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Metal alloy layers on substrates. The metal-alloy layers (e.g., lithium-metal layers, sodium-metal layers, and magnesium-metal layers) can be disposed on, for example, a solid-state electrolyte material. The metal-alloy layers can be used in, for example, solid-state batteries. A metal alloy layer can be an anode or part of an anode of a solid state battery.
A coating is applied to a base material. The coating comprises a viscoelastic layer having a surface in which cavities are formed; and a constraint layer. The viscoelastic layer is disposed on the base material, and the constraint layer is disposed on, and partially bonded, at an interface, to the viscoelastic layer over the surface in which the cavities are formed. The cavities are filled with particles configured for vibration and frictional interaction at the partially bonded interface between the partially bonded viscoelastic layer and the constraint layer. A turbine blade having an airfoil with the subject coating is also provided.
Photovoltaic structures having multiple absorber layers separated by a diffusion barrier are provided. In one aspect, a method of forming an absorber on a substrate includes: depositing a first layer of light absorbing material on the substrate; depositing a diffusion barrier; depositing a second layer of light absorbing material on the diffusion barrier, wherein the first layer of light absorbing material has a different band gap from the second layer of light absorbing material; and annealing the absorber, wherein the diffusion barrier prevents diffusion of elements between the first layer of light absorbing material and the second layer of light absorbing material during the annealing. A solar cell and method for formation thereof are also provided.
A radiation detector includes a p-i-n architecture including a p-type contact layer, an n-type contact layer, and an intrinsic layer between the p-type contact layer and the n-type contact layer. The intrinsic layer includes a thin film comprising a highly crystalline 2D layered perovskite material. The radiation detectors according to embodiments of the present disclosure generate high open circuit voltages, have good detecting photon density limits and high sensitivities, and can be self-powered.
A layered catalyst structure for purifying an exhaust gas stream includes a catalyst support and a palladium catalyst layer including an atomic dispersion of palladium ions electrostatically adsorbed onto an exterior surface of the catalyst support. The catalyst support includes an alumina substrate, a first ceria layer disposed on and extending substantially continuously over the alumina substrate, and a second colloidal ceria layer formed directly on the first ceria layer over the alumina substrate. The palladium catalyst layer is formed on the exterior surface of the catalyst support by applying a palladium-containing precursor solution to the exterior surface of the catalyst support and then heating the catalyst support and the palladium-containing precursor solution. The palladium-containing precursor solution includes a positively charged palladium complex in an aqueous medium and has a pH greater than a point of zero charge of the second colloidal ceria layer.
Tri-structural-isotropic (TRISO) particle has been successful in high temperature gas cooled reactor (HTGR), but an improved design is required for future development. In this paper, two alternative designs of TRISO particle are proposed by introducing ZrC to the coating layers. One design is to add an individual ZrC layer between the inner PyC layer and the SiC layer. Another design is to construct a periodic coating layer with the repeated sequence of SiC/SiC-ZrC by doping pulsed ZrCl{sub 4} at proper time intervals during the SiC preparation process. The designed coating layers were successfully prepared on the ZrO{sub 2}/buffer/IPyC particles by the fluidized bed chemical vapor deposition (FB-CVD) method. Microstructures and characterizations of the composite coating layers were given based on XRD, SEM, EDX and Raman scattering analysis. By controlling the pulse parameter, the grain size of SiC is significantly decreased which means doping ZrCl{sub 4} can interrupt normal growth of SiC crystals. (authors)
Numerical weather prediction is often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model 4.0 was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City. We compare three different simulations in their ability to reproduce the observations, each using a different boundary-layer parametrization. Specifically, we examine the Mellor–Yamada–Janjic (MYJ), Yonsei University (YSU), and Mellor–Yamada–Nakanishi–Niino (MYNN) boundary-layer parametrizations. All three predict the wind speed well during the day but overpredict it at night. The MYNN parametrization is better than MYJ at predicting the daytime turbulence in the surface layer, but both underpredict the nocturnal turbulence. Additionally, the MYJ parametrization is best at predicting the reciprocal Obukhov length, while MYNN and YSU both significantly overpredict thermal stability. Reconstructing the reciprocal Obukhov length from other simulated parameters produces more accurate values for both parametrizations. All three models overpredict the boundary-layer height, particularly under convective conditions. The MYJ parametrization overestimates boundary-layer height the most, while YSU and MYNN have comparable performance with MYNN having an advantage in predicting the stable boundary-layer height. Several days were found where the WRF simulations predict significant deviations from the prevailing diurnal pattern in wind direction, which are not found in the observations.
