that were on average 45% lower than those of heatwaves with lower evaporation fluxes (lower tertile). The commensurate surface cooling induced by higher transpiration was only 2% during heatwaves, suggesting that transpiration has a limited ability to mitigate extreme surface temperatures. This study allows for improved prediction of ecosystem feedbacks under extreme thermal stress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

VIC-Global Parameter Dataset Sensitivity with the Variable Infiltration Capacity Model: Evaluating the importance of dynamic land surface parameters when using the VIC-Global parameter dataset

Accurate prediction of runoff is essential to water resources management, flood risk assessment, and ecosystem protection. However, many hydrological models still have relatively substantial limitations when representing the influence of land use and land cover (LULC) on runoff generation and routing. Changes in LULC, such as deforestation, urban expansion, agricultural intensification, and wetland loss, have been shown to alter the water balance at the land surface through fundamental hydrologic processes (e.g., interception, infiltration, evapotranspiration, and soil storage). However, it remains an open question what the exact magnitude and timing of these impacts are for the spatial and temporal scales commonly used in engineering applications. In this analysis we focus on one aspect of recent LULC change for assessing human impacts, which is urbanization. Specifically we seek to determine the impacts of urbanization on the magnitude and timing of surface runoff and baseflow in HUC-12 basins in Clark County, Nevada which has experienced rapid urbanization. We use the Variable Infiltration Capacity (VIC) hydrology model with a widely used off-the-shelf dataset of land surface parameters, VIC-Global, both of which have been commonly used in the past for water and energy balance modeling for large scale hydrologic studies. We examine two scenarios where the first scenario removes all urbanized land cover and parameterizes those areas of the basins as barren or open shrubland. The second scenario tests the opposite case where all areas of the basins are classified as urban regardless of their present classification. The results from the VIC model show there is a low sensitivity for daily surface runoff between scenarios. The daily baseflow values indicate similar low sensitivity to the classification change during specific periods, but then have substantial differences during other period when large precipitation events are occurring. This is likely due to the assumed parameter values for the urban land cover classification made by the VIC-Global dataset. Using a static land cover parameterization is reasonable for large domain hydrology models that are being used for near-term planning horizons (<30 years). However, longer planning horizons where feedbacks between the atmosphere and land surface are important, especially in transient climate situations, considerations for how to update land surface parameters should be incorporated.

42 ENGINEERING↗
DOE OSTI2024

Inverse design of pore wall chemistry and topology through active learning of surface group interactions

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. Furthermore, this proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of Surface Defects on WO 3 Photoelectrodes for Catalyzing Chloride Oxidation in Water

Tungsten oxide (WO 3 ) is an n-type semiconductor due to oxygen vacancies (□ O •• in Kroger-Vink notation) or surface protonation as H x WO 3 . It is one of the few acid-stable oxides under large positive bias, which makes WO 3 ideal for interrogating the mechanism of the chloride oxidation reaction (COR). The large, positive valence band edge of ∼3 eV provides the overpotential necessary to carry out the COR, but the reaction competes with the oxygen-evolution reaction in water. The □ O •• defect density can be controlled by the atmosphere under which the material is annealed, so WO 3 films were prepared by a spin-coating method from an ammonium metatungstate precursor annealed at 500 °C under air, flowing O 2 , and flowing argon. Annealing the films in a flowing O 2 atmosphere hinders the formation of □ O ••, and annealing in Ar leads to greater surface W 6+ , likely due to expelling intercalated H + . The saturated photocurrent density (j ph ) is highest in films with the greatest concentration of W 5+ and greatest concentration of oxide defects: (0.66 mA/cm 2 annealed in air, 0.58 mA/cm 2 annealed in Ar, and 0.49 mA/cm 2 annealed in O 2 , reported at 1.5 V vs Ag/AgCl, pH 3 (before the onset of a dark reaction). The defect concentrations are determined by X-ray photoelectron spectroscopy. In all cases the Faradaic efficiency for the COR is near unity. Finally, we demonstrate that W 5d states can be probed by ligand K-edge X-ray absorption near-edge spectroscopy via pre-edge (Cl 1s → W 5d) transitions, lower in energy than the ligand-centered (Cl 1s → 4p) transition. We use this analysis to show the presence of W─Cl covalent bonds on the WO 3 films post-COR, corroborated by DFT calculations. Furthermore, this result stands in contrast to the commonly assumed mechanistic proposal invoking outer-sphere electron transfer to a physisorbed chloride ion.

