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At least 721 records · Page 40

Refined Classical Force Field for Choline Chloride and Ethylene Glycol Mixtures over Wide Composition Range

In this work, a classical force field based on the General Amber Force Field (GAFF) was refined for the simulation of choline chloride (ChCl) and ethylene glycol (EG) mixtures over a wide composition range by scaling the partial charges and van der Waals parameters. The scaling factors were derived by fitting the simulation results to only eight experimental density and viscosity data points of pure EG, and ChCl/EG mixtures at 1:2, 1:4, and 1:6 molar ratios. Using the refined force field, properties essential for electrochemical applications such as density, viscosity, self-diffusion coefficient, and ionic conductivity were calculated, and excellent agreement to experimental results was found even for compositions and temperatures not used in the fitting procedure. In addition, new experimental data for density, viscosity, and ionic conductivity are reported as a function of temperature and composition for this mixture. To the best of our knowledge, this is the first classical force field developed for the study of ChCl/EG mixtures over a composition range that includes the eutectic point. Using the new model, the liquid dynamics was studied in terms of ionic conductivity. It was found that the dynamics in ChCl/EG mixtures with ChCl mole fraction higher than 20% is similar to that of ionic liquids, high temperature molten salts, and highly concentrated water-in-salt electrolytes.

25 ENERGY STORAGE↗

Resolving the dynamic correlated disorder in KTa 1- x Nb x O 3

Understanding the complex temporal and spatial correlations of ions in disordered perovskite oxides is critical to rationalize their functional properties. Here, in this study, we provide new insights into the longstanding controversy regarding the off-centering of transition metal ions in the archetypal ferroelectric alloy KTa 1-x Nb x O 3 (KTN). By mapping the full energy (E) and wavevector (Q) dependence of the dynamical structure factor S(Q, E) using neutron scattering, and rationalizing our observations with atomistic simulations leveraging machine learning, we fully resolve the static vs dynamic nature of diffuse scattering sheets, as well as their composition (x) and temperature dependence. Our first-principles simulations, extended with machine-learning molecular dynamics, reproduce both inelastic neutron spectra and diffuse features, and establish how dynamically-correlated transition metal off-centerings couple to phonons, unifying local and collective viewpoints. This study sheds new light into an exemplary ferroelectric systems and shows the importance of mapping the full S(Q, E) to reveal critical spatio-temporal correlations of atomic disorder from which functional properties emerge.

42 ENGINEERING↗

MC{sup 2}-3/DIF3D Analysis of the ZPPR-15B Foil Measurements

The Zero Power Physics Reactor (ZPPR) fast critical facility at the Argonne National Laboratory-West site in Idaho was built in 1969 to obtain neutron physics information necessary for the design of fast breeder reactors. The ZPPR-15 phases A through D were intended to model a 330 MWt Integral Fast Reactor (IFR) concept. This work focuses on foil measurements in the shielding regions of ZPPR-15B. The ZPPR-15B core simulated an equilibrium cycle U-Pu-Zr fuel core where plutonium created in the blankets was sufficient to negate the need for enriched {sup 235}U feedstock. ZPPR-15B consisted of an inner core zone, an outer core zone of higher fissile content, a thin radial blanket and a thick steel reflector. The inner and outer core zones were of approximately equal volumes and were designed to simulate a sodium-cooled, metal-fueled fast reactor with approximately 10 wt.% zirconium in the target fuel composition. Consistent with the IFR program, ZPPR-15B had Zr plates in the inner core region to simulate a Zr alloyed fuel composition. The outer core had no Zr plates due to the limited inventory of Zr plates and thus consisted of drawers which had stainless steel plates rather than Zr. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A machine learning approach to predict thermal expansion of complex oxides

Although it is of scientific and practical importance, the state-of-the-art of predicting the thermal expansion of oxides over broad temperature and composition ranges by physics-based atomistic simulations is currently limited to qualitative agreements. We present an emerging machine learning (ML) approach to accurately predict the thermal expansion of cubic oxides with a dataset consisting of experimentally measured lattice parameters while using the metal cation polyhedron and temperature as descriptors. High-fidelity ML models that can accurately predict temperature- and composition-dependent lattice parameters of cubic oxides with isotropic thermal expansions have been successfully trained. The ML-predicted thermal expansions of oxides not included in the training dataset have shown good agreement with available experiments. The limitations of the current approach and challenges to go beyond cubic oxides with isotropic thermal expansion are also briefly discussed.

