SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Robust, highly water-soluble quinone derivatives are efficiently prepared by a scalable electrosynthetic protocol employing low-cost commercially available precursors.
With enigmatic observations of enhanced reactivity of wet CO 2 -rich fluids with metal silicates, the mechanistic understanding of molecular processes governing carbonation proves critical in designing secure geological carbon sequestration and economical carbonated concrete technologies. Here, we use the first principle and classical molecular simulations to probe the impact of nanoconfinement on physicochemical processes at the rock–water–CO 2 interface. We choose nanoporous calcium–silicate–hydrate (C–S–H) and forsterite (Mg 2 SiO 4 ) as model metal silicate surfaces that are of significance in cement chemistry and geochemistry communities, respectively. We show that while a nanometer-thick interfacial water film persists at unsaturated conditions consistent with in situ infrared spectroscopy, the phase behavior of the water–CO 2 mixture changes from its bulk counterpart depending on the surface chemistry and nanoconfinement. We also observe enhanced solubility at the interface of water and CO 2 phases, which could amplify the CO 2 speciation rate. Additionally, through free energy calculations, we show that CO 2 could be found in a metastable state near the C–S–H surface, which can potentially react with surface water and hydroxyl groups to form carbonic acid and bicarbonate. These findings support the explicit consideration of nanoconfinement effects in reactive and non-reactive pore-scale processes.
The adoption of batteries across diverse applications requires electrode materials with a wider range of performance metrics, such as cost, safety, and material availability. Along the path to discovering new commercially viable materials, a fundamental understanding of chemical and atomic structure features that provide structural stability and effective ion transport is essential. In support of new understanding, we report the cycling behavior of metastable R-Nb 2 O 5 . R-Nb 2 O 5 adopts an ‘idealized’ V 2 O 5 structure, in which [NbO 6 ] octahedra alternate in edge- and corner-sharing resulting in ReO 3 -like slabs, whereas Wadsley–Roth materials have ReO 3 -like blocks, linked through edge-sharing octahedra at intersecting crystallographic shear planes. We find that this slab structure is stable during cycling, with minor atomic structure changes and cycling curves that are symmetric on discharge and charge, resembling the behavior of Wadsley–Roth materials more than other related materials, such as ReO 3 , V 2 O 5 , or Nb 3 O 7 F. Based on our findings, R-Nb 2 O 5 can serve as a ‘structural bridge’ between Wadsley–Roth block structures and V 2 O 5 , through which we can relate inter- and intra-polyhedral structures to cycling behavior and structural stability during cycling.
Using first-principles calculations here, we show that Mn and Cr layers under graphene exhibit almost zero magnetic moment due to anti-ferromagnetic order, while ferromagnetic coupling in Fe, Co, and Ni leads to large magnetic moment. The transition metal partially supported graphene, with a mixture of supported and pristine areas, exhibits an oscillatory electrostatic potential, thus alternating the electric field across the supported and pristine areas. Such an effect can be utilized to control mass transport and nanostructure self-organization on graphene at the atomic level.
Bioenergy with carbon capture and storage (BECCS) is considered a potential source of net negative carbon emissions and, if deployed at sufficient scale, could potentially help reduce carbon dioxide emissions and concentrations. However, the viability and economic consequences of large-scale BECCS deployment are not fully understood. We use the GCAM integrated assessment model to explore the potential global and regional economic impacts of BECCS. BECCS always needs a net subsidy to be deployed; it never produces net tax revenue. We show that by mid-century, in a world committed to limiting climate change to 2°C, carbon tax revenues have peaked and are rapidly approaching the point where climate mitigation is a net burden on general tax revenues. Assuming that the required policy instruments are available to support BECCS deployment, we consider its effects on regional fossil fuels and biomass trade patterns. We find that in a world committed to limiting climate change to 2°C, the absence of CCS harms fossil-fuel exporting regions, while the presence of CCS and BECCS allows greater continued use and export of fossil fuels. We also explore the relationship between carbon prices, food crop prices and BECCS. We show that the carbon price and food-crop prices are directly related. We also show that BECCS reduces the upward pressure on food crop prices exerted by carbon prices due to its effect on lowering carbon prices and lowering the total biomass demand in climate change mitigation scenarios. All of this notwithstanding, many challenges, both technical and institutional, remain to be addressed before BECCS could be deployed at scale.
