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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Assessment of Internal Fabric of Particulate Materials

Particle arrangement and distribution within a soil matrix has long been recognized as having significant influence on the mechanical behavior of cohesionless soils. It is well known that two soil specimens having the same grain type (e.g., quartz, feldspar, etc.), same grain size distribution and relative density (or void ratio) can display completely different mechanical behavior. Because of the different fabric configurations in the otherwise similar specimens, they are likely to have different mechanical properties such as stress-strain response, anisotropy, dilatancy, etc. Soil Fabric is defined as the arrangement of particles, particle groups and associated pore space. In the literature, fabric analysis techniques are mainly classified as destructive (e.g., specimen stabilization, thin-sectioning, and microscopy), and nondestructive techniques (e.g., magnetic resonance imaging, ultrasonic testing, x-ray radiography, and computed tomography). Quantifying the void ratio and its distribution is the main parameter used to describe the fabric of particulate materials. This paper presents a comprehensive literature review of fabric analysis techniques applied to particulate materials. In addition, the results of a comprehensive investigation to quantify void ratio of sand specimens will be presented and discussed. The sand used in the experiments in a natural, uniform rounded to sub-rounded silica sand known as F-75 banding sand with mean particle size of 0.22 mm. Uniform specimens and specimens subjected to different axial-strain levels tested under triaxial and biaxial conditions are examined to evaluate void ratio evolution and its distribution using destructive thin-sectioning and nondestructive Computed Tomography (CT) techniques. Details of a new innovative polygon generation technique called Voronoi tessellation used to quantify void ratio of microscopic images of sand grains will be presented and compared to classical Oda's method. Finally, frequency distribution of void ratio calculated using CT analysis will be presented and discussed.

Alshibi, Khalid A.↗
DOE OSTI2026

Haze processing of atmospheric particles during wintertime in the Indo-Gangetic Plains

The impacts of haze on visibility, air quality, and climate are not well quantified due to a lack of understanding of the evolution of the mixing state and phase state of atmospheric particles during haze processing. The variability of the mixing state of atmospheric particles contributes significantly to uncertainties associated with the estimated aerosol radiative forcing. We collected particle samples in January 2018 from the highly polluted Indo-Gangetic plain during hazy conditions to study haze-processed particles. Single particle analysis using multi-modal micro-spectroscopy techniques revealed an abundance (40–70% by number) of potassium-rich sulfate particles from biomass-burning influenced smoke. Tilted view imaging showed that most of the organic particles that had inorganic potassium and sulfate inclusions were liquid-like while those without inclusions were more semi-solid. High-resolution mass spectrometry analysis revealed a significant presence of organosulfates and nitroxy-organosulfates in the morning samples (24%) compared to the afternoon samples (9%), despite higher relative humidity in the afternoon. Overall, our results highlight the significant contribution of both organic and inorganic sulfate to the total particulate sulfur budget during haze processing in winter, when anthropogenic emissions such as household burning, agricultural burning, and vehicular emissions are major contributors to particle mass.

Mathai, Susan [Pacific Northwest National Laborato↗
DOE OSTI2023

Molecular Imaging Reveals Two Distinct Mixing States of PM 2.5 Particles Sampled in a Typical Beijing Winter Pollution Case

Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM 2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles, while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. Finally, the new results provide key 3-D molecular information of mixing states, which is highly desirable for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models, and improving the understanding of aerosols on air quality and human health.

