Behavior of iodate substituted ettringite during aqueous leaching
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As interest in long duration effects of space habitation increases, understanding the behavior of model organisms living within the habitats engineered to fly them is vital for designing, validating, and interpreting future spaceflight studies. Only a handful of papers have previously reported behavior of mice and rats in the weightless environment of space (Andreev-Andrievskiy, et al., 2013; Cancedda et al., 2012; Ronca et al., 2008). The Rodent Research Hardware and Operations Validation Mission (Rodent Research-1; RR1) utilized the Rodent Habitat (RH) developed at NASA Ames Research Center to fly mice on the ISS. Ten adult (16-week-old) female C57BL6J mice were launched on September 21st, 2014 in an unmanned Dragon Capsule, and spent 37 days in flight. Here we report group behavioral phenotypes of the RR1 Flight (FLT) and environment-matched Ground Control (GC) mice in the RH during this long duration flight. Video was recorded for 34 days on the ISS, permitting daily assessments of overall health and well being of the mice, and providing a valuable repository for detailed behavioral analysis. As compared to GC mice, RR1 FLT mice exhibited the same range of behaviors, including eating, drinking, exploration, self- and allogrooming, and social interactions at similar or greater levels of occurrence. Overall activity was greater in FLT as compared to GC mice, with spontaneous ambulatory behavior, including organized circling or race-tracking behavior that emerged within the first few days of flight following a common developmental sequence, comprising the primary dark cycle activity of FLT mice. Circling participation by individual mice persisted throughout the mission. Analysis of group behavior over mission days revealed recruitment of mice into the group phenotype, coupled with decreasing numbers of collisions between circling mice. This analysis provides insights into the behavior of mice in microgravity, and clear evidence for the emergence of a distinctive, organized group behavior unique to the weightless space environment. Supported by the NASA Rodent Research Project, Space Biology Program, and Space Life Sciences Training Program.
As interest in long duration effects of space habitation increases, understanding the behavior of model organisms living within the habitats engineered to fly them is vital for designing, validating, and interpreting future spaceflight studies. Only a handful of papers have previously reported behavior of mice and rats in the weightless environment of space (Andreev-Andrievskiy, et al., 2013; Cancedda et al., 2012; Ronca et al., 2008). The Rodent Research Hardware and Operations Validation Mission (Rodent Research-1; RR1) utilized the Rodent Habitat (RH) developed at NASA Ames Research Center to fly mice on the ISS. Ten adult (16-week-old) female C57BL6J mice were launched on September 21st, 2014 in an unmanned Dragon Capsule, and spent 37 days in flight. Here we report group behavioral phenotypes of the RR1 Flight (FLT) and environment-matched Ground Control (GC) mice in the RH during this long duration flight. Video was recorded for 34 days on the ISS, permitting daily assessments of overall health and well being of the mice, and providing a valuable repository for detailed behavioral analysis. As compared to GC mice, RR1 FLT mice exhibited the same range of behaviors, including eating, drinking, exploration, self- and allogrooming,and social interactions at similar or greater levels of occurrence. Overallactivity was greater in FLT as compared to GC mice, with spontaneous ambulatory behavior, including organized circling or race-tracking behavior that emerged within thefirst few days of flight following a common developmental sequence, comprising theprimary dark cycle activity of FLT mice. Circling participation by individual micepersisted throughout the mission. Analysis of group behavior over mission days revealed recruitment of mice into the group phenotype, coupled with decreasing numbers of collisions between circling mice. This analysis provides insights into the behavior of mice in microgravity, and clear evidence for the emergence of a distinctive,organized group behavior unique to the weightless space environment.
Climate change is a major global concern. Greenhouse gas emissions that cause global climate change are directly or indirectly affected by human activities. Individual low-carbon behaviors are crucial in reducing CO 2 emissions and improving environmental and ecological health. To effectively promote individual low-carbon behavior, this study designed a questionnaire on the factors influencing individual low-carbon intentions and behavior based on theoretical models of environmental behavior. A total of 2430 valid questionnaires were collected in China. This study focuses on analyzing the impact of demographic characteristics, internal and external factors on individual low-carbon behaviors and their interrelationships. The research shows correlations between internal and external factors in determining low-carbon intention or behaviors. Internal factors-related low-carbon behavior is not closely linked with demographic variables, whereas the external factors-related low-carbon behavior vary significantly by age, residence, education, marital status, occupation, and income. The findings have important implications for designing effective policies to promote low-carbon behaviors, such as creating a more favorable external environment and increasing the use of policy tools for reducing CO 2 emission.