Toluene is a volatile organic compound that is a common indoor contaminant. According to the U.S. Department of Health and Human Services, chronic toluene exposure negatively affects organ systems, such as nervous and respiratory, and acts as a fetotoxic agent in the development of humans. Toluene exposure causes damage to human myelin sheaths, thus we propose that damage to the fly nervous system will be similar to that seen in humans exposed to toluene. Our ultimate goal is to determine the effects of toluene exposure on developmental and neuronal processes in D. melanogaster . In this first phase, we hypothesize that toluene‐exposed adults, at the interpolated Lethal Exposure (LE 50 ), will demonstrate decreased fecundity and that offspring from toluene‐exposed females will have decreased survivability from the egg to adult stage. We developed a continuous flow system that delivers known concentrations of gaseous toluene to populations of D. melanogaster . Ten to twenty adult female flies per trial were exposed for 24 hours to known concentrations of toluene. Surviving females were collected, counted and mated to non‐exposed adult males. The toluene‐exposed females were placed on a colored agar plate to lay eggs for 24 hours. Eggs were counted to determine fecundity (number of eggs produced by a single female fly). Survivability of eggs to later life stages, was measured by counting number of larvae, pupae, and adults divided by number eggs, larvae, and pupae respectively. The interpolated LE 50 of gaseous toluene was between 1000 and 1500 ppm after 24‐hour exposure. Fecundity of toluene‐exposed females decreased by approximately 50% when compared to airexposed females. The survivability of offspring of air‐exposed flies from egg to larval stages was 84% higher than published studies. We observed that larval eclosure from eggs laid by toluene‐exposed females was 35–50% higher on days 1 and 2 when compared to larval eclosure from eggs of air‐exposed exposed females. On days 3–6 the eclosure rate was relatively similar. These data showed toluene's effects on fecundity and survivability were measurable, however, additional replicates are in progress to fully assess the life table characteristics of offspring of toluene‐exposed female flies. Further studies will focus on toluene's effect on nervous and reproductive organs of fruit flies, along with a study on the mutagenic effects of toluene on fly DNA. Support or Funding Information U.S. DOE, Hispanic‐Serving Institutions, STEM Articulation Grant P031C110128 This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Electron core-hole processes at absorption edges sport several signatures, primarily in the form of bound states and/or excitonic enhancement. Here, through analysis of the resonant-Raman Auger effect for the two-dimensional transition-metal dichalcogenide MoS 2 , we demonstrate that these effects have significant manifestations at the S K edge. We characterize two asymmetric excitonically enhanced edges: one at the fundamental band edge and one several electron volts above it following a second band gap that lies entirely within the unoccupied states, with the latter revealing an anomalous postcollision interaction effect. In conclusion, our interpretation is supported by comparison of both the photoemission valence-band spectrum and the S K-edge x-ray-absorption spectrum with electronic structure calculations and an ab initio solution of the Bethe-Salpeter equation that accurately accounts for the electron-core-hole interaction.
Network intrusion detection systems (NIDS) are commonly used to detect malware communications, including command-and-control (C2) traffic from botnets. NIDS performance assessments have been studied for decades, but mathematical modeling has rarely been used to explore NIDS performance. This paper details a mathematical model that describes a NIDS performing packet inspection and its detection of malware's C2 traffic. Here, the paper further describes an emulation testbed and a set of cyber experiments that used the testbed to validate the model. These experiments included a commonly used NIDS (Snort) and traffic with contents from a pervasive malware (Emotet). Results are presented for two scenarios: a nominal scenario and a “stressed” scenario in which the NIDS cannot process all incoming packets. Model and experiment results match well, with model estimates mostly falling within 95 % confidence intervals on the experiment means. Model results were produced 70-3000 times faster than the experimental results. Consequently, the model's predictive capability could potentially be used to support decisions about NIDS configuration and effectiveness that require high confidence results, quantification of uncertainty, and exploration of large parameter spaces. Furthermore, the experiments provide an example for how emulation testbeds can be used to validate cyber models that include stochastic variability.