36 MATERIALS SCIENCE↗

Axial Tensile Failure Analysis of SiC{sub f}/Ti Composite Based on Continuum Cohesive Zone Model

In this paper, the failure behavior of SiC fiber-reinforced Ti-6Al-4V matrix composite (SiC{sub f}/Ti) under longitudinal loads was studied experimentally and theoretically. Experimental results show that the interface of SiC{sub f}/Ti composite is continuous and integral. Through SEM observations, it was found that transverse matrix cracks initiated from the debonding region of the interface. A three-dimensional representative volume element was developed to simulate the failure process of SiC{sub f}/Ti-6Al-4V composite. A continuum cohesive zone model is employed to describe the debonding behavior at the interface, compared with a discrete one. More accurate simulated results were obtained by a continuum cohesive zone model, corresponding to experimental results. The transverse cracking behavior of the matrix was simulated. The stress–strain curves predicted by the continuum cohesive zone model show a good agreement with the experimental results. The fiber volume fraction, interface strength and interface toughness are investigated to exhibit their influences upon the longitudinal mechanical characteristics of SiC{sub f}/Ti-6Al-4V composite.

36 MATERIALS SCIENCE↗

Performance investigation of a high-field active magnetic regenerator

Regenerative magnetic cycles are of interest for small-scale, high-efficiency cryogen liquefiers; however, commercially relevant performance has yet to be demonstrated. To develop improved engineering prototypes, an efficient modeling tool is required to screen the multi-parameter design space. In this work, we describe an Active Magnetic Regenerative Refrigerator (AMRR) prototype using a high-field superconducting magnet that produces a 100 K temperature span. Using the experimental data, a semi-analytic AMR element model is validated and enhanced system performance is simulated using liquid propane as a heat transfer fluid. In addition, the regenerator composition and fluid flow are simultaneously optimized using a differential evolution algorithm. Simulation results indicate that a natural gas liquefier with a 160 K span and a second-law efficiency exceeding 20% is achievable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

V31 Test Report

The V31 containment vessel was procured by the US Army Recovered Chemical Material Directorate (RCMD) as a third - generation EDS containment vessel. It is the fifth EDS vessel to be fabricated under Code Case 2564 of the 2019 ASME Boiler and Pressure Vessel Code, which provides rules for the design of impulsively loaded vessels. The explosive rating for the vessel, based on the code case, is twenty-four (24) pounds TNT - equivalent for up to 1092 detonations. This report documents the results of explosive tests that were performed on the vessel at Sandia National Laboratories in Albuquerque, New Mexico to qualify the vessel for field operations use. There were three design basis configurations for qualification testing. Qualification test (1) consisted of a simulated M55 rocket motor and warhead assembly of 24lbs of Composition C-4 (30 lb TNT equivalent). This test was considered the maximum load case, based on modeling and simulation methods performed by Sandia prior to the vessel design phase. Qualification test (2) consisted of a regular, right circular cylinder, unitary charge, located central to the vessel interior of 19.2 lb of Composition C-4 (24 lb TNT equivalent). Qualification test (3) consisted of a 12-pack of regular, right circular cylinders of 2 lb each, distributed evenly inside the vessel (totaling 19.2 lb of C-4, or 24 lb TNT equivalent). All vessel acceptance criteria were met.