Cl K-edge↗
DOE OSTI2023

Multiple redox mechanisms for water-gas shift reaction on Fe 3 O 4 (1 1 1) surface: A density functional theory and mean-field microkinetic modeling study

In this work, we investigated redox mechanisms for the high temperature (HT) water–gas shift reaction (WGSR) on the Fe 3 O 4 (1 1 1) surface using density functional theory (DFT) calculations and mean-field microkinetic modeling (MKM). The redox pathways branched into three Langmuir-Hinshelwood processes (LH1, LH2 and LH3) and one Mars-van-Krevelen (MVK) process (in the presence of oxygen vacancy) from multidentate binding of CO and CO 2 over four available reactive sites (Fe oct2 , Fe tet1 , Fe bridge, and O1). We found that the LH1 and LH2 processes have CO adsorption at a single iron site (Fe oct2 or Fe tet1 ), while the LH3 and MVK processes have stronger chemisorption of CO or CO 2 by both the Fe oct2 site and the O 1 site. From the mechanistic study of these reaction path, we recognized that availability of O 1 sites was key to proceed to either CO oxidation by the single site (LH1, LH2) or by the dual site (LH3, MVK). We observed that the reaction energetics were significantly different in the CO oxidation steps, where the single or dual site results in markedly different apparent activation energy (73–281 kJ/mol) and reaction rates (10 -3 –10 -10 mol∙m -2 ∙s -1 ) among the four reaction mechanisms. The utilization of mean field MKM with DFT reaction energetics helps explain the experimental debates for the catalytic reaction details as well as providing a possible direction to engineer the catalyst with higher activity.

42 ENGINEERING↗
DOE OSTI2022

Microbial Community Structure and Ecological Networks during Simulation of Diatom Sinking

Microbial-mediated utilization of particulate organic matter (POM) during its downward transport from the surface to the deep ocean constitutes a critical component of the global ocean carbon cycle. However, it remains unclear as to how high hydrostatic pressure (HHP) and low temperature (LT) with the sinking particles affects community structure and network interactions of the particle-attached microorganisms (PAM) and those free-living microorganisms (FLM) in the surrounding water. In this study, we investigated microbial succession and network interactions in experiments simulating POM sinking in the ocean. Diatom-derived 13C- and 12C-labeled POM were used to incubate surface water microbial communities from the East China Sea (ECS) under pressure (temperature) of 0.1 (25 °C), 20 (4 °C), and 40 (4 °C) MPa (megapascal). Our results show that the diversity and species richness of the PAM and FLM communities decreased significantly with HHP and LT. Microbial community analysis indicated an increase in the relative abundance of Bacteroidetes at high pressure (40 MPa), mostly at the expense of Gammaproteobacteria, Alphaproteobacteria, and Gracilibacteria at atmospheric pressure. Hydrostatic pressure and temperature affected lifestyle preferences between particle-attached (PA) and free-living (FL) microbes. Ecological network analysis showed that HHP and LT enhanced microbial network interactions and resulted in higher vulnerability to networks of the PAM communities and more resilience of those of the FLM communities. Most interestingly, the PAM communities occupied most of the module hubs of the networks, whereas the FLM communities mainly served as connectors of the modules, suggesting their different ecological roles of the two groups of microbes. These results provided novel insights into how HHP and LT affected microbial community dynamics, ecological networks during POM sinking, and the implications for carbon cycling in the ocean.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Wave-powered water pump for upwelling in aquaculture: Numerical model and ocean test

Wave-powered upwelling can increase the productivity and survivability of several aquaculture species. This enhancement is due to transporting cold, nutrient-rich ocean water, typically found lower in the water column, to the surface. Macroalgaes, like kelp, exhibit increased growth from these altered conditions. The University of New Hampshire’s (UNH) wave-powered water pump (wave pump) is a point absorber wave energy converter (WEC) that uses ocean waves to create relative motion between a spar buoy and a concentric float which drives an internal pump. A numerical model of the wave pump was developed using WEC-Sim to predict device performance in the ocean. Wave pump performance was evaluated during a five day ocean test near Appledore Island in Maine in March 2023, where volumetric flow rate, relative distance between spar and float, and wave conditions were measured. These data were then used for numerical model validation. The ocean deployment recorded the device’s performance in a variety of sea states, with average significant wave heights up to 0.7 m. The ocean test data were compared to the WEC-Sim numerical model of the device with favorable results. Average values of device stroke period, stroke height, and flow rate agreed between the ocean test and model data to within approximately 16 to 22%. Furthermore, the validated numerical model provides a valuable tool for improving the design and developing a commercial-scale, wave-powered water pump for use in aquaculture.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Surfactant inhibition mechanisms of carbonate mineral dissolution in shale