The penetration of wind energy has increased significantly in the power grid in recent times. Although wind is abundant, environment-friendly, and cheap, it is variable in nature and does not contribute to system inertia as much as conventional synchronous generators. Coupled with the low inertia contribution, the generation intermittency of wind power leads to reliability and stability issues in the power system. Energy storage systems (ESSs) are among the most prominent alternatives to alleviate these concerns associated with high wind penetration. This paper proposes a planning strategy to size ESS for the reliability and frequency security of wind-rich power grids. A probabilistic methodology for ESS sizing is developed utilizing a composite reliability-based framework with sequential Monte Carlo simulation (MCS). The MCS generates composite reliability indices for the power system, which are employed to obtain the capacity for a reliability energy storage system (RESS). Simultaneously, the MCS-derived probability of synchronization of conventional generators is integrated into an analytical approach for sizing a frequency support energy storage system (FESS). The effect of wind farm dispersion across geographical regions is incorporated in the framework to study possible reductions in the ESS size while maintaining the system reliability and frequency security. Furthermore, the efficacy of the proposed strategy is demonstrated on the RTS-GMLC test system.
This paper presents a hierarchical control system to mitigate the variability of solar photovoltaic (PV) power plant and provide ancillary services to the electric grid without the need for additional non-solar resources. With coordinated management of each inverter in the system, the control system commands the power plant to proactively curtail a small fraction of its instantaneous maximum power potential, which gives the plant enough headroom to ramp up production from the overall power plant, for a service such as regulation reserve. This control system is practical for continuously changing cloud cover conditions in partially cloudy days. A case study from a site in Hawaii with one-second resolution solar irradiance data is used to verify the efficacy of the proposed control system. The proposed control algorithm is subsequently compared with the alternative control technology from the literature, the grouping control algorithm; the results show that the proposed hierarchical control system is over 10 times more effective in reducing generator mileage to support power fluctuations from solar PV power plants.
Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.
Objective . To evaluate the efficacy and safety of mesalamine in conjunction with probiotics for ulcerative colitis. Methods . Random controlled trials (RCTs) were searched in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and VIP (VIP Database for Chinese Technical Periodicals) from inception to October 2019. Methodological quality was assessed by the Cochrane Collaboration tool. The quality of evidence was rated by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Data analysis was carried out in Review Manager 5.3. Results . A total of fifteen studies met the criteria for inclusion. Thirteen studies reported the clinical efficacy, three studies provided data on the clinical symptom scores, two trials reported disease activity index, four studies evaluated endoscopic score, and twelve studies reported adverse events. For ulcerative colitis (UC), mesalamine and probiotics had better clinical efficacy than mesalamine alone (≤8 weeks: RR = 1.12, 95% CI: 1.07–1.18, P < 0.0001; >8 weeks: RR = 1.25, 95% CI: 1.11–1.41, P = 0.0003). On the clinical symptom scores, disease activity index, and endoscopic score, UC patients receiving mesalamine and probiotics had significant difference than patients receiving mesalazine alone (MD = −2.02, 95% CI: −3.28 to −0.76, P = 0.002; MD = −1.20, 95% CI: −1.76 to −0.65, P < 0.001; and MD = −0.42, 95% CI: −0.61 to −0.23, P < 0.0001, respectively). There was no statistically significant difference in adverse events between the two groups (RR = 0.88, 95% CI: 0.54 to 1.43, P = 0.60). Conclusion . Our meta‐analysis results supported that mesalamine and probiotics were effective and safe in treating ulcerative colitis.
Because the incidence of breast cancer increases decades after ionizing radiation exposure, aging has been implicated in the evolution of the tumor microenvironment and tumor progression. In this paper, we investigated radiation-induced carcinogenesis using a model in which the mammary glands of 10-month-old BALB/c mice were transplanted with Trp53-null mammary tissue 3 days after exposure to low doses of sparsely ionizing γ-radiation or densely ionizing particle radiation. Mammary transplants in aged, irradiated hosts gave rise to significantly more tumors that grew more rapidly than those in sham-irradiated mice, with the most pronounced effects seen in mice irradiated with densely ionizing particle radiation. Tumor transcriptomes identified a characteristic immune signature of these aggressive cancers. Consistent with this, fast-growing tumors exhibited an immunosuppressive tumor microenvironment with few infiltrating lymphocytes, abundant immunosuppressive myeloid cells, and high COX-2 and TGFβ. Only irradiated hosts gave rise to tumors lacking cytotoxic CD8 + lymphocytes (defined here as immune desert), which also occurred in younger irradiated hosts. These data suggest that host irradiation may promote immunosuppression. To test this, young chimera mice were fed chow containing a honeybee-derived compound with anti-inflammatory and immunomodulatory properties, caffeic acid phenethyl ester (CAPE). CAPE prevented the detrimental effects of host irradiation on tumor growth rate, immune signature, and immunosuppression. These data indicated that low-dose radiation, particularly densely ionizing exposure of aged mice, promoted more aggressive cancers by suppressing antitumor immunity. Dietary intervention with a nontoxic immunomodulatory agent could prevent systemic effects of radiation that fuel carcinogenesis, supporting the potential of this strategy for cancer prevention.