42 ENGINEERING↗

V31 Test Report

The V31 containment vessel was procured by the US Army Recovered Chemical Materiel Directorate (RCMD) as a third-generation EDS containment vessel. It is the fifth EDS vessel to be fabricated under Code Case 2564 of the 2019 ASME Boiler and Pressure Vessel Code, which provides rules for the design of impulsively loaded vessels. The explosive rating for the vessel, based on the code case, is twenty-four (24) pounds TNT-equivalent for up to 1092 detonations. This report documents the results of explosive tests that were performed on the vessel at Sandia National Laboratories in Albuquerque, New Mexico to qualify the vessel for field operations use. There were three design basis configurations for qualification testing. Qualification test (1) consisted of a simulated M55 rocket motor and warhead assembly of 24lbs of Composition C-4 (30 lb TNT equivalent). This test was considered the maximum load case, based on modeling and simulation methods performed by Sandia prior to the vessel design phase. Qualification test (2) consisted of a regular, right circular cylinder, unitary charge, located central to the vessel interior of 19.2 lb of Composition C-4 (24 lb TNT equivalent). Qualification test (3) consisted of a 12-pack of regular, right circular cylinders of 2 lb each, distributed evenly inside the vessel (totaling 19.2 lb of C-4, or 24 lb TNT equivalent). All vessel acceptance criteria were met .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analysis of InGaN light-emitting diodes with GaN-AlGaN and AlGaN-GaN composition-graded barriers

The effects of InGaN-based light-emitting diodes (LEDs) with Al composition increasing and decreasing GaN-AlGaN barriers along the growth direction are studied numerically. Simulation results suggest that the LEDs with GaN-AlGaN composition-decreased barriers show more significant enhancement of light-output power and internal quantum efficiency than LEDs with composition-increasing GaN-AlGaN barriers when compared with the conventional LED with GaN barriers, due to the improvement in hole injection efficiency and electron blocking capability. Moreover, the optical performance is further improved by replacing GaN-AlGaN barriers with AlGaN-GaN barriers of the same Al composition-decreasing range, which are mainly attributed to the modified band diagrams. In addition, the major causes of the different efficiency droop behaviors for all the designed structures are explained by the electron leakage current and the different increase rates of hole concentration with injection current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantitative Structure–Property Relationship (QSPR) Analysis of ZrO 2 -Containing Soda-Lime Borosilicate Glasses

Quantitative structure–property relationship (QSPR) analysis is a promising approach to correlate structural features with properties of glass materials that lack long-range order and usually have complex structures. By using carefully chosen descriptors based on structural models generated from molecular dynamics (MD) simulations, correlations with properties and insights on glass behaviors can be obtained. Zirconia can significantly alter glass properties including chemical durability, even in a small amount, and hence plays an important role in vitrification of nuclear waste where long-term chemical durability is desired. In this study, borosilicate glasses with the composition of xZrO 2 –(61 – x)SiO 2 –17B 2 O 3 –18Na 2 O–4CaO with x = 0, 1, 2, 4, 6, and 8 were simulated using classical MD simulations with the recently developed composition-dependent potentials. Short-range (e.g., bond distance and coordination numbers) and medium-range (e.g., Qn distribution, network connectivity, and ring-size distribution) structural features altered by ZrO 2 were obtained and analyzed. The use of a descriptor (Fnet descriptor) that combines short-range structural characteristics, from MD simulations, and the cation-oxygen single bond strength was found to provide excellent linear correlations with the density and initial dissolution rate of these glasses. Furthermore, the results show that by combining MD simulations and QSPR analysis the composition and structural effect on the properties of complex multicomponent glasses can be elucidated, thus suggesting that this is a promising approach for future glass research and new composition design.

36 MATERIALS SCIENCE↗

Impact of chamber wall loss of gaseous organic compounds on secondary organic aerosol formation: Explicit modeling of SOA formation from alkane and alkene oxidation

