Connections between the Speciation and Solubility of Ni(II) and Co(II) in Molten ZnCl2
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The recognition of membrane separations as a vital technology platform for enhancing the efficiency of separation processes has been steadily increasing. Concurrently, 3D printing has emerged as an innovative approach to fabricating reverse osmosis membranes for water desalination and treatment purposes. This method provides a high degree of control over membrane chemistry and structural properties. In particular, when compared to traditional manufacturing techniques, 3D printing holds the potential to expedite customization, a feat that is typically achieved through conventional manufacturing methods but often involves numerous processes and significant costs. This review aims to present the current advancements in membrane manufacturing technology specifically tailored for water desalination purposes, with a particular focus on the development of 3D-printed membranes. A comprehensive analysis of recent progress in 3D-printed membranes is provided. However, conducting experimental work to investigate various influential factors while ensuring consistent results poses a significant challenge. To address this, we explore how membrane manufacturing processes and performance can be effectively pre-designed and guided through the use of molecular dynamics simulations. Finally, this review outlines the challenges faced and presents future perspectives to shed light on research directions for optimizing membrane manufacturing processes and achieving optimal membrane performance.
This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.
In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.
Single-layer FeSe on SrTiO 3 (001) substrates shows a superconducting transition temperature much higher than that of bulk FeSe, which has been attributed to factors such as electron doping, interfacial electron–phonon coupling, and electron correlations. To pinpoint the primary driver, we grew single-layer FeSe films on SrTiO 3 (001) substrates with coexisting TiO 2 and SrO surface terminations. Scanning tunneling spectroscopy revealed a larger superconducting gap (17.0 meV) on the TiO 2 -termination than on the SrO-termination (10.5 meV). Tunneling spectroscopy also showed a larger work function on the SrO surface, resulting in reduced charge transfer to FeSe, as confirmed by angle-resolved photoemission spectroscopy. Scanning transmission electron microscopy further revealed distinctive interfacial atomic-scale structures, with the Se–Fe–Se tetrahedral angle changing from 109.5° on the SrO-termination to 104.9° on the TiO 2 -termination. Compared to dynamical mean field theory calculations, our results indicate that enhanced superconductivity in single-layer FeSe/TiO 2 arises from optimal electron correlations, in addition to sufficient charge transfer from the substrate.
The study of infrasound (acoustic) and gravity waves sources and propagation in the atmosphere of a planet gives us precious insight on atmosphere dynamics, climate, and even internal structure. The implementation of modern pressure sensors with high rate sampling on stratospheric balloons is improving their study. In our work we analyzed the data from the National Aeronautics and Space Administration Ultra Long Duration Balloon mission (16 May to 30 June 2016). Here, we focus on the balloon's transit of the Andes Mountains. We detected gravity waves that are associated to troposphere convective activity and mountain waves. An increase of the horizontal wavelengths from 50 to 70 km with increasing distance to the mountains is favoring the presence of mountain waves. We also report on the detection of infrasounds generated by the mountains in the 0.01–0.1 Hz range with a pressure amplitude increase by a factor 2 relative background signal. Besides, we characterized the decrease of microbaroms power when the balloon was flying away from the ocean coast. These observations suggest, in a way similar to microseisms for seismometers, that microbaroms are the main background noise sources recorded in the stratosphere even far from the ocean sources. Finally, we observed a broadband signal above the Andes, between 0.45 and 2 Hz, probably associated with a thunderstorm. The diversity of geophysical phenomena captured in less than a day of observation stresses the interest of high rate pressure sensors on board long-duration balloon missions.
This research effort examined the application of Nafion polymers in alcohol solvents as an anti-ice surface coating, as a mixture with hydrophilic polymers and freezing point depressant salt systems. Co-soluble systems of Nafion, polymer and salt were applied using dip coating methods to create smooth films for frost observation over a Peltier plate thermal system in ambient laboratory conditions. Cryo-DSC was applied to examine freezing events of the Nafion-surfactant mixtures, but the sensitivity of the measurement was insufficient to determine frost behavior. Collaborations with the Fog Chamber at Sandia-Albuquerque, and in environmental SAXS measurements with CINT-LANL were requested but were not able to be performed under the research duration. Since experimental characterization of these factors is difficult to achieve directly, computational modeling was used to guide the scientific basis for property improvement. Computational modeling was performed to improve understanding of the dynamic association between ionomer side groups and added molecules and deicing salts. The polyacrylic acid in water system was identified at the start of the project as a relevant system for exploring the effect of varying counterions on the properties of fully deprotonated polyacrylic acid (PAA) in the presence of water. Simulations were modeled with four different counterions, two monovalent counterions (K+ and Na+) and two divalent counterions (Ca2+ and Mg2+). The wt% of PAA in these systems was varied from ~10 to 80 wt% PAA for temperatures from 250K to 400K. In the second set of simulations, the interpenetration of water into a dry PAA film was studied for Na+ or Ca2+ counterions for temperatures between 300K and 400K. The result of this project is a sprayable Nafion film composite which resists ice nucleation at -20 °C for periods of greater than three hours. It is composed of Nafion polymer, hydrophilic polyethylene oxide polymer and CaCl2 anti-ice crosslinker. Durability and field performance properties remain to be determined.
