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At least 1,009 records · Page 56

Effect of charge and anisotropic diffusivity on ion exchange kinetics in nuclear waste form materials

Motifs of radionuclide absorption particles (absorbers or fillers) for the nuclear waste treatment usually have crystal structures with nano-sized tunnels for fast ion diffusion. On the other hand, the accumulation of ions generates an electric field which affects the ion diffusion. Therefore, the strong anisotropic kinetic properties and the electric field affect ion exchange kinetics, especially in an assembly of these particles which may block the fast diffusion tunnels for each other. In this work, we developed a mesoscale model to describe the effect of anisotropic kinetic properties and electric field on ion exchange kinetics. With the model we simulated the effect of anisotropic diffusivity, electrochemical potential, particle morphology, size and aggregation on ion exchange kinetics during batch experiments. Here, tt is found that 1) ion exchange results in charge accumulation inside the particle because different ions have different diffusivities and different diffusion driving forces. The electric neutrality is not preserved; 2) the electric field speeds up the slower diffusion ions (either uptake or release) and slows down the faster diffusion ions to reduce charge accumulation and maintains charge neutrality; 3) the ion exchange becomes very slow at the later stages because a) diffusion driving force (electrochemical gradient, Cs + concentration in the solution and Na + inside the particle) continuously decreases, as observed in batch experiments; and b) the diffusivity decreases due to the Cs + concentration dependence of ion diffusivity. This can explain the observed experimental phenomena that the radionuclide capacity usually cannot be reached; 4) for needle-like particle and their clusters, both surface area and diffusion distance along the direction with the fastest diffusivities have significant impact on the ion exchange kinetics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Energy savings and life cycle cost analysis of advanced double skin facade system applied to old apartments in South Korea

South Korea is one of the most densely populated countries in the world, and the population density in urban areas is much higher among others. Apartments are the most common form of residential buildings due to their high population density. More than 60% of domestic residential buildings are apartments, with more than 10 million households. The high population density is a problem that has long plagued South Korea because more than 45% of apartments are old apartments that are more than 20 years old. Old apartment buildings have low thermal performance that results in lots of energy consumption. Balconies, which worked as a thermal buffer, are also being removed by residents to expand indoor space. According to the green remodeling project supported by the Korean government, the typical retrofitting method is replacing external windows with the high-efficiency window in old apartments in South Korea. Here, this paper proposes a retrofitting method using an extended double-skin façade (DSF) system that replaces exterior windows and acts as a thermal buffer. The simulation model is developed with the EnergyPlus simulation program to conduct energy performance analyses. The simulation model has been calibrated using actual experimental data collected between October 1, 2019, and January 15, 2020. Results show that the cooling, heating, and lighting energy can be reduced up to 44.1% by fully utilizing electric energy generated by solar PV panels integrated with the DSF system. The payback period is about 15 years based on the energy price provided by the utility company. Although the payback period is long, it has great potential of energy savings and CO 2 emission reductions. The DSF system should be considered as a way of renovation, considering other factors such as increased real estate values and energy cost increases in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Particle-based high-temperature thermochemical energy storage reactors

Solar and other renewable energy driven gas-solid thermochemical energy storage (TCES) technology is a promising solution for the next generation energy storage systems due to its high operating temperature, efficient energy conversion, ultra-long storage duration, and potential high energy density. Experimental and theoretical studies suggest that the respective gravimetric and volumetric TCES energy storage densities vary from 200 to 3000 kJ kg –1 and 1–3 GJ m –3 . Solar radiation or heat generated from electric furnaces powered by renewable electricity can be stored in the form of chemical energy through endothermic reactions, while the stored chemical energy can be converted to thermal energy via an exothermic reaction when needed. The design of highly effective reactors requires a deep understanding of materials, thermodynamics, chemical kinetics, and transport phenomena. At time of writing, TCES reactors are yet to be deployed at commercially relevant scales, leaving a substantial gap between development efforts and commercial feasibility. Therefore, this review aims to examine the state-of-the-art design and performance of particle-based TCES reactors with different reactive materials. Fundamentals related to TCES reactive materials, reaction conditions, thermodynamics and kinetics, and transport phenomena are reviewed in detail to provide a comprehensive understanding of the reactor design and operation. Five major types of TCES reactors have been comprehensively reviewed and compared, including fixed, moving, rotary, fluidized, and entrained bed reactors. Most reported prototype reactors in the literature operate at lab scale with thermal inputs below 40 kW, and scaled TCES reactors (e.g., at megawatt level) are yet to be demonstrated. The nominal reactor operating temperatures range from 300 to 1500 °C, depending on the selected chemistry, reactive material, and heat sources. To evaluate their designs, the reactors are assessed in aspects of performance, cost, and durability. Discrepancies in performance indicators of energy storage density, extent of reaction, and various energy efficiencies are highlighted. The scale-up of reactors and power block integration, which hold the key to the successful commercialization of TCES systems, are critically analyzed. Furthermore, advanced materials (both reactive materials and ceramic reactor housing materials), effective particle flow control, advanced modeling tools, and novel system design may bring significant improvement to the energy efficiency, storage density and cost competitiveness of particle-based TCES reactors.