Recent studies have shown that low volatility gas-phase species can be lost onto the smog chamber wall surfaces. Although this loss of organic vapors to walls could be substantial during experiments, its effect on secondary organic aerosol (SOA) formation has not been well characterized and quantified yet. Here the potential impact of chamber walls on the loss of gaseous organic species and SOA formation has been explored using the Generator for Explicit Chemistry and Kinetics of the Organics in the Atmosphere (GECKO-A) modeling tool, which explicitly represents SOA formation and gas–wall partitioning. The model was compared with 41 smog chamber experiments of SOA formation under OH oxidation of alkane and alkene series (linear, cyclic and C 12 -branched alkanes and terminal, internal and 2-methyl alkenes with 7 to 17 carbon atoms) under high NO x conditions. Simulated trends match observed trends within and between homologous series. The loss of organic vapors to the chamber walls is found to affect SOA yields as well as the composition of the gas and the particle phases. Simulated distributions of the species in various phases suggest that nitrates, hydroxynitrates and carbonylesters could substantially be lost onto walls. The extent of this process depends on the rate of gas–wall mass transfer, the vapor pressure of the species and the duration of the experiments. Furthermore, this work suggests that SOA yields inferred from chamber experiments could be underestimated up a factor of 2 due to the loss of organic vapors to chamber walls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗

Resolving Detonation NanoDiamond Size Evolution and Morphology at Sub-Microsecond Time-Scales During High-Explosive Detonations

Characterization of the initial morphology of detonation nanodiamond (DND) has been the focus of many research studies that aim to develop fundamental understanding of carbon condensation under extreme conditions. Identifying the pathways of DND formation has the potential for significant impact in many of the controlled synthesis of nanoscale carbon with tailored functionality; currently, a wide range of possible (and conflicting) mechanisms of nucleation and growth have been proposed and further research is essential. Building a comprehensive understanding of DND formation is challenging because it requires in situ characterization on the sub-µs time-scale during a high explosive detonation. In this study, time resolved small angle X-ray scattering (TR-SAXS) is used to reveal the early-stage DND morphology from < 0.1 μs to 6 μs after the detonation front passes through the X-ray beam path. We address the ambiguity of models previously reported for analysis of small angle scattering from DND by comparing (i) in situ, TR-SAXS recorded during early-stage particulate formation and (ii) ex situ SAXS and transmission electron microscopy measurements (TEM) of products recovered from detonation of the same high-explosive within a carefully designed ice chamber. The SAXS from both late-time ( > 1 μs) in situ and recovered DND exhibit consistent features in the I(q) curve. Such close similarity allows a high fidelity SAXS model derived from the ex situ SAXS and TEM measurements to be applied to the in situ data, which yields new insight into the early stage (< 1µs) morphology of DND. Our analysis indicates a size-distribution of DND particles is observed within 0.1 μs post-detonation and have a mean core diameter slightly below 4 nm and surface texture that consists of hemispherical protrusions that extend ~ 1 nm from the surface. Beyond ~ 0.3 μs, the size distribution increases slightly, while the surface texture persists for several microseconds after the detonation. Combined with thermochemical simulations, these results indicate that during detonation of Composition B, carbon is condensed into nanoscale diamond much faster than previously reported in other studies. Furthermore, the surface texture of the DND is shown to arise during condensation rather than via subsequent graphitization.

carbon condensation↗

Physical and optical properties of the International Simple Glass

Abstract Radioactive waste immobilization is a means to limit the release of radionuclides from various waste streams into the environment over a timescale of hundreds to many thousands of years. Incorporation of radionuclide-containing wastes into borosilicate glass during vitrification is one potential route to accomplish such immobilization. To facilitate comparisons and assessments of reproducibility across experiments and laboratories, a six-component borosilicate glass (Si, B, Na, Al, Ca, Zr) known as the International Simple Glass (ISG) was developed by international consensus as a compromise between simplicity and similarity to waste glasses. Focusing on a single glass composition with a multi-pronged approach utilizing state-of-the-art, multi-scale experimental and theoretical tools provides a common database that can be used to assess relative importance of mechanisms and models. Here we present physical property data (both published and previously unpublished) on a single batch of ISG, which was cast into individual ingots that were distributed to the collaborators. Properties from the atomic scale to the macroscale, including composition and elemental impurities, phase purity, density, thermal properties, mechanical properties, optical and vibrational properties, and the results of molecular dynamics simulations are presented. In addition, information on the surface composition and morphology after polishing is included. Although the existing literature on the alteration of ISG is not extensively reviewed here, the results of well-controlled static alteration experiments are presented here as a point of reference for other performance investigations.