Sensors manufactured using piezoresistive elastomeric nanocomposites have a wide range of applications in many fields such as structural health monitoring, robotics, and biomedical industries. Additive manufacturing of these sensors, achieved using Direct Ink Writing (DIW), has provided numerous advantages including increased sensitivity and the fabrication of complex geometry. However, solid sensors manufactured either additively or using conventional methods, display a greater level of hysteresis, especially at strains higher than 10%, which limits their sensitivity. The solid sensors also display a greater level of piezoresistive relaxation where the resistance change with time either in a static or dynamic loading environment. Porosity can be introduced in the form of varying infill patterns and densities to reduce bulk material effects. In this paper, a lattice structure with four infill densities are investigated, and the samples are printed using a grid infill pattern. The fabricated samples are characterized using a scanning electron microscope (SEM) to validate the microstructural features and layer bonding. The pressure-sensing capability of each sensor is investigated using cyclic compression loading at various strain levels. Sensing results show that an increase in sensitivity, as well as a decrease in hysteresis with an increase in porosity, compared to solid samples (100% in-fill). The highest porosity was measured to be 62.3% with a corresponding 112% increase in the gauge factor compared to the solid bulk. These results indicate that introducing porosity using DIW is a sensible strategy to improve the piezoresistive performance of nanocomposites and to allow for the tunability of sensing capacity in pressure sensors
The tensile strength of metals at extreme strain rates is a key predictor of their performance in ballistic and structural impact applications. An important experimental method to reach these extreme strain rates is the use of high-amplitude, short-duration pulsed lasers. The Jupiter Laser Facility at the Lawrence Livermore National Laboratory enabled probing for the first time the mechanical response of several promising High Entropy Alloys at times on the order of nanoseconds (strain rates of ∼10 7 and ∼10 9 s −1 ). The measured strength is in the range of 6 to 10 GPa, ten times the quasistatic value. The mechanisms of plastic deformation and failure were identified and quantified through analysis and molecular dynamics simulation. The reflected wave amplitudes, obtained by VISAR, were used to determine the tensile (spall) stress. The high tensile strength obtained is due to two factors: the strain-rate dependence of plastic flow and the kinetics of void nucleation, growth, and coalescence. The experimental results are compared with an analytical prediction considering both grain-interior and grain-boundary void initiation. Molecular dynamics simulations, conducted at strain rates of 10 8 and 10 9 s −1 , rationalize the experimental results. In conclusion, they provide valuable information about the process of failure evolution, and reveal that grain boundary separation plays a pivotal role in spalling.
Here, we report the development of an experimental approach to efficiently determine the energy level structure of an individual silicon vacancy (SiV) center in a magnetic field along an arbitrary direction. This approach uses two coupling rates (one each for the ground and the excited states) to characterize the combined effects of static strain and dynamic Jahn-Teller coupling and exploits the fact that orbital Zeeman effects vanish when the magnetic field is normal to the SiV axis. With an analytical expression for the energy level structure of the SiV under a transverse magnetic field, the two coupling rates can be directly derived from two measurements: one on the frequency separation between two spin-conserved transitions and the other on the coherent population trapping resonance of the SiV ground spin states. A detailed comparison between the numerical calculation and the experimental result on the dependence of the spin-conserved splitting on both the amplitude and direction of the magnetic field further reveals unequal orbital magnetic coupling for the ground and excited states, indicating that unequal orbital quenching factors are needed for an accurate description of the SiV energy level structure in a magnetic field.
Abstract There are inherent challenges in scaling stomatal conductance (g ) from leaf to canopy particularly over seasonal time scales when species distribution and canopy structure evolve. We address this gap using carbonyl sulfide (OCS) and CO fluxes from a predominantly C3 prairie and C4 maize field in the midwestern United States. The g derived from OCS fluxes captured a transition in the stomatal limitation on gross primary productivity (GPP) through the growing season as well as seasonally persistent g dynamics such as temperature optimum and a positive response of nighttime g to vapor pressure deficit. Near the termination of the prairie growing season, we observed a decrease in the relative OCS to CO flux that we hypothesize emerged from a rising contribution of C4 plants to productivity. The results show how plot‐scale OCS and CO fluxes can be used as a trace gas diagnostic for transitions in the limiting factors for community GPP.