3-D molecular imaging↗
DOE OSTI2025

Review: Recent advances of ToF-SIMS for environmental analysis and imaging

Background: Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis technique, initially developed and applied in inorganic materials and semiconductors. In past decades, ToF-SIMS has attracted more attention in its analysis capabilities of organic materials, with increased applications in biology, medical, and health development. It has also become a versatile and effective tool in environmental analysis due to its high mass resolution, mass accuracy, and depth profiling. Results: In this review, we first give an overview of the principle of ToF-SIMS and follow with recent ToF-SIMS applications in exemplary environmental study cases, including atmospheric aerosol, soil, water, plant, and organic solvent analysis. Moreover, sample preparation techniques are summarized in relation to corresponding environmental applications. Specifically, we call attention to ToF-SIMS investigations showcasing studies in surface chemical compositions, images, and depth profile analysis. These findings emphasize the important role of interfacial chemistry in environmental processes and provide valuable insights into dynamic processes, such as chemical transformation, particle formation, plant biology, and microbial inspired biotechnology development. The mass spectral imaging results acquired by ToF-SIMS offer a deeper understanding of intermediate stages and transient phases for environmental specimens. Significance: In situ and operando imaging offer new possibilities in studying phenomena in real time with high spatial resolution. Furthermore, it is anticipated that more research groups will use ToF-SIMS in environmental research given recent advances in measurement capabilities and surging needs in chemical mapping of complex analytes and systems.

Aerosol↗
DOE OSTI2023

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗
DOE OSTI2026

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2019

Noise Measurements of a Low-Noise Top-Mounted Propulsion Installation for a Supersonic Airliner

A model-scale exhaust system was tested to validate low-noise concepts and noise prediction methods. The tests involved far-field acoustics, translating phased array, and particle image velocimetry; this report covers the far-field acoustic measurements. Data were acquired for a series of nozzles with different chevron designs, both uninstalled and installed on a representative aircraft planform. The impact of the various chevron treatments on the far-field noise was documented, along with the impact of the pylon and planform. For the baseline nozzle, installation produced a 2EPNdB reduction, as assumed in system studies. Chevrons were used to shift noise sources upstream to maximize the installation benefits and to reduce unshielded sources downstream. These resulted in reductions of 4-5EPNdB relative to the uninstalled baseline nozzle. Detailed analysis of spectral directivities behind the integrated EPNL metric gave insight into how well these concepts actually work. When correlated with particle image velocimetry measurements and phased array measurements, reported in companion papers, the explanation of acoustic benefits from top-mounted propulsion is clear as is the path toward optimization of the concept.

Supersonics↗
NASA NTRS2008

Sensitivity of Multiangle Imaging to the Optical and Microphysical Properties of Biomass Burning Aerosols

The treatment of biomass burning (BB) carbonaceous particles in the Multiangle Imaging SpectroRadiometer (MISR) Standard Aerosol Retrieval Algorithm is assessed, and algorithm refinements are suggested, based on a theoretical sensitivity analysis and comparisons with near-coincident AERONET measurements at representative BB sites. Over the natural ranges of BB aerosol microphysical and optical properties observed in past field campaigns, patterns of retrieved Aerosol Optical Depth (AOD), particle size, and single scattering albedo (SSA) are evaluated. On the basis of the theoretical analysis, assuming total column AOD of 0.2, over a dark, uniform surface, MISR can distinguish two to three groups in each of size and SSA, except when the assumed atmospheric particles are significantly absorbing (mid-visible SSA approx.0.84), or of medium sizes (mean radius approx.0.13 pin); sensitivity to absorbing, medium-large size particles increases considerably when the assumed column AOD is raised to 0.5. MISR Research Aerosol Retrievals confirm the theoretical results, based on coincident AERONET inversions under BB-dominated conditions. When BB is externally mixed with dust in the atmosphere, dust optical model and surface reflection uncertainties, along with spatial variability, contribute to differences between the Research Retrievals and AERONET. These results suggest specific refinements to the MISR Standard Aerosol Algorithm complement of component particles and mixtures. They also highlight the importance for satellite aerosol retrievals of surface reflectance characterization, with accuracies that can be difficult to achieve with coupled surface-aerosol algorithms in some higher AOD situations.