Thin/tunable liquid/gas diffusion layers (TT-LGDLs) or porous transport layers (TT-PTLs), have exhibited superior multifunctional performance in proton exchange membrane electrolyzer cells (PEMECs), which can be attributed to their unique structures, such as planar surface, straight-through pores, thin thickness, etc. For achieving better PEMEC performance, TT-LGDLs with smaller pore size are desired. However, in this case, mass diffusion issues are brought in when some of the pores are covered by the flow field lands or shoulders. The coverage of the pores can lead to very high transport resistance, which may reduce the number of active oxygen evolution reaction sites, and therefore lower down the PEMEC performance. The in-plane transport enhancement layer for TT-LGDLs/PTLs are proposed to develop a dual-layer LGDL/PTL structure for improving the mass diffusion and the PEMEC performance. The results of this research reveal that the dual-layer LGDL/PTL structure exhibits smaller ohmic resistance and mass transport resistance, and therefore improve the PEMEC performance, without obvious changes in kinetic losses. The total ohmic resistance and mass transport resistance can be reduced by about 23% and 41%, respectively, with an ~830 um pore TT-LGDL/PTL stacking on a ~100 um pore TT-LGDL/PTL. The results indicate the feasibility of stacking the in-plane transport enhancement layer with large pore sizes onto a small pore TT-LGDLs/PTLs for high efficiency and low cost PEMEC practical applications.
Two-dimensional (2D) layered materials offer intriguing possibilities for novel physics and applications. Before any attempt at exploring the materials space in a systematic fashion, or combining insights from theory, computation, and experiment, a formal description of information about an assembly of arbitrary composition is required. Here, we introduce a domain-generic notation that is used to describe the space of 2D layered materials from monolayers to twisted assemblies of arbitrary composition, existent or not yet fabricated. The notation corresponds to a theoretical materials concept of stepwise assembly of layered structures using a sequence of rotation, vertical stacking, and other operations on individual 2D layers. Its scope is demonstrated with several example structures using common single-layer materials as building blocks. This work overall aims to contribute to the systematic codification, capture, and transfer of materials knowledge in the area of 2D layered materials.
As machine learning becomes more integrated into atmospheric science, XGBoost has gained popularity for its ability to assess the relative contributions of influencing factors in the atmospheric boundary layer height. To examine how these factors vary across seasons, a seasonal analysis is necessary. However, dividing data by season reduces the sample size, which can affect result reliability and complicate factor comparisons. To address these challenges, this study replaces default parameters with grid search optimization and incorporates cross-validation to mitigate dataset limitations. Using XGBoost with four years of data from the atmospheric radiation measurement (ARM) (Southern Great Plains (SGP) C1 site, cross-validation stabilizes correlation coefficient fluctuations from 0.3 to within 0.1. With optimized parameters, the R value can reach 0.81. Analysis of the C1 site reveals that the relative importance of different factors changes across seasons. Lower tropospheric stability (LTS, ~0.53) is the dominant factor at C1 throughout the year. However, during DJF, latent heat flux (LHF, 0.44) surpasses LTS (0.22). In SON, LTS (0.58) becomes more influential than LHF (0.18). Further comparisons among the four long-term SGP sites (C1, E32, E37, and E39) show seasonal variations in relative importance. Notably, during JJA, the differences in the relative importance of the three factors across all sites are lower than in other seasons. This suggests that boundary layer development in the summer is not dominated by a single factor, reflecting a more intricate process likely influenced by seasonal conditions such as enhanced convective activity, higher temperatures, and humidity, which collectively contribute to a balanced distribution of parameter impacts. Furthermore, the relative importance of LTS gradually increases from morning to noon, indicating that LTS becomes more significant as the boundary layer approaches its maximum height. Consequently, the LTS in the early morning in autumn exhibits greater relative importance compared to other seasons. This reflects a faster development of the mixing layer height (MLH) in autumn, suggesting that it is easier to retrieve the MLH from the previous day during this period. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization.