Partial anion substitution in transition metal oxides provides rich opportunities to control and tune physical and chemical properties, for example, combining the merits of oxides and nitrides. In addition, the possibility of resulting anion sublattice order provides a means to target polar and chiral structures based on a wide array of accessible structural archetypes by design. Here, in this work, we investigate the local structures of a family of perovskite tantalum oxynitrides—ATaO 2 N (A = Ba, Sr, and Ca)—using a combination of experimental and theoretical approaches including neutron total scattering, density functional theory (DFT), and ab initio molecular dynamics (AIMD) simulations. We present the first experimental study of chemical short-range order (CSRO) in CaTaO 2 N, confirming local cis N ordering of the anion sub-lattice. Our systematic exploration of a local structure across the A cation size series (from the larger Ba to the smaller Ca) reveals a perovskite motif increasingly distorted with respect to long-range average structures. DFT and AIMD simulations support the observed trends. Overall, structures with cis ordering of the nitrogen anions in each TaO 4 N 2 octahedron are favored over those with trans ordering. With diminishing A cation size, local cis ordering and Ta off-centering play decreasing roles in overall lattice stability, overshadowed by the stabilizing effects of octahedral tilting. The influence of these factors on local dipole formation and frustrated dipole ordering are discussed.
Abstract Extreme precipitation has widespread impacts over the western US (WUS), which are expected to be exacerbated in the future given thermodynamically driven increases in atmospheric moisture and shifts in atmospheric circulation patterns. However, internal climate variability complicates how these factors affect future projections of precipitation changes. In this study, we investigate late 21st‐century changes in mean‐state responses over the North Pacific Ocean and associated WUS precipitation extremes using the Multi‐Model Large Ensemble Archive, which is a recent and valuable resource to disentangle the effects of model structural differences from internal variability. We found that inter‐model differences in precipitation extremes over the WUS are large: from south to north (here, from California to Washington), models show different levels of increases for both the frequency and intensity of heavy precipitation. In general, the Pacific Northwest sees a more consistent signal than California. We show that wet‐season mean circulation influences extreme precipitation, by using a decomposition of the relative contributions of thermodynamic (atmospheric humidity) and dynamic (large‐scale circulation) driven changes. The thermodynamic contribution dominates, however, the dynamic contribution varies with latitude and differs substantially between model ensembles. Inter‐model differences affect the spread in not only the magnitude, but also the sign of the dynamic contribution. This implies that mean circulation changes contribute to uncertainty in quantifying the regional structure of concentrated moisture flux and future extreme events. This result highlights the need to more accurately constrain projected North Pacific coupled circulation changes to narrow the spread in projections of future precipitation extremes.
Concentrated Solar Power (CSP) is a promising method for using Solar power for electricity generation with thermal energy storage. One of the primary drivers of structural design costs of CSP collector structures is wind loading. To date, the design of these structures has relied on data from wind tunnels that do not adequately capture the dynamic effects observed at scale. NREL initiated a field measurement campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs, providing insights on structural dynamic response, and generating a first-of-a-kind, comprehensive, high-resolution wind-loading dataset available for validating simulations of wind loading on collector structures. The measurements at NSO consist of Sonic anemometers on masts at different heights to characterize the incoming flow and conditions within and above the trough field, in combination with a Doppler Lidar scanning the horizontal plane above the troughs. The wind measurements at NSO have been continuously operating since October 2021 and provide a year-long dataset characterizing wind and turbulence conditions. The structural load measurements start in November 2022 and will complement the wind measurements. In this poster, we present first results of the wind measurement campaign by highlighting days with different atmospheric flow conditions. We identified three main factors altering the flow over the parabolic troughs: Wind speed, wind direction, and the angle of the parabolic troughs. The highest loads are expected when the wind blows perpendicular to the trough rows. In this case, the first rows experience the highest loads and block the subsequent rows, creating conditions with decreased wind speed and enhanced turbulence within the trough field. Also, turbulent length scales change. These affected conditions produce unique load cases on the structures that will be captured by the load measurements. If the wind blows along the trough rows, wind and turbulence conditions are less influenced by the troughs.
