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Pipette analysis and X-ray diffraction techniques were employed to characterize the particle size distribution and clay mineral content of the feldspar, calvert, ball, and jordan soils. In general, the ball, calvert, and jordan soils were primarily clay size particles composed of kaolinite and illite whereas the feldspar soil was primarily silt-size particles composed of quartz and feldspar minerals.
Context. On 2020 November 29, the first widespread solar energetic particle (SEP) event of solar cycle 25 was observed at four widely separated locations in the inner (. 1AU) heliosphere. Relativistic electrons as well as protons with energies > 50MeV were observed by Solar Orbiter (SolO), Parker Solar Probe (PSP), the Solar Terrestrial Relations Observatory (STEREO)-A and multiple near-Earth spacecraft. The SEP event was associated with an M4.4 class X-ray flare and accompanied by a coronal mass ejection (CME) and an extreme ultraviolet (EUV) wave as well as a type II radio burst and multiple type III radio bursts. Aims. We present multi-spacecraft particle observations and place them in context with source observations from remote sensing instruments and discuss how such observations may further our understanding of particle acceleration and transport in this widespread event. Methods. Velocity dispersion analysis (VDA) and time shift analysis (TSA) were used to infer the particle release times at the Sun. Solar wind plasma and magnetic field measurements were examined to identify structures that influence the properties of the energetic particles such as their intensity. Pitch angle distributions and first-order anisotropies were analyzed in order to characterize the particle propagation in the interplanetary medium. Results. We find that during the 2020 November 29 SEP event, particles spread over more than 230° in longitude close to 1AU. The particle onset delays observed at the different spacecraft are larger as the flare–footpoint angle increases and are consistent with those from previous STEREO observations. Comparing the timing when the EUV wave intersects the estimated magnetic footpoints of each spacecraft with particle release times from TSA and VDA, we conclude that a simple scenario where the particle release is only determined by the EUV wave propagation is unlikely for this event. Observations of anisotropic particle distributions at SolO, Wind, and STEREO-A do not rule out that particles are injected over a wide longitudinal range close to the Sun. However, the low values of the first-order anisotropy observed by near-Earth spacecraft suggest that diffusive propagation processes are likely involved.
Particulate matter (PM) pollution has become a major environmental concern in many developing countries. PM pollution control remains a great challenge owing to the complex sources and evolution processes of PM particles. There are two categories of PM, i.e., primary and secondary PM particles, and the primary PM emissions play a key role in the formation of PM pollution. Knowledge of primary PM particle compositions, sources, and evolution processes is of great importance to the effective control of PM pollution. In order to characterize PM particles effectively, their fundamental properties including the morphology, concentration distribution, surface chemistry, and composition must be systematically investigated. In this study, we collected and analyzed six types of PM 10 and PM 2.5 particles from different sources using an in situ sampling approach. The concentration distributions of PM particles were analyzed and comparative analysis of the morphologies, distributions, capture mechanisms, and compositions of PM particles was conducted using scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and energy-dispersive X-ray spectroscopy. We found that there were significant differences in the structures, morphologies, and capture mechanisms of PM 2.5 and PM 10 particles. As a result, the systematic comparative investigation in this work will benefit the study of evolution processes and the effective control of PM pollution in the future.
NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.
NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.
Report describes computer-simulation study of motions of various numbers of ions in Paul trap. Study part of continuing effort to understand motions of trapped charged particles (atoms, ions, molecules, or dust particles). Motions characterized in terms of heating by radio-frequency fields, formation of crystallike structures in cold clouds of trapped particles, and other phenomena important in operation of radio-frequency traps in frequency standards.
This paper presents the results of detailed analyses of the images from experiments that were conducted on the formation of solid hydrogen particles in liquid helium. Solid particles of hydrogen were frozen in liquid helium, and observed with a video camera. The solid hydrogen particle sizes, their agglomerates, and the total mass of hydrogen particles were estimated. Particle sizes of 1.9 to 8 mm (0.075 to 0.315 in.) were measured. The particle agglomerate sizes and areas were measured, and the total mass of solid hydrogen was computed. A total mass of from 0.22 to 7.9 grams of hydrogen was frozen. Compaction and expansion of the agglomerate implied that the particles remain independent particles, and can be separated and controlled. These experiment image analyses are one of the first steps toward visually characterizing these particles, and allow designers to understand what issues must be addressed in atomic propellant feed system designs for future aerospace vehicles.