The Behavior, Constraint, and Scenario (BeCoS) tool has been developed to allow engineers to specify system and component behaviors. The tool is a web application that is developed in JavaScript and uses the React framework for the user interface and Redux for maintaining application state. The foundation of the tool is its underlying ontology, which expands upon a previously-defined behavior ontology with a scenario ontology. The behavior ontology includes elements like behaving elements, state variables, parameters, and constraints, while the scenario ontology includes core constructs like activities, temporal constraints, and timepoints. BeCoS allows users to easily create behaving elements and to specify their state variables, parameters, state machines, and constraints. BeCoS also allows users to develop temporal constraint networks that specify constraints on component states over time. BeCoS is a prototype tool that has been deployed and tested by systems engineers on the Europa Clipper project, which generated several use cases and helped steer its current developmental effort. By enabling systems engineers to specify behavior in a semantically-rigorous manner, BeCoS is an enabling technology for analyses that previously could not be performed, and when exporting its model to other tools, allows for consistent behavior models to be used.
The Behavior, Constraint, and Scenario (BeCoS) tool has been developed to allow engineers to specify system and component behaviors. The tool is a web application that is developed in JavaScript and uses the React framework for the user interface and Redux for maintaining application state. The foundation of the tool is its underlying ontology, which expands upon a previously-defined behavior ontology with a scenario ontology. The behavior ontology includes elements like behaving elements, state variables, parameters, and constraints, while the scenario ontology includes core constructs like activities, temporal constraints, and timepoints. BeCoS allows users to easily create behaving elements and to specify their state variables, parameters, state machines, and constraints. BeCoS also allows users to develop temporal constraint networks that specify constraints on component states over time. BeCoS is a prototype tool that has been deployed and tested by systems engineers on the Europa Clipper project, which generated several use cases and helped steer its current developmental effort. By enabling systems engineers to specify behavior in a semantically-rigorous manner, BeCoS is an enabling technology for analyses that previously could not be performed, and when exporting its model to other tools, allows for consistent behavior models to be used.
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In this contribution, we combined electrochemical cycling and X-ray photoelectron spectroscopy (XPS) to understand the nonpassivating behavior of the solid electrolyte interphase (SEI) on Si anodes during the first cycles. Based on galvanostatic measurements, we show that the irreversible capacity loss is reduced after the first cycle, and it stays almost constant from the second cycle onwards. XPS was used to determine the root causes of the Coulombic inefficiency, showing that the rate of decomposition of the organic solvents strongly decreased after the first cycle, whereas the rate of salt decomposition is almost unchanged between cycles. We determine that the inhibition of the decomposition reaction of the organic solvent is responsible for the lower Coulombic loss during the second electrochemical cycle in comparison to the first, whereas the nonpassivating behavior toward the salt decomposition is one of the main causes of capacity loss upon cycling. Here, we further revisit the role of cracking in contributing to capacity loss. Whereas high volumetric expansion remains an issue plaguing the performance of Si anodes, our chronoamperometry studies reveal that the SEI formed on Si anodes does not passivate even when the electrode is fully expanded, and no additional surface is exposed. Overall, our work establishes the need to address the chemical and electrochemical instability of the SEI on the Si anode in addition to the more notorious issue of cracking.
This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.
The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures used to assess behavioral health and performance risks related to future exploration class space missions. The HFBP-EM addresses the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analog (HERA) campaigns 4 and 5, and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogs of spaceflight environments. A subset of the HFBP-EM suite was collected in spaceflight as part of the HRP Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are the same across studies, differences across research settings (e.g., experimental manipulations, mission scenarios, and mission length) and implementation of the measures require that the data are harmonized to ensure comparable views across missions. The purpose of our project was to develop a harmonized database of analyzable HFBP-EM data from spaceflight and analog settings, and to summarize the trajectory of behavioral health and performance outcomes within and between mission settings. In this presentation, we will summarize the harmonized dataset and the trajectory of BMed related measures including depression, neurobehavioral function, mood, cognition, and operationally relevant individual performance over time and by campaign and mission.
Introduction to graphite Fabrication of graphite Unique features of nuclear grade graphite Providing the properties As-fabricated material properties of interest Thermal diff, thermal stability, mechanical strength, etc. General graphite behavior and degradation Microstructure: key to behavior Crystallographic structure Basal plane (covalent) bonding Porosity and pore microstructure Degradation Irradiation behavior Oxidation behavior Molten salt issues
With the advancement of renewable energy, the processing and handling of biomass feedstocks has drawn enormous research interest. The key to economically viable and operationally reliable biomass handling processes involves a complete understanding of the flow behavior of different feedstocks as functions of the inherent critical material properties environmental conditions, and critical processing parameters. This review introduces the basic principles and methods in bulk solids flow and highlights recent efforts to understand the flow behavior of biomass feedstocks. The effects of inherent properties, environmental parameters, and handling equipment on the flow behavior of biomass feedstocks are presented. Particle size, shape, moisture, consolidation stress, temperature, storage time at rest, chemical treatment, and the material and geometry of the handling equipment all substantially influence biomass flowability. The limitations of current studies and the potential methods to overcome them are presented. Finally, an outlook for future research effort is provided, with proposed opportunities for improving the characterization of biomass flow.