Chen, Wei-Ting↗
NASA NTRS2008

New Insights into the Composition and Texture of Lunar Regolith Using Ultrafast Automated Electron-Beam Analysis

Sieved grain mounts of Apollo 16 drive tube samples have been examined using QEMSCAN - an innovative electron beam technology. By combining multiple energy-dispersive X-ray detectors, fully automated control, and off-line image processing, to produce digital mineral maps of particles exposed on polished surfaces, the result is an unprecedented quantity of mineralogical and petrographic data, on a particle-by-particle basis. Experimental analysis of four size fractions (500-250 microns, 150-90 microns, 75-45 microns and < 20 microns), prepared from two samples (64002,374 and 64002,262), has produced a robust and uniform dataset which allows for the quantification of mineralogy; texture; particle shape, size and density; and the digital classification of distinct particle types in each measured sample. These preliminary data show that there is a decrease in plagioclase modal content and an opposing increase in glass modal content, with decreasing particle size. These findings, together with data on trace phases (metals, sulphides, phosphates, and oxides), provide not only new insights into the make-up of lunar regolith at the Apollo 16 landing site, but also key physical parameters which can be used to design lunar simulants, and compute Figures of Merit for each material produced.

Rickman, Doug↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
DOE OSTI2022

Quantifying the Impact of Charge Rate and Number of Cycles on Structural Degeneration of Li-Ion Battery Electrodes

A quantitative link between crack evolution in lithium-ion positive electrodes and the degrading performance on cells is not yet well established nor is any single technique capable of doing so widely available. Here, we demonstrate a widely accessible high-throughput approach to quantifying crack evolution within electrodes. The approach applies super-resolution scanning electron microscopy (SEM) imaging of cross-sectioned NMC532 electrodes, followed by segmentation and quantification of crack features. Crack properties such as crack intensity, crack width and length are quantified as a function of charge rate (1C, 6C, and 9C) and cycle number (25, 225, and 600 cycles). Hundreds of particles are characterized for statistical confidence in the quantitative crack measurements. The data on crack evolution is compared to electrochemical data from full cells and half cells with the NMC532 positive electrodes. We show that while crack evolution strongly correlates with capacity fade in the first 25 cycles, it does not correlate well for the following hundreds of cycles indicating that cracking may not be the dominant cause of capacity fade throughout the cycle-life of cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Multi-Particle Three-Dimensional Covariance Imaging: “Coincidence” Insights into the Many-Body Fragmentation of Strong-Field Ionized D 2 O

We demonstrate the applicability of covariance analysis to three-dimensional velocity-map imaging experiments using a fast timestamping detector. Studying the photofragmentation of strong-field doubly ionized D$_2$O molecules, we show that combining high count rate measurements with covariance analysis yields the same level of information typically limited to the `gold standard' of true, low count rate coincidence experiments, when averaging over a large ensemble of photofragmentation events. This increases the effective data acquisition rate by approximately two orders of magnitude, enabling a new class of experimental studies. This is illustrated through an investigation into the dependence of three-body D$_2$O$^{2+}$ dissociation on the intensity of the ionizing laser, revealing mechanistic insights into the nuclear dynamics driven during the laser pulse. Here, the experimental methodology laid out, with its drastic reduction in acquisition time, is expected to be of great benefit to future photofragment imaging studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Dynamics Explorer measurements of particles, fields, and plasma drifts over a horse-collar auroral pattern

As shown from ground-based measurements and satellite-borne imagers, one type of global auroral pattern characteristic of quiet (usually northward IMF) intervals is that of a contracted but thickened emission region of a pattern referred to as 'horse-collar' aurora (Hones et al., 1989). In this report we use the Dynamics Explorer data set to examine a case in which this horse-collar pattern was observed by the DE-1 auroral imager, while at the same time DE-2, at lower altitude, measured precipitating particles, electric and magnetic fields, and plasma drifts. Our analysis shows that, in general, there is close agreement between the optical signatures and the particle precipitation patterns. In many instances, over scales ranging from tens to a few hundred kilometers, electron precipitation features and upward field-aligned currents are observed at locations where the plasma flow gradients indicate negative V-average x E. The particle, plasma, and field measurements made along the satellite track and the 2D perspective of the imager provide a means of determining the configuration of convective flows in the high-latitude ionosphere during this interval of northward IMF. Recent mapping studies are used to relate the low-altitude observations to possible magnetospheric source regions.