25 ENERGY STORAGE↗

Multiobjective Optimal Controlled Variable Selection for a Gas Turbine–Solid Oxide Fuel Cell System Using a Multiagent Optimization Platform

Hybrid gas turbine–fuel cell systems have immense potential for high efficiency in electrical power generation with cleaner emissions compared with fossil-fueled power generation. We report a systematic controlled variable (CV) selection method is deployed for a hybrid gas turbine–fuel cell system in the HyPer (hybrid performance) facility at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL) for maximizing its economic and control performance. A three-stage approach is used for the CV selection comprising a priori analysis, multiobjective optimization, and a posteriori analysis. The a priori analysis helps to screen off several candidate CVs, thus reducing the size of the combinatorial optimization problem for multiobjective CV selection. For optimal CV selection, a transfer function model of the HyPer facility is identified. By considering several candidate models, the final transfer function model is selected using Akaike’s Final Prediction Error criterion. Experimental data from the HyPer facility are used to estimate the noise in the measurement data. For solving the combinatorial multiobjective optimization problem for CV selection, a multiagent optimization platform comprising simulated annealing, genetic algorithm, and efficient ant colony optimization algorithms is used. Pareto-optimal CV sets exhibit a high trade-off between the economic and control objective. The a posteriori analysis is undertaken for several top Pareto-optimal CV sets. An optimal CV set is selected that shows the best compromise between process economics and controllability under both nominal and off-design conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Active and Robust Air Electrode for Reversible Protonic Ceramic Electrochemical Cells

Reversible protonic ceramic electrochemical cells (RPCECs) are a promising option for efficient and low-cost generation of electricity and hydrogen. Commercialization of R-PCECs, however, hinges on the development of highly active and robust air electrodes. Here, we report an air electrode consisting of PrBa 0.8 Ca 0.2 Co 2 O 5+δ and in situ exsolved BaCoO 3–δ nanoparticles (PBCC–BCO) that shows minimal polarization resistance (~0.24 Ω cm 2 at 600 °C) and high stability when exposed to humidified air with 3–50% H 2 O. An R-PCEC utilizing PBCC-BCO demonstrates remarkable performances at 600 °C: achieving a peak power density of 1.06 W cm –2 in the fuel cell mode and a current density of 1.51 A cm –2 at 1.3 V in an electrolysis mode. More importantly, the RPCECs demonstrate an exceptionally high durability over 1833 h of continuous operation in the electrolysis mode. Furthermore, this work offers an efficient approach to design of high-performance and durable electrodes for R-PCECs.

25 ENERGY STORAGE↗

Chemical Long-Range Disorder in Prussian Blue Analogues for Potassium Storage

Ordered Prussian blue analogues (PBAs) are vital cathode materials for ion storage, but strong interactions between the framework and host ions, especially large ions like K + , hinder ion migration, leading to poor diffusion kinetics and reduced reaction activity. Here, in this study, we present an approach to overcome this challenge by constructing chemical long-range disorder (LRD) in PBAs, involving maintaining inherent local coordination while introducing disorder over long-range spatial dimensions. Order control is achieved by introducing a large-sized lattice to disrupt the original lattice growth during synthesis. Unlike traditional monocrystalline particles, the abundant grain boundaries in the obtained LRD structure create significant potential fluctuations, generating additional electric fields that enhance ion transport. Furthermore, the short lattice coherence length reduces interaction between the framework and K + . These factors collectively contribute to the improved electrochemical activity of LRD PBAs during K + storage. This finding opens new avenues for designing PBA structures and offers insights into their structure-electrochemical performance relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generation of a Strong Parallel Electric Field and Embedded Electron Jet in the Exhaust of Moderate Guide Field Reconnection