Effective flood simulation capabilities can tremendously support early warning and disaster prevention. To examine the applicability of a fully physics-based and high-performance flood simulation and forecasting modeling framework for a flood-prone region in Taiwan, we conduct a numerical experiment that couples the Weather Research and Forecasting (WRF) Model, WRF-Hydrological modeling system (WRF-Hydro), and the Two-Dimensional Runoff Inundation Toolkit for Operational Needs (TRITON) to perform integrated rainfall, streamflow, and flood simulations. Furthermore, we first use the coupled WRF and WRF-Hydro (WWH) to predict rainfall and streamflow and then drive TRITON with the predicted streamflow hydrographs to simulate flood depth and inundation area. With the refined spatial resolution and parameterization, this framework can better predict rainfall with reasonable spatial patterns. Although WWH could overestimate the amount of rainfall in some areas, the uncertain rainfall–streamflow predictions produce reasonable flood maps able to pinpoint regions at risk of flooding. In terms of model efficiency, the graphics processing unit–based computation can yield a speed-up factor as high as ∼13 compared to the central processing unit–based computation, promoting the efficacy of the coupled modeling framework in practical real-time flood forecasting.
The mission of Employee Health Services (EHS) at Sandia National Laboratories is to positively and efficiently impact the health of Sandia through patient-centered, cost-effective, community-connected care in support of its mission and people. We strive to continuously improve the delivery of health and wellness services. For the past few years, we have modeled our health programs around findings from the 2010 World Economics Forum (WEF): there are 8 top health risks and behaviors that drive 15 chronic conditions which account for 80% of the total health-care costs for all chronic illness worldwide. The WEF goes on to state that information and innovation are the keys to prevention, and EHS has decided to take a strong stand in both categories by utilizing health scorecards and department dashboards to visualize and share metrics with Sandia Leadership to foster improvements in employee wellness and optimize wellness offerings. Finally, these 2 types of information-sharing tools allow us to track the dollars spent and saved on our wellness programs, and show leadership where there is risk, where there is progress, and where there is need by providing current data that gives monthly, quarterly, and yearly feedback.
A key goal of NextGen Profiles' fleet utilization study was to conduct a comprehensive, strategic, and standardized assessment of the operational behavior and utilization patterns across EV and EVSE production-ready fleets. These data-driven insights were intended to inform current fleet management strategies and support future infrastructure planning, ensuring the effective adoption and adaptation of the growing EV fleet market. The study applied a series of metrics defined in NextGen Profiles to evaluate diverse fleet operations across various use cases, emphasizing trends in charging, routing, and other critical behaviors. The fleet utilization dataset includes these three sets of metrics from 17 EV fleets, each consisting of a wide range of vehicle types and operational categories, as well as two EVSE fleets. Data were collected from a variety of sources and reformatted into a unified structure before metric computation, ensuring consistency and comparability across all fleets. To protect confidentiality, all fleet metadata are anonymized, and the publicly released metric datasets are aggregated to an hourly cadence.
This archive contains model output, code, and scripts for simulations of coupled manganese-carbon cycling in temperate forest soil profiles. These model results were generated as part of a study investigating how manganese availability influences soil organic carbon stocks and demonstrating a new model framework for coupling carbon and manganese cycling. The simulations were in support of a manuscript: "Modeling interactive effects of manganese bioavailability, nitrogen deposition, and warming on soil carbon storage." The study addresses the research questions: How does Mn bioavailability, as driven by subsurface mineral properties, pH, and redox status, affect temperate forest soil organic carbon and litter carbon stocks?How is the relationship between Mn bioavailability and carbon cycling affected by changes in temperature and nitrogen deposition?"Model simulations were conducted in a reactive transport modeling framework using PFLOTRAN coupled to python. Multiple model simulations testing different Mn-bearing mineral solubilities, hydrological patterns, nitrogen deposition rates, and temperatures are included. Soil properties, including total and exchangeable Mn concentrations, are based on values reported for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), a temperate forested watershed in central Pennsylvania, U.S.A where Mn cycling through vegetation has been documented.File formats include netCDF (.nc), python script (.py), shell script (.sh), plain text PFLOTRAN input file (.in), and plain text PFLOTRAN database file (.dat), and gzipped tar archive (tar.gz).
This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.