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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Comprehensive study of carbon dioxide adsorption in the metal–organic frameworks M 2 (dobdc) (M = Mg, Mn, Fe, Co, Ni, Cu, Zn)
Analysis of the CO 2 adsorption properties of a well-known series of metal–organic frameworks M 2 (dobdc) (dobdc 4– = 2,5-dioxido-1,4-benzenedicarboxylate; M = Mg, Mn, Fe, Co, Ni, Cu, and Zn) is carried out in tandem with in situ structural studies to identify the host–guest interactions that lead to significant differences in isosteric heats of CO 2 adsorption. Neutron and X-ray powder diffraction and single crystal X-ray diffraction experiments are used to unveil the site-specific binding properties of CO 2 within many of these materials while systematically varying both the amount of CO 2 and the temperature. Unlike previous studies, we show that CO 2 adsorbed at the metal cations exhibits intramolecular angles with minimal deviations from 180°, a finding that indicates a strongly electrostatic and physisorptive interaction with the framework surface and sheds more light on the ongoing discussion regarding whether CO 2 adsorbs in a linear or nonlinear geometry. This has important implications for proposals that have been made to utilize these materials for the activation and chemical conversion of CO 2 . For the weaker CO 2 adsorbents, significant elongation of the metal–O(CO 2 ) distances are observed and diffraction experiments additionally reveal that secondary CO 2 adsorption sites, while likely stabilized by the population of the primary adsorption sites, significantly contribute to adsorption behavior at ambient temperature. In conclusion, density functional theory calculations including van der Waals dispersion quantitatively corroborate and rationalize observations regarding intramolecular CO 2 angles and trends in relative geometric properties and heats of adsorption in the M 2 (dobdc)–CO 2 adducts.
Large-Scale Synthesis and Comprehensive Structure Study of δ‑MnO2
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Comprehensive study of the electronic and optical behavior of highly degenerate p-type Mg-doped GaN and AlGaN
The bulk and 2-dimensional (2D) electrical transport properties of heavily Mg-doped p-type GaN films grown on AlN buffer layers by Metal Modulated Epitaxy are explored. Distinctions are made between three primary p-type conduction mechanisms: traditional valence band conduction, impurity band conduction, and 2D conduction within a 2D hole gas at a hetero-interface. The bulk and 2D contributions to the overall carrier transport are identified and the relative contributions are found to vary strongly with growth conditions. Films grown with III/V ratio less than 1.5 exhibit high hole concentrations exceeding 2 × 10{sup 19} cm{sup −3} with effective acceptor activation energies of 51 meV. Films with III/V ratios greater than 1.5 exhibit lower overall hole concentrations and significant contributions from 2D transport at the hetero-interface. Films grown with III/V ratio of 1.2 and Mg concentrations exceeding 2 × 10{sup 20} cm{sup −3} show no detectable inversion domains or Mg precipitation. Highly Mg-doped p-GaN and p-AlGaN with Al fractions up to 27% similarly exhibit hole concentrations exceeding 2 × 10{sup 19} cm{sup −3}. The p-GaN and p-Al{sub 0.11}Ga{sub 0.89}N films show broad ultraviolet (UV) photoluminescence peaks, which intercept the valence band, supporting the presence of a Mg acceptor band. Finally, a multi-quantum-well light-emitting diode (LED) and p-i-n diode are grown, both of which demonstrate rectifying behavior with turn-on voltages of 3–3.5 V and series resistances of 6–10 Ω without the need for any post-metallization annealing. The LED exhibits violet-blue luminescence at 425 nm, while the p-i-n diode shows UV luminescence at 381 nm, and both devices still show substantial light emission even when submerged in liquid nitrogen at 77 K.
Biopolymer‐assisted Synthesis of P‐doped TiO 2 Nanoparticles for High‐performance Lithium‐ion Batteries: A Comprehensive Study
Abstract TiO 2 material has gained significant attention for large‐scale energy storage due to its abundant, low‐cost, and environmentally friendly properties, as well as the availability of various nanostructures. Phosphorus doping has been established as an effective technique for improving electronic conductivity and managing the slow ionic diffusion kinetics of TiO 2 . In this study, non‐doped and phosphorus doped TiO 2 materials were synthesized using sodium alginate biopolymer as chelating agent. The prepared materials were evaluated as anode materials for lithium‐ion batteries (LIBs). The electrodes exhibit remarkable electrochemical performance, including a high reversible capacity of 235 mAh g −1 at 0.1 C and excellent first coulombic efficiency of 99 %. An integrated approach, combining operando XRD and ex‐situ XAS, comprehensively investigates the relationship between phosphorus doping, material structure, and electrochemical performance, reinforced by analytical tools and first principles calculations. Furthermore, a full cell was designed using 2 %P‐doped TiO 2 anode and LiFePO 4 cathode. The output voltage was about 1.6 V with high initial specific capacity of 148 mAh g −1 , high rate‐capability of 120 mAh g −1 at 1 C, and high‐capacity retention of 96 % after 1000 cycles at 1 C.
Sustainable agricultural residue removal for bioenergy: A spatially comprehensive US national assessment
Not Available
International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station
Abstract The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward (Bowyer et al., 2013). Fission-based production of 99Mo for medical purposes also releases radioxenon isotopes to the atmosphere (Saey, 2009). One of the ways to mitigate the effect of emissions from medical isotope production is the use of stack monitoring data, if it were available, so that the effect of radioactive xenon emissions could be subtracted from the effect from a presumed nuclear explosion, when detected at an IMS station location. To date, no studies have addressed the impacts the time resolution or data accuracy of stack monitoring data have on predicted concentrations at an IMS station location. Recently, participants from seven nations used atmospheric transport modeling to predict the time-history of 133Xe concentration measurements at an IMS station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well (a high composite statistical model comparison rank or a small mean square error with the measured values). The results suggest release data on a 15 min time spacing is best. The model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. Further research is needed to identify optimal methods for selecting ensemble members and those methods may depend on the specific transport problem. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. The one submission that best predicted small concentrations also included releases from nuclear power plants. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in discriminating those releases from releases from a nuclear explosion.