Abstract Magnetospheric Multiscale observed an extended current layer concurrent with a strong parallel electric field. The current layer is embedded in the reconnection exhaust and is consistent with an extended magnetized jet expected in roughly symmetric moderate guide field reconnection. The strong parallel electric field observed at the jet balances a strong gradient in the parallel electron pressure caused by a transition between magnetized electrons with T e ‖ > T e ⊥ on one side of the jet and demagnetized, roughly isotropic electrons across the thin current layer. Simulation results show how this transition can occur and how the associated electron pressure gradients in Ohm's law balance the parallel electric field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

CFD-based design optimization of ducted hydrokinetic turbines

Abstract Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines.

13 HYDRO ENERGY↗

Guest Editorial: Advanced Data-Analytics for Power System Operation, Control, and Enhanced Situational Awareness

Along with the smart grid development, modern power systems are entering a ‘data-intensive’ era. A vast volume of data from power grids is being collected through advanced sensing and communication technologies, such as smart metering data, phasor measurement data, as well as meteorological data (e.g., wind speed and solar irradiance) related to renewable power generation. Such data contains comprehensive information about the power system covering equipment's health status, power grid's static and dynamic characteristics, renewable power generation, customers’ electricity usage pattern, etc. Therefore, advanced data-analytics techniques are needed to convert such data to knowledge for practical applications. In line with the trend of widespread data-driven applications in power systems, this Special Issue aims to present state-of-the-art research works on advanced data-analytics for power system's operation, control, and situational awareness. There are in total twenty-six papers accepted for publication in this Special Issue through careful peer reviews and revisions. Under the overarching theme of data-driven applications in power systems, the selected papers are broadly categorised into five topics. The summary of every topic is given below. You are, however, strongly encouraged to read the full paper if interested.

Xu, Yan↗

Laser intensity scaling of the magnetic field from a laser-driven coil target

In this paper, we report on the first direct voltage and current measurements from a laser-generated magnetic field coil target. The magnetic field was observed to scale with the laser intensity as $B ∝ \mathcal{I}^{0.66±0.13}_\text{laser}$. This scaling relation can be derived from the measured voltage approximated by the laser-heated plasma electron temperature $T_e$. The experiments used a 1053 nm laser with pulse lengths ranging from 0.5 to 20 ns and intensities ranging from 10 9 to 10 14 W/cm 2 to generate an electric potential that drives current through the coil. We show that the behavior of the coil can be described with a lumped-element circuit model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spin current generation and detection in uniaxial antiferromagnetic insulators

Spin current represents a flow of spin angular momentum and does not require movement of charges. Magnetic insulators can therefore work as a source as well as a medium of spin currents, which has been established in ferrimagnetic insulators. Here, we report recent progress in the generation and electrical detection of spin currents in uniaxial antiferromagnetic insulators carried by antiferromagnetic magnons, both thermally and resonantly excited, respectively, via the spin Seebeck effect and antiferromagnetic spin pumping by subterahertz microwaves. These findings open up many exciting possibilities of potential antiferromagnetic applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Increased thermal conductivity and decreased electron–phonon coupling factor of the aluminum scandium intermetallic phase (Al 3 Sc) compared to solid solutions

Aluminum scandium alloys and their intermetallic phases have arisen as potential candidates for the next generation of electrical interconnects. Here, in this work, we measure the in-plane thermal conductivity and electron–phonon coupling factor of aluminum scandium alloy thin films deposited at different temperatures, where the temperature is used to control the grain size and volume fraction of the Al 3 Sc intermetallic phase. As the Al 3 Sc intermetallic formation increases with higher deposition temperature, we measure increasing in-plane thermal conductivity and a decrease in the electron–phonon coupling factor, which corresponds to an increase in grain size. Our findings demonstrate the role that chemical ordering from the formation of the intermetallic phase has on thermal transport.