36 MATERIALS SCIENCE↗

Examining phase separation and crystallization in glasses with X-ray nano-computed tomography

X-ray nano-computed tomography (nano-CT) is a powerful technique to characterize and visualize 3 dimensional (3D) phenomena in complex glasses at the nanoscale. This technique can offer a unique opportunity to explore the intricate morphology of multicomponent glass and glass-ceramic samples, due to its low X-ray energy and high spatial resolution (down to 50 nm). In the current demonstration paper, nano-CT provided insight into crystallization and phase separation, as well as a variety of other phenomena, including corrosion, fracture, and porosity. At scales ranging from 100 to 20 μm, the microstructures of phase separation in borosilicate, complex silicate, and chalcogenide glass compositions were examined. In addition, crystallites present in simulant nuclear waste glasses, volcanic glasses, and other related samples were explored. Nano-CT analysis can add to the understanding of (1) the formation processes, (2) distributions, interactions, and compositions of phases, and (3) the mechanisms, structures, and growth of crystallization and phase separation. Nano-CT offers wide potential in the field of glass science, especially when (1) common characterization methods are insufficient, (2) simple sample preparation is required, (3) 3D rendering is needed, or (4) compelling images of small, complex features are desired.

36 MATERIALS SCIENCE↗

High-Fidelity Large-Signal Order Reduction Approach for Composite Load Model

With the increasing penetration of electronic loads and distributed energy resources, conventional load models cannot capture their dynamics. Therefore, a new comprehensive composite load model is developed by Western Electricity Coordinating Council (WECC). However, this model is a complex high-order non-linear system with multi-time-scale property, which poses challenges on power system studies with heavy computational burden. In order to reduce the model complexity, the authors firstly develop a large-signal order reduction (LSOR) method using singular perturbation theory. In this method, the fast dynamics are integrated into the slow ones to preserve transient characteristics of the former. Then, accuracy assessment conditions are proposed and embedded into the LSOR to improve and guarantee the accuracy of reduced-order model. Finally, the reduced-order WECC composite load model is derived by using the proposed algorithm. Overall, simulation results show that the reduced-order large-signal model significantly alleviates the computational burden while maintaining similar dynamic responses as the original composite load model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Facile synthesis of Ag–Cu{sub 2}O composites with enhanced photocatalytic activity

Highlights: • Ag–Cu{sub 2}O nanocomposites were synthesized via awet-chemical precipitation route. • The growth temperature does not exceed 50 °C in any step of the synthesis. • Enhanced photocurrent of Ag–Cu{sub 2}O composites, compared to pure Cu{sub 2}O particles. • The photocatalytic property was studied upon simulated sunlight. • Enhanced photocatalytic property of Ag–Cu{sub 2}O composites, compared to pure Cu{sub 2}O particles. - Abstract: Silver–cuprous oxide (Ag–Cu{sub 2}O) microcomposites are successfully prepared by a facile low-cost solution method. The obtained materials were characterized by X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), field emission scanning electron microscopy (FESEM), ultraviolet–visible (UV–vis) spectroscopy, X-ray photoelectron spectroscopy (XPS). Experiments demonstrated that the formation of Ag–Cu{sub 2}O microcomposites was significantly influenced by the concentration of AgNO{sub 3}, and with increasing the concentration of AgNO{sub 3}, the optical absorption of the composites becomes strong. The photocatalytic activity of the prepared Ag–Cu{sub 2}O composites was determined by measuring the degradation of methyl orange solution under visible light, to find out its potential application in waste water treatment. The results reveal that the photocurrent of the composite is about 4 times higher than that of pure Cu{sub 2}O and the visible light photocatalytic activity of the composite is enhanced greatly on degradation of methyl orange. The reason for improvement in photocatalytic activity of the Ag–Cu{sub 2}O composites was also discussed.

36 MATERIALS SCIENCE↗