Oxygen and transition metal (TM) vacancies in transition metal oxides (TMOs) play an important role in materials functionalities. For TMO cathodes of Li-ion batteries, vacancies can be introduced, either deliberately or inevitably, during materials synthesis or upon electrochemical cycling. Effects of vacancies on the electrochemical properties of cathodes critically depend on the dynamic characteristics of vacancies during the battery cycling. However, a fundamental understanding of such characteristics in the layer structured cathode remains elusive. Here, using scanning transmission electron microscopy (STEM), we reveal a cycling-induced aggregation behavior of oxygen and TM vacancies in a Ni-rich layer structured cathode of secondary particles. We discover that during the initial charging, vacancies aggregate to form visible vacancy-rich nanoregions (vacancy clusters) firstly at the outer layer of the secondary particle, and then the vacancy-cluster populated region extends to the inner part of particle upon fully charged. The spatial distinction of preferential nucleation of vacancy clusters at the outer layer indicates that the vacancy migration and clustering is associated with Li migration flux, which is larger at the outer layer, as all the Li from the inner part has to go through the outer layer. With extended cycling (> 50), these vacancy clusters become immobilized. We further reveal that the generation of these vacancy clusters is correlated to the material-synthesis conditions. Our findings solve a long-standing puzzle on the origin, nature, and behavior of the commonly visible vacancy clusters in the NMC cathode, providing insights on correlation between properties and dynamic behaviors of atomic-scale defects in layered oxide cathodes.
This dataset contains input and output files from density functional theory (DFT) simulations used to study the disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y (0 ≤ x + y ≤ 1) alloys and their binary end members MnTe, MnSb, and MnBi. The alloys adopt the hexagonal NiAs-type (nickeline) structure and span ternary (MnTexSb1-x, MnTexBi1-x, MnBixSb1-x), and quaternary compositions across the full MnTe–MnSb–MnBi composition triangle. For each alloy composition, the dataset provides DFT calculations in three magnetic configurations: A-type antiferromagnetic (AFM), C-type AFM, and ferromagnetic (FM). Every magnetic configuration folder contains the fully relaxed crystal structure (CONTCAR), VASP input parameters (INCAR), and the main VASP output file (OUTCAR), from which total electronic energies, Mn magnetic moments, lattice parameters, and percent volume changes between magnetic states are extracted. These data are used to construct compositional phase diagrams, evaluate thermodynamic stability (formability), and map magnetoelastic responses across the alloy space. For A-type AFM and FM configurations, additional data are provided as follows: (i) FORCE_CONSTANTS and thermal_properties.yaml files at the top level of A-type_AFM/ and FM/ folders — present only for compositions marked with an asterisk (*) in Table I of the main text. These are derived from Phonopy finite-displacement calculations on full disordered 128-atom supercells and provide vibrational free energy, entropy (Svib)contribution from explicit disorder calculations. (Table I of the associated main manuscript) (ii) A VCA/ subfolder within A-type_AFM/ and FM/, containing FORCE_CONSTANTS and thermal_properties.yaml from Virtual Crystal Approximation phonon calculations (without spin-orbit coupling). VCA data are available for all compositions and are used to estimate vibrational contributions to the Gibbs free energy across the full composition space. (iii) A SOC/ subfolder containing CONTCAR, INCAR, and OUTCAR from spin-orbit coupling calculations, providing relativistic corrections to electronic energies and lattice parameters (Tables S2–S3 of the SM, and Table I of the main manuscript). (iv) A SOC/VCA/ subfolder containing FORCE_CONSTANTS and thermal_properties.yaml from VCA phonon calculations performed within the SOC framework, combining relativistic and vibrational thermodynamic corrections. The computed properties are used to map the AFM–FM magnetic crossover near MnTe0.75Sb0.25, demonstrate disorder- and spin-induced phonon broadening, identify a semiconductor-to-metal crossover, and quantify the pronounced magnetoelastic volume response near the magnetic phase boundary.
Previous work using Photostress on TIG welded, heat treated specimens of 2219-T87 parent material and 2319 weld material indicated that behavior of the joint can be highly irregular and non-uniform. Welded joints 1.40 inches thick exhibited a totally non-uniform behavior through the weld thickness with the 'wide' side of the weld being much more ductile than the 'narrow' side. It is believed that this difference in behavior through the weld is, in part, caused by procedures used when laying the weld bead. Joints similar to weldments in references 1 and 2 are an integral part of the aft skirt of the SRB of the shuttle. Since the ultimate safety factor for the lower portion of the weld is below the minimum required safety factor, a photostress analysis of this lower portion will be conducted in the vicinity of the weld. A test program using photostress will be conducted in accordance with the project planning document entitled 'Photostress Evaluation Requirements for AFT Skirt Test Article No. 4'.