Chemical elements↗

Efficient backward x-ray emission in a finite-length plasma irradiated by a laser pulse of picosecond duration

Motivated by experiments employing picosecond-long, kilojoule laser pulses, we examined x-ray emission in a finite-length underdense plasma irradiated by such a pulse using two-dimensional particle-in-cell simulations. We found that, in addition to the expected forward emission, the plasma also efficiently emits in the backward direction. Our simulations reveal that the backward emission occurs when the laser exits the plasma. The longitudinal plasma electric field generated by the laser at the density down-ramp turns around some of the laser-accelerated electrons and re-accelerates them in the backward direction. As the electrons collide with the laser, they emit hard x rays. The energy conversion efficiency is comparable to that for the forward emission, but the effective source size is smaller. We show that the picosecond laser duration is required for achieving a spatial overlap between the laser and the backward energetic electrons. At peak laser intensity of 1.4×1020 W/cm2, backward-emitted photons (energies above 100 keV and 10° divergence angle) account for 2×10−5 of the incident laser energy. This conversion efficiency is three times higher than that for similarly selected forward-emitted photons. The source size of the backward photons (5 μm) is three times smaller than the source size of the forward photons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ionization effects in single-shot carrier-envelope phase detection with gas-gap devices

The carrier-envelope phase (CEP) is a key parameter for attosecond waveform control of ultrashort laser pulses. For laser systems with high repetition rates, however, single-shot CEP detection is still challenging. Building on recent findings on phase detection with electric current generation in gases, we show that with an optimized detection method, a long-term stable single-shot phase detection is feasible. We investigate the achievable performance depending on various parameters such as pulse duration, gas pressure, or incident intensity. The latter exhibits a regime where the saturation of the ionization process boosts the phase sensitivity of the signal, which is elucidated by numerical calculations.

47 OTHER INSTRUMENTATION↗

Experimental characterization of discharge plasma dynamics in a square capillary for prospective applications in laser wakefield acceleration

Research on plasma generated by electrical discharge in gas-filled capillaries plays an important role in advancing laser wakefield accelerators. We present a comprehensive study of the temporal and spatial distribution of plasma density within a short, 1 cm long, square-shaped capillary filled with hydrogen gas. Two transverse capillary sizes, 500 μm and 300 μm, were investigated achieving peak plasma densities of 0.9 × 10 18 cm −3 and 2.5 × 10 18 cm −3 , respectively, at the capillary center. In addition, we explore how these distributions depend on discharge parameters, specifically discharge current and gas flow through the capillary. Plasma density was determined by analyzing the Stark broadening of the hydrogen Balmer-alpha line. The results obtained were compared with the theoretical models and simulations. The comparison between the model predictions and the experimental data at the transient ionization stage of the discharge reveals a discrepancy of a factor of ∼1.3–2.1, depending on the capillary size, which is thoroughly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics

Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.

14 SOLAR ENERGY↗

Anomaly detection in PV systems using constrained low-rank and sparse decomposition

PV (photovoltaic) systems, also known as solar panel systems, play an essential role in the mitigation of greenhouse gas emissions and the promotion of renewable energy. Through the conversion of sunlight into usable energy, electricity is generated without emitting greenhouse gases and producing pollutants. Notwithstanding the evolutionary significance of PV systems, the occurrence of defects and anomalies in PV systems may result in diminished power output, consequently impeding the efficiency of the systems and potentially resulting in hazards in certain circumstances. Therefore, early detection of faults and anomalies in PV systems is imperative to guarantee the reliability, efficiency, and safety of the systems. In this article, we develop a signal decomposition for the purpose of anomaly detection in PV systems. The proposed methodology is grounded on the concept of low-rank and sparse decomposition, with consideration given to the signs of the decomposed low-rank and sparse components, as well as the smooth variations within and between periods in the mean signals. Through the implementation of Monte Carlo simulations, we showcase the efficacy of our proposed methodology in identifying anomalies of varying durations and magnitudes in PV systems. A case study is employed to validate the proposed methodology in detecting anomalies in real PV systems.

14 SOLAR ENERGY↗