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Formation of large particles on substrate is eliminated by actively exhausting reacted gases. Effluent gas backflow is prevented by pumping in curtain of nitrogen above fresh reactive gases from several directions.
The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."
The capacity to identify realizable many-body configurations associated with targeted functional forms for the pair correlation function $g_2(r)$ or its corresponding structure factor $\textit{S(k)}$ is of great fundamental and practical importance. While there are obvious necessary conditions that a prescribed structure factor at number density ρ must satisfy to be configurationally realizable, sufficient conditions are generally not known due to the infinite degeneracy of configurations with different higher-order correlation functions. A major aim of this paper is to expand our theoretical knowledge of the class of pair correlation functions or structure factors that are realizable by classical disordered ensembles of particle configurations, including exotic “hyperuniform” varieties. We first introduce a theoretical formalism that provides a means to draw classical particle configurations from canonical ensembles with certain pairwise-additive potentials that could correspond to targeted analytical functional forms for the structure factor. This formulation enables us to devise an improved algorithm to construct systematically canonical-ensemble particle configurations with such targeted pair statistics, whenever realizable. As a proof of concept, we test the algorithm by targeting several different structure factors across dimensions that are known to be realizable and one hyperuniform target that is known to be nontrivially unrealizable. Our algorithm succeeds for all realizable targets and appropriately fails for the unrealizable target, demonstrating the accuracy and power of the method to numerically investigate the realizability problem. Subsequently, we also target several families of structure-factor functions that meet the known necessary realizability conditions but are not known to be realizable by disordered hyperuniform point configurations, including $\textit{d}$-dimensional Gaussian structure factors, $\textit{d}$-dimensional generalizations of the two-dimensional one-component plasma (OCP), and the $\textit{d}$-dimensional Fourier duals of the previous OCP cases. Moreover, we also explore unusual nonhyperuniform targets, including “hyposurficial” and “antihyperuniform” examples. In all of these instances, the targeted structure factors are achieved with high accuracy, suggesting that they are indeed realizable by equilibrium configurations with pairwise interactions at positive temperatures. Remarkably, we also show that the structure factor of nonequilibrium perfect glass, specified by two-, three-, and four-body interactions, can also be realized by equilibrium pair interactions at positive temperatures. In this work, our findings lead us to the conjecture that any realizable structure factor corresponding to either a translationally invariant equilibrium or nonequilibrium system can be attained by an equilibrium ensemble involving only effective pair interactions. Our investigation not only broadens our knowledge of analytical functional forms for $g_2(r)$ and $\textit{S(k)}$ associated with disordered point configurations across dimensions but also deepens our understanding of many-body physics. Moreover, our work can be applied to the design of materials with desirable physical properties that can be tuned by their pair statistics.
The NASA CERES project provides the scientific community with regional broadband fluxes designed for long-term climate monitoring. The CERES climate quality dataset requires that the CERES instrument, as well as the MODIS and VIIRS imager records to be radiometrically stable over time. Deep Convective Clouds (DCCs) are spectrally uniform, near-Lambertian natural diffusers offering high signal-to-noise ratio and stable radiometric response in the VIS-NIR spectrum. For shortwave infrared (SWIR) wavelengths greater than 1.2µm, the DCC response is significantly influenced by cloud particle size and atmospheric absorption. Previous studies improved the characterization of the SWIR band DCC radiance, by using channel specific monthly empirical BRDFs as well as using the probability density function mean statistic to track the SWIR band stability. Also, that the DCC radiance is greater over land than over ocean and that the TWP DCC radiance has the lowest tropical DCC radiance. This study confirms and improves upon the previous studies. The study stratified the tropics regionally into land and ocean domains and applied their respective ocean-only and land-only empirical monthly BRDFs and normalized the land DCC BRDF corrected radiances with their ocean counterpart. This approach provided the most stable DCC response. The DCC BRDF corrected radiance monthly standard error was 0.24%, 0.62%, 0.59%, and 0.43% for the 1.24µm, 1.37µm, 1.61µm, and 2.25µm SWIR bands, which reduced the standard error 20%, 13%, 24%, and 26%, respectively when compared with the all-surface approach. The same approach was attempted over the Tropical Western Pacific and found not to be an improvement over the tropical domain. Further stratification of the tropical domain will need to balance sufficient sampling while accounting for regional DCC radiance differences.
Methods have been developed at the Langley Vortex Research Facility to simulate and measure the deposition patterns of aerially applied sprays and granular materials by means of tests with small-scale models of agricultural and dynamically scaled test particles. Interactions between the aircraft wake and the dispersed particles are studied with the aim of modifying wake characteristics and dispersal techniques in order to increase swath width, improve deposition pattern uniformity, and minimize drift. This paper examines the particle sizing analysis, test methods for particle dispersal from the model aircraft, and measurement and computer analysis of test deposition patterns. Results that indicate improved control of chemical drift by winglets are presented to demonstrate test methods.