In the paper "The Mutual Interference of Boundary Layers," the authors investigated the problem of the interference of two planes intersecting at right angles on the boundary layers formed by the motion of fluid along the line of intersection of these planes. In the present paper, the results of the preceding one are generalized to the case of planes intersecting at any angle. The motion of a fluid in an angle less than 180 degrees is discussed and the enlargement of the boundary layers near the line of intersection of the planes, the limits of the interference effects of the boundary layers, and the corrections on the drag are determined. All computations are conducted by the Karman-Pohlhausen method for laminar and turbulent boundary layers. The results are reduced to tabulated form.
The investigation of twisted stacked few-layer MoS 2 has revealed novel electronic, optical, and vibrational properties over an extended period. For the successful integration of twisted stacked few-layer MoS 2 into a wide range of applications, it is crucial to employ a noninvasive, versatile technique for characterizing the layered architecture of these complex structures. Here, in this work, we introduce a machine learning-assisted low-frequency Raman spectroscopy method to characterize the twist angle of few-layer stacked MoS 2 samples. A feedforward neural network (FNN) is utilized to analyze the low-frequency breathing mode as a function of the twist angle. Moreover, using finite difference method (FDM) and density functional theory (DFT) calculations, we show that the low-frequency Raman spectra of MoS 2 are mainly influenced by the effect of the nearest and second nearest layers. A new improved linear chain model (TA-LCM) with taking the twist angle into the consideration is developed to understand the interlayer breathing modes of stacked few-layer MoS 2 . This approach can be extended to other 2D materials systems and provides an intelligent way to investigate naturally stacked and twisted interlayer interactions.
The current generation of state-of-the-art global climate models are being run at increasingly higher horizontal resolutions, with the goal of resolving organised deep convection explicitly. How a kilometre-scale resolution impacts the representation of the atmospheric boundary layer is, however, not well known. Using statistical analysis on global fields as well as high-frequency data at selected locations, produced with the Integrated Forecasting System (IFS) model for the Next Generation Earth-system Models (nextGEMS) project, we investigate the horizontal resolution dependence of some boundary-layer processes. We find that a change in resolution from 9 to 2.8 km causes no substantial changes to boundary-layer properties and processes at most of the locations studied, although some global changes are detected that indicate circulation changes. Small changes to the boundary-layer depth and structure are found in the Tropics. The short simulation length and lack of data for optimal boundary-layer analysis limits the conclusions, especially in relation to the connection between the boundary layer and the atmosphere general circulation.
Two-dimensional (2D) layered oxides have recently attracted wide attention owing to the strong coupling among charges, spins, lattice, and strain, which allows great flexibility and opportunities in structure designs as well as multifunctionality exploration. In parallel, plasmonic hybrid nanostructures exhibit exotic localized surface plasmon resonance (LSPR) providing a broad range of applications in nanophotonic devices and sensors. A hybrid material platform combining the unique multifunctional 2D layered oxides and plasmonic nanostructures brings optical tuning into the new level. Here, a novel self-assembled Bi 2 MoO 6 (BMO) 2D layered oxide incorporated with plasmonic Au nanoinclusions has been demonstrated via one-step pulsed laser deposition (PLD) technique. Comprehensive microstructural characterizations, including scanning transmission electron microscopy (STEM), differential phase contrast imaging (DPC), and STEM tomography, have demonstrated the high epitaxial quality and particle-in-matrix morphology of the BMO-Au nanocomposite film. DPC-STEM imaging clarifies the magnetic domain structures of BMO matrix. Three different BMO structures including layered supercell (LSC) and superlattices have been revealed which is attributed to the variable strain states throughout the BMO-Au film. Owing to the combination of plasmonic Au and layered structure of BMO, the nanocomposite film exhibits a typical LSPR in visible wavelength region and strong anisotropy in terms of its optical and ferromagnetic properties. This study opens a new avenue for developing novel 2D layered complex oxides incorporated with plasmonic metal or semiconductor phases showing great potential for applications in multifunctional nanoelectronics devices.