Concentrated Solar Power (CSP) is a promising method for using Solar power for electricity generation with thermal energy storage. One of the primary drivers of structural design costs of CSP collector structures is wind loading. To date, the design of these structures has relied on data from wind tunnels that do not adequately capture the dynamic effects observed at scale. NREL initiated a field measurement campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs, providing insights on structural dynamic response, and generating a first-of-a-kind, comprehensive, high-resolution wind-loading dataset available for validating simulations of wind loading on collector structures. The measurements at NSO consist of Sonic anemometers on masts at different heights to characterize the incoming flow and conditions within and above the trough field, in combination with a Doppler Lidar scanning the horizontal plane above the troughs. The wind measurements at NSO have been continuously operating since October 2021 and provide a year-long dataset characterizing wind and turbulence conditions. The structural load measurements start in November 2022 and will complement the wind measurements. In this poster, we present first results of the wind measurement campaign by highlighting days with different atmospheric flow conditions. We identified three main factors altering the flow over the parabolic troughs: Wind speed, wind direction, and the angle of the parabolic troughs. The highest loads are expected when the wind blows perpendicular to the trough rows. In this case, the first rows experience the highest loads and block the subsequent rows, creating conditions with decreased wind speed and enhanced turbulence within the trough field. Also, turbulent length scales change. These affected conditions produce unique load cases on the structures that will be captured by the load measurements. If the wind blows along the trough rows, wind and turbulence conditions are less influenced by the troughs.
Direct numerical simulations of free round jets at a Reynolds number (Re D ) of 5000, based on jet diameter (D) and jet-exit bulk velocity (U e ), are performed to study jet turbulence characteristics at supercritical pressures. The jet consists of nitrogen (N 2 ) that is injected into N 2 at the same temperature. To understand turbulent mixing, a passive scalar is transported with the flow at unity Schmidt number. Two sets of inflow conditions that model jets issuing from either a smooth contraction nozzle (laminar inflow) or a long pipe nozzle (turbulent inflow) are considered. By changing one parameter at a time, the simulations examine the jet-flow sensitivity to the thermodynamic condition (characterized in terms of the compressibility factor ($Z$) and the normalized isothermal compressibility), inflow condition and ambient pressure (p ∞ ) spanning perfect- to real-gas conditions. The inflow affects flow statistics in the near field (containing the potential core closure and the transition region) as well as further downstream (containing fully developed flow with self-similar statistics) at both atmospheric and supercritical p ∞ . The sensitivity to inflow is larger in the transition region, where the laminar-inflow jets exhibit dominant coherent structures that produce higher mean strain rates and higher turbulent kinetic energy than in turbulent-inflow jets. Decreasing $Z$ at a fixed supercritical p ∞ enhances pressure and density fluctuations (non-dimensionalized by local mean pressure and density, respectively), but the effect on velocity fluctuations depends also on the local flow dynamics. When $Z$ is reduced, large mean strain rates in the transition region of laminar-inflow jets significantly enhance velocity fluctuations (non-dimensionalized by local mean velocity) and scalar mixing, whereas the effects are minimal in jets from turbulent inflow.
Abstract Bacteria on and inside leaves can influence forest tree health and resilience. The distribution and limits of a tree species’ range can be influenced by various factors, with biological interactions among the most significant. We investigated the processes shaping the bacterial needle community across the species distribution of limber pine, a widespread Western conifer inhabiting a range of extreme habitats. We tested four hypotheses: (i) Needle community structure varies across sites, with site-specific factors more important to microbial assembly than host species selection; (ii) dispersal limitation structures foliar communities across the range of limber pine; (iii) the relative significance of dispersal and selection differs across sites in the tree species range; and (iv) needle age structures bacterial communities. We characterized needle communities from the needle surface and tissue of limber pine and co-occurring conifers across 16 sites in the limber pine distribution. Our findings confirmed that site characteristics shape the assembly of bacterial communities across the host species range and showed that these patterns are not driven by dispersal limitation. Furthermore, the strength of selection by the host varied by site, possibly due to differences in available microbes. Our study, by focusing on trees in their natural setting, reveals real needle bacterial dynamics in forests, which is key to understanding the balance between stochastic and deterministic processes in shaping forest tree-microbe interactions. Such understanding will be necessary to predict or manipulate these interactions to support forest ecosystem productivity or assist plant migration and adaptation in the face of global change.
ABSTRACT We investigate the range of applicability of a model for the real-space power spectrum based on N-body dynamics and a (quadratic) Lagrangian bias expansion. This combination uses the highly accurate particle displacements that can be efficiently achieved by modern N-body methods with a symmetries-based bias expansion which describes the clustering of any tracer on large scales. We show that at low redshifts, and for moderately biased tracers, the substitution of N-body-determined dynamics improves over an equivalent model using perturbation theory by more than a factor of two in scale, while at high redshifts and for highly biased tracers the gains are more modest. This hybrid approach lends itself well to emulation. By removing the need to identify haloes and subhaloes, and by not requiring any galaxy-formation-related parameters to be included, the emulation task is significantly simplified at the cost of modelling a more limited range in scale.