Shaped emitters are of interest to a broad range of applications in vacuum electronic devices. In particular, thermionic energy converters (TECs) take advantage of shaped emitters to increase the local surface field, thereby extracting more current for a given cathode temperature and applied voltage. However, modeling these devices is challenging; Warp [J.-L. Vay, D. P. Grote, R. H. Cohen, and A. Friedman, Comput. Sci. Discov. 5, 014019 (2012)] is a fully 3D particle-in-cell code capable of handling a wide range of physics problems and is well suited to modeling TECs. Additionally, recent improvements to Warp have enabled the accurate modeling of emitters with arbitrary curved surfaces. Specifically, the inclusion of subgrid resolution for computing the electrostatic potential and the ability to apply mesh refinement for specific areas of interest allow for a more accurate solution to the fields on these surfaces. These improvements coupled with Warp’s ability to handle variable particle weights make it an ideal candidate for simulating these complex devices. In this paper, the authors study the applicability of different subgrid configurations for simulating shaped emission surfaces and field convergence for different mesh-refinement techniques. They then implement a custom weighting algorithm that allows for uniform sampling of emission surfaces with a large variation in the surface electric field. They then use this algorithm to study emission for curved emitters in both the field-enhancement regime and the space-charge regime.
At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $^→_𝑝$$^{miss}_{T}$) is a crucial observable in many analyses. In the standard model, $^→_𝑝$$^{miss}_{T}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel deep neural network based $^→_𝑝$$^{miss}_{T}$ estimator, DeepMET, developed by the CMS Collaboration at the LHC. The DeepMET algorithm produces a weight for each reconstructed particle based on its properties. The estimator is based on the negative vector sum of the weighted transverse momenta of all reconstructed particles in an event. Compared with other estimators currently employed by CMS, DeepMET improves the $^→_𝑝$$^{miss}_{T}$ resolution by 10%–30%, shows improvement for a wide range of final states, is easier to train, and is more resilient against the effects of additional proton-proton interactions accompanying the collision of interest.
We report conventional cathodes for Li-ion batteries (LIBs) are reaching their theoretical capacity limits. One way to meet the growing demands for high-capacity LIBs is by developing so-called Li-rich cathode materials that greatly benefit from additional capacities from anionic moieties in the structure. Li-rich materials are intrinsically subject to higher degrees of (de)intercalation, leaving the particles more prone to fractures and thus rapid capacity fade. Alkali-rich LiNaFeS 2 reversibly cycles with capacities exceeding 300 mAh g -1 , but its capacity fades faster than an isostructural material Li 2 FeS 2 . Using synchrotron-based transmission X-ray microscopy (TXM), we demonstrate that the capacity fade of LiNaFeS 2 stems from particle fractures in the first charge cycle. We improve the cycling performance of LiNaFeS 2 by means of cryomilling, which enhances capacity retention at cycle 50 by 76%. Through crystallographic and morphological characterization techniques, we confirm that cryomilling not only decreases particle and crystallite size while increasing microstrain but also prevents particles from fracturing. Cryomilling is a powerful tool to engineer nanoscale battery materials, and TXM allows the direct observation of morphological changes of the particles, which can be leveraged to develop next-generation cathode materials for LIBs.
We provide an overview of activities carried out at the TJ-II stellarator for improving our understanding of- and developing plasma physics models for particle density profiles in stellarators. Namely, we report on recent progress in turbulent particle transport simulation, validation of pellet deposition models, density profile shaping for performance control and new experimental techniques for edge turbulence and plasma-neutral interaction.
The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.
In neutrino-nucleus interactions, Final State Interactions (FSI) can cause nucleons to scatter or form heavier composite particles like deuterons and tritons. Observing these particles would provide direct evidence of FSI and help improve interaction models, which is essential for precise neutrino energy reconstruction in future experiments like DUNE. Our Goal: Develop an analysis to detect particles heavier than protons in ICARUS data to better constrain FSI models.
Utilizing a helical magnet profile to enhance axion-photon conversion showed great promise in laboratory searches for high axion masses. We extend the mechanism, known as the axion-magnetic resonance (AMR), from laser experiments to axion helioscopes and demonstrate its potential in covering QCD axion parameter space. Specifically, we apply AMR to the CAST experiment legacy, make projections for the upcoming IAXO experiment, and assess its implications for both axion-like particles and QCD axions. We observe considerable improvement in the experiment’s sensitivity reach in all cases.