Sharber, J. R.↗
NASA NTRS2007

Genesis Concentrator Target Particle Contamination Mapping and Material Identification

The majority of surface particles were found to be < 5 microns in diameter with increasing numbers close to the optical resolution limit of 0.3 microns. Acceleration grid EDS results show that the majority of materials appear to be from the SRC shell and SLA materials which include carbon-carbon fibers and Si-rich microspheres in a possible silicone binder. Other major debris material from the SRC included white paint, kapton, collector array fragments, and Al. Image analysis also revealed that SRC materials were also found mixed with the Utah mud and salt deposits. The EDS analysis of the acceleration grid showed that particles < 1 m where generally carbon based particles. Chemical cleaning techniques with Xylene and HF in an ultrasonic bath are currently being investigated for removal of small particles by the Genesis science team as well as ultra-pure water megasonic cleaning by the JSC team [4]. Removal of organic contamination from target materials is also being investigated by the science team with the use of UV-ozone cleaning devices at JSC and Open University [5]. In preparation for solar wind oxygen analyses at UCLA and Open University [1, 2], surface particle contamination on three Genesis concentrator targets was closely examined to evaluate cleaning strategies. Two silicon carbide (Genesis sample # 60001 and 60003) and one chemical vapor deposited (CVD) 13C concentrator target (60002) were imaged and mosaic mapped with optical microscopes. The resulting full target mosaic images and particle feature maps were subsequently compared with non-flight, but flight-like, concentrator targets and sample return capsule (SRC) materials. Contamination found on the flown concentrator acceleration grid was further examined using a scanning electron microscope (SEM). Energy dispersive X-ray spectroscopy (EDS) for particle identification was subsequently compared with the optical images from the flown targets. Figure 1 show that all three targets imaged in this report are fully intact and do not show any signs of material fractures. However, previous ellipsometry results and overview imaging of both flown SiC targets show a solar wind irradiation gradient from the center focal point to the outer edge [3]. In addition, due to the hard landing, each target has experienced varying degrees of impacts, scratches, and particle debris from the spacecraft and Utah impact site.

Calaway, Michael J.↗
NASA NTRS2003

Identification of Presolar Spinel Grains from a Murray Residue by Multi-Detection Raster Imaging

Grain size separate CG from the Murray CM2 carbonaceous chondrite contains mostly spinel grains of average diameter 0.5 m. Zinner et al. found that approximately 1% of these spinel grains are of presolar origin as determined by their large O isotopic anomalies. These O isotopic measurements were made with the NanoSIMS on individual grains that were well separated from one another on a gold foil. The grains were selected for analysis from secondary electron and secondary O-16(-) images. The primary beam was then successively deflected onto these single grains for O isotopic analysis. While single grain analysis on dispersed samples is effective for finding relatively abundant anomalous grains, ion imaging in a raster mode on tightly packed grains might be more efficient for locating few anomalous grains among predominantly isotopically normal grains. In fact, this was the analysis mode used by Messenger et al. to discover presolar silicates in interplanetary dust particles. In an exploratory effort that is also geared toward establishing the optimum isotopic imaging technique in the search for presolar silicate grains in primitive meteorites, we measured O isotopic ratios in spinel grains from the Murray CG separate by raster imaging of areas with more or less tightly packed grains.

Nguyen, A.↗
NASA NTRS1981

Wedge-and-strip anodes for centroid-finding position-sensitive photon and particle detectors

The paper examines geometries employing position-dependent charge partitioning to obtain a two-dimensional position signal from each detected photon or particle. Requiring three or four anode electrodes and signal paths, images have little distortion and resolution is not limited by thermal noise. An analysis of the geometrical image nonlinearity between event centroid location and the charge partition ratios is presented. In addition, fabrication and testing of two wedge-and-strip anode systems are discussed. Images obtained with EUV radiation and microchannel plates verify the predicted performance, with further resolution improvements achieved by adopting low noise signal circuitry. Also discussed are the designs of practical X-ray, EUV, and charged particle image systems.