The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.
Here, we introduce a stochastic methodology to reproduce the complex pore structure observed in commercial iridium catalyst layers. This method preserves the α pore (pores smaller than 250 nm) and β pore (pores greater than or equal to 250 nm) regions of the catalyst layer. The morphology of the generated materials was validated by comparing the pore size distributions of generated materials against those obtained from commercial materials imaged using x-ray nano computed tomography. We further demonstrate that the pore size distributions of the generated materials are statistically indistinguishable from the imaged catalyst layers, indicating that the stochastic methodology is capable of accurately reproducing catalyst layer morphology. Pore network modelling was conducted on the generated catalyst materials to simulate single-phase permeability, electrical conductivity, and ionic conductivity, and these properties were found to be within experimentally measured ranges for electrolyzer catalyst layers. Additionally, simulations were performed on the generated materials with varying ionomer and iridium catalyst loadings. As the ionomer loading is added, proton conductivity increases exponentially, which demonstrates the importance of optimizing ionomer loading, considering that these effects will be exacerbated in the hydration and temperature conditions of operating electrolyzers. The stochastic material generation method presented in this work is a powerful tool for the development of novel low loading catalyst layers, where the effect of various structural parameters on electrolyzer performance characteristics can be explored.
Thin foil based porous transport layers (PTLs) that contain highly structured pore arrays have shown promise as anode PTLs in proton exchange membrane electrolysis cells. These novel PTLs, fabricated with advanced manufacturing techniques, produce thin, tunable, multifunctional layers with reduced flow and interfacial resistances and high thermal and electric conductivities. To further optimize their design, it is important to understand their fundamental impact on the transport of protons, electrons, and liquid/vapor mixtures in the electrode. In this work, we develop a two-dimensional multiphysics model to simulate the coupled electrochemistry and multiphase transport in an electrolysis cell operated with the novel PTL architecture. The results show that larger pores improve access of water to the anode catalyst layer, which is beneficial for both the oxygen evolution reaction and membrane hydration. Larger pore sizes also improve oxygen gas transport from the catalyst layer, because generated oxygen gas is forced to travel in-plane through the anode catalyst layer until it reaches a pore opening that is connected to a channel. The discussed results confirm that the proposed thin foil based PTLs are fundamentally different from conventional PTLs, such as felts or layered meshes. The model developed in this work also provides generalizable insight into fundamental PEMEC phenomena, such as the competition between liquid and gas phase transport, membrane hydration and water management, and nonuniform electrochemical reactions, which are processes relevant to all PEMEC designs.
Here, structure of the pellet/cladding-interaction (PCI) layer of a high-burnup nuclear fuel with niobium-bearing cladding was investigated using modern transmission electron microscopy (TEM) techniques. Morphology of the PCI consisted of uniform zirconia layer on the cladding side and finger-like features towards to the ceramic fuel. The PCI layer showed a complex microstructure that constitutes three distinct zirconia layers formed by two zirconia phases. From cladding to fuel, monoclinic, tetragonal, and another tetragonal phase were determined via TEM diffraction patterns and precession electron diffraction (PED) using ASTAR microscopy platform (AMP). Characterizations showed that monoclinic and tetragonal phases close to the cladding were crack-free, but the tetragonal layer adjacent to the fuel contained cracks and pores. Presence of the monoclinic layer suggested that its formation involved the gaseous diffusion of oxygen below threshold dose of fission product damage before the fuel/cladding contact occurred. Furthermore, high-resolution TEM revealed compound phase of (U,Zr)O 2 at fringes of zirconia fingers on the fuel side.