Comprehensive Monitoring for Heterogeneous Geographically Distributed Storage
Storage capacity at CMS Tier-1 and Tier-2 sites reached over 100 Petabytes in 2014, and will be substantially increased during Run 2 data taking. The allocation of storage for the individual users analysis data, which is not accounted as a centrally managed storage space, will be increased to up to 40%. For comprehensive tracking and monitoring of the storage utilization across all participating sites, CMS developed a space monitoring system, which provides a central view of the geographically dispersed heterogeneous storage systems. The first prototype was deployed at pilot sites in summer 2014, and has been substantially reworked since then. In this paper we discuss the functionality and our experience of system deployment and operation on the full CMS scale.
Comprehensive Database of Environmental Mitigations Extracted from FERC-Licensed Hydropower Projects Using Artificial Intelligence Techniques, 1998-2023
This dataset provides a comprehensive inventory of environmental mitigation measures required by Federal Energy Regulatory Commission (FERC) licensed hydropower facilities from 461 licenses that were issued from 1998 to 2023. These licenses constitute 446 of the 1015 FERC projects that were active at the end of 2023. 17,612 mentions of environmental mitigations were identified and categorized in 128 unique categories. Mitigations were identified using a Natural Language Processing (NLP) approach, specifically with a Bidirectional Encoder Representations from Transformer (BERT) model. Model-derived results were then reviewed and updated by a subject matter expert as needed. This dataset introduces important enhancements to previous efforts to inventory environmental mitigations, such as including associated license text for each mitigation, tracking the number of instances a mitigation was identified within a license, and providing improved location information. These enhancements significantly expand the dataset's utility, offering greater analytical capabilities and ensuring reproducibility. The dataset is downloadable as a zip file containing the metadata and dataset files.
Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011
Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2 , SO 2 , PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.
A Comprehensive Analysis of the Interphasial and Structural Evolution over Long–Term Cycling of Ultrahigh–Nickel Cathodes in Lithium–Ion Batteries
Ultrahigh-Ni layered oxides hold great promise as high-energy-density cathodes at an affordable cost for lithium-ion batteries, yet their practical application is greatly hampered by the poor cyclability. Herein, by employing LiNi 0.94 Co 0.06 O 2 as a model cathode in a full-cell configuration, the interphasial and structural evolution processes of ultrahigh-Ni layered oxides are systematically investigated over the course of their service life (1500 cycles). By applying advanced analytic techniques (e.g., Li-isotope labeling, region-of-interest method), the dynamic chemical evolution on the cathode surface is revealed with spatial resolution, and the correlation between lattice distortion and cathode surface reactivity is established. Benefiting from in situ X-ray diffraction (XRD) analysis, the ultrahigh-Ni layered oxide is demonstrated to undergo dual-phase reaction mechanisms with huge lattice variation, which leads to a decrease in crystallinity and secondary particle pulverization. Furthermore, the critical impact of cathode surface reaction on the graphite anode–electrolyte interphase (AEI) is revealed at nanometer scale, and a universal chemical/physical evolution process of the AEI is illustrated, for the first time. Finally, the practical viability of ultrahigh-Ni layered oxides is demonstrated through Al-doping strategy. Finally, this work presents a comprehensive understanding of the structural and interphasial degradation of ultrahigh-Ni layered oxide cathodes for developing high-energy-density lithium-ion batteries.
GeoSoilEnviroCARS (Sector 13) at the Advanced Photon Source: a comprehensive synchrotron radiation facility for Earth science research at ambient and extreme conditions
GeoSoilEnviroCARS (GSECARS) is a comprehensive analytical laboratory for Earth and environmental science research using X-ray beams from the Advanced Photon Source, Argonne National Laboratory. State-of-the-art instruments are available for (1) high-pressure/high- or low-temperature diffraction, total scattering, and spectroscopy (Brillouin, Raman, and VIS-IR) using the laser heated diamond anvil cell (DAC); (2) high-pressure/high-temperature diffraction, scattering, and imaging as well as acoustic emission (AE) and ultrasonics using the large-volume press (LVP); (3) powder, single crystal, and surface/interface diffraction; (4) X-ray absorption fine structure spectroscopy; (5) X-ray fluorescence microprobe analysis; and (6) microtomography. As shown here, experiments are facilitated by senior level staff who collaborate on all aspects of the analytical work including experiment design, sample preparation, data collection, data interpretation, and publication preparation. Both technical and scientific synergies occur as a result of the intimate association of the various techniques and scientists experienced in the applications of synchrotron radiation to Earth, environmental, and planetary science problems. The facility includes state-of-the-art instrumentation designed and built in-house, including custom X-ray optics, online and offline laser-based systems, specialized sample environments and positioning systems, as well as pixel-array and multi-crystal energy dispersive X-ray detectors, which are available to be shared among the experimental stations.
Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
Comprehensive study of a versatile polyol synthesis approach for cathode materials for Li-ion batteries
Abstract not provided
Multi-year application of WRF-CAM5 over East Asia-Part I: Comprehensive evaluation and formation regimes of O3 and PM2.5
Not Available
Radionuclide observables during the Integrated Field Exercise of the Comprehensive Nuclear-Test-Ban Treaty
Not Available
Machine learning for international freight transportation management: A comprehensive review
Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.