Martin, C.↗
DOE OSTI2024

Multitiered computational methodology for extracting three-dimensional rotational diffusion coefficients from x-ray photon correlation spectroscopy data without structural information

X-ray photon correlation spectroscopy (XPCS) is a powerful technique for analyzing particle systems by investigating their dynamics in suspensions across a broad range of temporal and spatial scales. This is done by illuminating samples with coherent x-ray beams and calculating the correlation function of the obtained x-ray scattering images. XPCS is uniquely suited for studying Brownian dynamics, consisting of translational and rotational diffusion. While traditional XPCS image analysis techniques can extract translational diffusion components, they are unable to estimate rotational diffusion coefficients. Here, we introduce a methodology that combines the angular-temporal cross-correlation analysis and a algorithmic framework called Multi-Tiered Estimation for Correlation Spectroscopy in 3D for estimating three-dimensional rotational diffusion coefficients from XPCS images of three-dimensional particle systems. We demonstrate our methodology for extracting rotational diffusion coefficients from XPCS data by applying it to simulated noisy x-ray images of systems of crossing nanotubes and proteins that evolve under translational and rotational Brownian motion for different diffusion rates. Furthermore, our results show that our approach determines rotational diffusion coefficients within a few percent error.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Analysis of TRMM Microphysical Measurements: Tropical Rainfall Measuring Mission (TRMM)

SPEC Incorporated participated in three of the four TRMM field campaigns (TEFLUN-A, TEFLUN-B and KWAJEX), installing and operating a cloud particle imager (CPI) and a high volume precipitation spectrometer (HVPS) on the SPEC Learjet in TEFLUN-A, the University of North Dakota Citation in TEFLUN-B and KWAJEX, and a CPI on the NASA DC-8 in KWAJEX. This report presents and discusses new software tools and algorithms that were developed to analyze microphysical data collected during these field campaigns, as well as scientific interpretations of the data themselves. Software algorithms were developed to improve the analysis of microphysical measurements collected by the TRMM aircraft during the field campaigns. Particular attention was paid to developing and/or improving algorithms used to compute particle size distributions and ice water content. Software was also developed in support of production of the TRMM Common Microphysical Product (CMP) data files. CMP data files for TEFLUN-A field campaign were produced and submitted to the DAAC. Typical microphysical properties of convective and stratiform regions from TEFLUN-A and KWAJEX clouds were produced. In general, it was found that in the upper cloud region near -20 to -25 C, stratiform clouds contain very high (greater than 1 per cubic centimeter) concentrations of small ice particles, which are suspected to be a residual from homogeneous freezing and sedimentation of small drops in a convective updraft. In the upper cloud region near -20 to -25 C, convective clouds contain aggregates, which are not found lower in the cloud. Stratiform clouds contain aggregates at all levels, with the majority in the lowest levels. Convective cloud regions contain much higher LWC and drop concentrations than stratiform regions at all levels, and higher LWC in the middle and upper regions. Stratiform clouds contain higher IWC than convective clouds only at the lowest level. Irregular shaped ice particles are found in very high concentrations throughout both convective and stratiform cloud regions. A striking difference in particle shape in cirrus formed in situ, cirrus formed from maritime anvils and cirrus formed from continental anvils. Over 50% of the mass of in situ cirrus ice particles is composed of bullet rosettes, while bullet rosettes are virtually non-existent in maritime and tropical anvils. Tropical anvils are composed of mostly singular, plates, capped columns, and blocky irregular shapes, while continental anvils have a much higher percentage of aggregates, some of which are chains of small spheroidal particles that appear to result from homogeneous freezing of drops. A correlation between high electric fields in continental anvils and the formation of aggregates is hypothesized.

Source record↗