Polarimetry is one of the most promising types of remote sensing for improved characterization of atmospheric aerosol. Indeed, aerosol particles constitute a highly variable atmospheric component characterized by a large number of parameters describing particle sizes, morphologies (including shape and internal structure), absorption and scattering properties, amounts, horizontal and vertical distribution, etc. Reliable monitoring of all these parameters is very challenging, and therefore the aerosol effects on climate and environment are considered to be among the most uncertain factors in climate and environmental research. In this regard, observations that provide both the angular distribution of the scattered atmospheric radiation as well as its polarization state at multiple wavelengths covering the UV–SWIR spectral range carry substantial implicit information on the atmospheric composition. Therefore, high expectations in improving aerosol characterization are associated with detailed passive photopolarimetric observations. The critical need to use space-borne polarimetry for global accurate monitoring of detailed aerosol properties was first articulated in the late 1980s and early 1990s. By now, several orbital instruments have already provided polarization observations from space, and a number of advanced missions are scheduled for launch in the coming years by international and national space agencies. The first and most extensive record of polarimetric imagery was provided by POLDER-I, POLDER-II, and POLDER/PARASOL multi-angle multi-spectral polarization sensors. Polarimetric observations with the POLDER-like design intended for collecting extensive multi-angular multi-spectral measurements will be provided by several instruments, such as the MAI/TG-2, CAPI/TanSat, and DPC/GF-5 sensors recently launched by the Chinese Space Agency. Instruments such as the 3MI/MetOp-SG, MAIA, SpexOne and HARP2 on PACE, POSP, SMAC, PCF, DPC–Lidar, ScanPol and MSIP/Aerosol-UA, MAP/Copernicus CO2 Monitoring, etc. are planned to be launched by different space agencies in the coming decade. The concepts of these future instruments, their technical designs, and the accompanying algorithm development have been tested intensively and analyzed using diverse airborne prototypes. Certain polarimetric capabilities have also been implemented in such satellite sensors as GOME-2/MetOp and SGLI/GCOM-C.
CuInSe 2 nanocrystals offer promise for optoelectronics including thin-film photovoltaics and printed electronics. Additive manufacturing methods such as photonic curing controllably sinter particles into quasi-continuous films and offer improved device performance. To gain understanding of nanocrystal response under such processing conditions, we investigate impacts of photoexcitation on colloidal nanocrystal lattices via time-resolved X-ray diffraction. We probe three sizes of particles and two capping ligands (oleylamine and inorganic S 2- ) to evaluate resultant crystal lattice temperature, phase stability, and thermal dissipation. Elevated fluences produce heating and loss of crystallinity, the onset of which exhibits particle size dependence. We find size-dependent recrystallization and cooling lifetimes ranging from 90 to 200 ps with additional slower cooling on the nanosecond time scale. Sulfide-capped nanocrystals show faster recrystallization and cooling compared to oleylamine-capped nanocrystals. Using these lifetimes, we find interfacial thermal conductivities from 3 to 28 MW/(m 2 K), demonstrating that ligand identity strongly influences thermal dissipation.
Using aircraft in-situ measurements, the microphysics of cirrus clouds observed on 28 Oct. 1986 during FIRE were examined. Results are presented as one component of a coordinated study of the cirrus on the day. The study contributes to the understanding of cold clouds by: (1) providing microphysical data to supplement satellite and aircraft data for investigating cirrus cloud radiative effects; (2) providing more complete information on ice particle evolution and cloud forcing mechanisms than has been available through the use of instrumentation with higher resolution and more accurate calibration; (3) expanding the knowledge of the particle characteristics in cold liquid water clouds, through improved instrumentation and by making use of sensors on other platforms, such as lidar; and (4) by estimating the ice nucleus concentrations active at low temperatures in the upper troposphere from the concentrations of ice particles in colloidally stable liquid water clouds.
Using aircraft in-situ measurements, the microphysics of cirrus clouds observed on 28 Oct. 1986 during FIRE were examined. Results are presented as one component of a coordinated study of the cirrus on the day. The study contributes to the understanding of cold clouds by: (1) providing microphysical data to supplement satellite and aircraft data for investigating cirrus cloud radiative effects; (2) providing more complete information on ice particle evolution and cloud forcing mechanisms than has been available through the use of instrumentation with higher resolution and more accurate calibration; (3) expanding the knowledge of the particle characteristics in cold liquid water clouds, through improved instrumentation and by making use of sensors on other platforms, such as lidar; and (4) by estimating the ice nucleus concentrations active at low temperatures in the upper troposphere from the concentrations of ice particles in colloidally stable liquid water clouds.
Using continuously-differentiable (C 1 ) interpolation methods previously developed for computer visualization and other applications, a new class of shape functions is constructed and applied to electrostatic (ES) Particle-In-Cell (PIC) simulations on simplex (triangle or tetrahedral) meshes. The resulting shape functions are non-negative and partition unity,and lead to a reduction of shot noise and aliasing associated with particle interpolation to and from the mesh. For an energy-conserving implementation as chosen, C 1 interpolation of the potential leads to a continuous (C 0 ) electric field, with associated improved fidelity of particle motion.