Surfactants are common additives to hydraulic fracturing and enhanced oil recovery (EOR) fluids, and are under consideration for amendment to supercritical carbon dioxide for geological carbon sequestration (GCS). The effect of a common anionic surfactant, internal olefin sulfonate (IOS), on mineral dissolution from shale into brine was evaluated. When added to brine at concentrations exceeding the critical micelle concentration (94 mg/L), IOS inhibited carbonate mineral dissolution in an Eagle Ford shale, as well as dissolution of optical quality calcite (the dominant carbonate in the shale). Laser profilometry images provide spatial resolution across > 3 orders of magnitude, and indicate that IOS addition to brine both enhances the formation of new etch pits in calcite, and impedes their further growth. Time-of-flight secondary ion mass spectrometry surface profiles show for the first time that IOS preferentially adsorbs at calcite pit edges versus flat calcite surfaces (i.e., terraces). Surface pressure calculations, sulfur K-edge near edge X-ray absorption fine structure (NEXAFS) spectroscopy results, and density functional theory (DFT) calculations support this observation; the DFT results indicate that the sulfonate head group of the IOS molecule binds strongly to the calcite step site as compared to the terrace site. The S K-edge NEXAFS results indicate that IOS adsorbed more to etched calcite surfaces compared to smooth calcite surfaces. Overall, the results indicate that weak adsorption on flat calcite surfaces (i.e., terraces) disrupts water structure and enhances mass transfer of dissolution, while strong adsorption on calcite pit edges displaces adsorbed water and inhibits further etch pit growth. This work provides the first direct evidence of preferential adsorption of IOS to etched calcite surfaces and links it to macroscopic dissolution kinetics. Finally, this work has implications for surfactant-containing fluids used in hydraulic fracturing, EOR and potentially GCS for subsurface injection into carbonate rich reservoirs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SPRUCE Outflow Chemistry Data for Experimental Plots Beginning in 2016

This data set includes the chemistry of outflow waters in the SPRUCE experiment plots located in the S1 bog of the USDA Forest Service Marcell Experimental Forest (MEF) in northern Minnesota, 40 km north of Grand Rapids. These data are post-treatment data from the warming and elevated carbon dioxide (CO2) treatments associated with the SPRUCE experiment. There are ten experimental plots in SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). Sample collection and analyses started in March of 2016 and will continue for the duration of the experiment. Samples were analyzed for pH, specific conductivity, anion concentrations (chloride, sulfate), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon (TOC) concentrations. Subsets of the samples have been analyzed for natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O), dissolved carbon dioxide (δ13C-CO2), and dissolved methane (δ13C-CH4), and concentrations of total mercury (Thg), methylmercury (MeHg), ferrous iron (Fe2+), ferric iron (Fe3+), dissolved inorganic carbon (DIC), and dissolved methane (CH4).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

What Are the Similarities and Differences in Marine Boundary Layer Cloud and Drizzle Microphysical Properties During the ACE–ENA and MARCUS Field Campaigns?

This study compares macrophysical and microphysical properties of single-layered, liquid-dominant MBL clouds from the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) (above 60°S) and the ARM East North Atlantic (ENA) site during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) field campaign. A total of 1,136 (16.5% of clouds) and 6,034 5-min cloud samples are selected from MARCUS and ARM ENA in this study. MARCUS clouds have higher cloud-top heights, thicker cloud layers, larger liquid water path, and colder cloud temperatures than ENA. Thinner, warmer MBL clouds at ENA can contain higher layer-mean liquid water content due to higher cloud and ocean surface temperatures along with greater precipitable water vapor (PWV). MARCUS has a higher drizzle frequency rate (71.8%) than ENA (45.1%). Retrieved cloud and drizzle microphysical properties from each field campaign show key differences. MARCUS clouds feature smaller cloud droplets, whereas ENA clouds have larger cloud droplets, especially at the upper region of the cloud. From cloud top to cloud base, drizzle drop sizes increase while number concentrations decrease. Drizzle drop radius and number concentration decrease from cloud base to drizzle base due to net evaporation, and MARCUS' lower specific humidity leads to a higher drizzle base than ENA. In conclusion, the broader surface pressure and lower tropospheric stability (LTS) distributions during MARCUS have demonstrated that there are different synoptic patterns for selected cases during MARCUS with less PWV, while ENA is dominated by high pressure systems with nearly doubled PWV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Generation of reactive species in water film dielectric barrier discharges sustained in argon, helium, air, oxygen and nitrogen

Activation of liquids with atmospheric pressure plasmas is being investigated for environmental and biomedical applications. When activating the liquid using gas plasma produced species (as opposed to plasmas sustained in the liquid), a rate limiting step is transport of these species into the liquid. To first order, the efficiency of activating the liquid is improved by increasing the ratio of the surface area of the water in contact with the plasma compared to its volume—often called the surface-to-volume ratio (SVR). Maximizing the SVR then motivates the plasma treatment of thin films of liquids. In this paper, results are discussed from a computational investigation using a global model of atmospheric pressure plasma treatment of thin water films by a dielectric barrier discharge (DBD) sustained in different gases (Ar, He, air, N 2 , O 2 ). The densities of reactive species in the plasma activated water (PAW) are evaluated. The residence time of the water in contact with the plasma is increased by recirculating the PAW in plasma reactor. Longer lived species such as H 2 O 2aq and NO 3 - aq accumulate over time (aq denotes an aqueous species). DBDs sustained in Ar and He are the most efficient at producing H 2 O 2aq , DBDs sustained in argon produces the largest density of NO 3 - aq with the lowest pH, and discharges sustained in O 2 and air produce the highest densities of O 3aq . Finally, comparisons to experiments by others show agreement in the trends in densities in PAW including O 3aq , OH aq , H 2 O 2aq and NO 3 - aq , and highlight the importance of controlling desolvation of species from the activated water.

42 ENGINEERING↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