The indoor air quality of the International Space Station (ISS), in terms of particulate matter, has been assessed through a sampling experiment that collected airborne debris for return to Earth. The Aerosol Sampling Experiment took place on ISS in December 2016 and January 2017, with sample return in February 2017. For redundancy, two different aerosol samplers collected particles in two size ranges spanning from 10 nm to hundreds of micrometers. Multiple analysis techniques have been used to characterize the particles, such as reflective light microscopy, manual scanning electron microscopy (SEM) analysis (secondary and backscattered imaging) with energy dispersive spectroscopy (EDS) x-ray analysis, computer controlled scanning electron microscopy (CCSEM) and Raman spectroscopy. Sampling took place in five locations on ISS, with the greatest deposition of particles in Node 3, followed by Node 1, the US Lab and Node 2. The PMM had very few airborne particles, as expected, owing to the lack of human presence. A large proportion of the sampled material consisted of fibers from clothing. Many particles had complex morphologies or contained multiple metals in a carbonaceous matrix. Metal particles were analyzed for each sampling location in terms of both weight and number percent, with 27 heavy metals detected. Fiberglass and TiO2 particles were present in every location. Quantitative analysis results are presented, and where possible, particle emission sources are identified with the intention to fuel discussions on mitigation.
This paper presents a new type of analysis for predicting the thermal conductivity of disperse composites from the properties of the component phases and elementary characterizations of particle shapes and orientation. This analysis successfully predicted the sensitivity to particle shape which was confirmed by experiments also reported in this paper. These results suggest that highly elongated particles may be used to achieve dramatic modifications of thermal conductivity and the analysis presented here may be a useful tool in the design or development of disperse composites of specific thermal conductivity. The analysis may also apply to other properties such as electrical conductivity or magnetic permeability.
This project improved understanding of how atmospheric aerosol particles form and evolve, with a focus on the role of water-driven (aqueous-phase) chemical reactions in the atmosphere. These processes occur in clouds, fog, and humid air and can significantly change the composition and properties of airborne particles, known as aerosols, which influence air quality and climate. By combining field measurements, laboratory experiments, and advanced analytical techniques, the project identified key chemical signatures that allow scientists to distinguish particles formed through aqueous processes from those formed in the gas phase. Observations from multiple environments, including wildfire smoke, urban regions, and cloud-influenced areas, show that aqueous chemistry is an important pathway for particle formation and aging. The project also developed new measurement approaches using uncrewed aerial systems (UAS) to capture how aerosol composition varies with altitude, providing critical insights into how particles interact with clouds. In addition, new data analysis frameworks were created to better interpret long-term aerosol measurements and improve characterization of particle sources and transformations. These results have been integrated into a global database of aerosol measurements and used to support atmospheric modeling efforts. Overall, the project provides important tools and knowledge to improve predictions of how aerosols affect climate and air quality, particularly through their interactions with radiation and clouds.
The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.
Nuclear fusion between protons and boron-11 nuclei has undergone a revival of interest thanks to the rapid progress in pulsed laser technology. Potential applications of such reaction range from controlled nuclear fusion to radiobiology and cancer therapy. A laser-driven fusion approach consists in the interaction of high-power, high-intensity pulses with H- and B-rich targets. We report on an experiment exploiting proton-boron fusion in CN-BN targets to obtain high-energy alpha particle beams (up to 5 MeV) using a very compact approach and a tabletop laser system with a peak power of ~10 GW, which can operate at high-repetition rate (up to 1 kHz). The secondary resonance in the cross section of proton-boron fusion (~150 keV in the center-of-mass frame) is exploited using a laser-based approach. The generated alpha particles are characterized in terms of energy, flux, and angular distribution using solid-state nuclear-track detectors, demonstrating a flux of ~10 5 particles per second at 10 Hz, and ~10 6 per second at 1 kHz. Hydrodynamic and particle-in-cell numerical simulations support our experimental findings. Potential impact of our approach on future spread of ultra-compact, multi-MeV alpha particle sources driven by moderate intensity (10 16 -10 17 W/cm 2 ) laser pulses is anticipated.
Results are presented from analyses that were conducted to explain the presence of chromium, detected noninvasively using energy dispersive X-ray fluorescence (XRF), in the unusually large (2-3mm diameter) rough gem-like purple pigment particles in the paint used for a Faiyum mummy portrait. An approximately 50 µm diameter particle of the chromium-containing purple pigment was extracted from the Portrait of a Bearded Man, dated to Roman Imperial Egypt in the second century, circa 170-180 CE, accession #32.6 in the Walters Art Museum collection. The particle was characterized using energy dispersive X-ray fluorescence analysis, electron microscopy, diffraction, and atom probe tomography. It is demonstrated that the purple pigment particle is a heterogeneous organic pigment, specifically, a lake pigment likely derived from either plant or insect matter, which contains minor percentages of both transition metals and alkali / alkali earth metals, with nanometer-scale crystallites of lead carbonates and sulfates. The analyses revealed for the first time the nanoscale microstructure and stratigraphy in an ancient lake pigment. Results suggest that similarities with respect to time-period and place of production may be developed among unprovenienced Faiyum mummy portraits to help localize workshops or artists, using analyses focused on lake pigments to characterize specifically metal-based mordants.
To study neutron-induced charged-particle reactions with high precision, the Low Energy Neutron-induced Charged-particle (Z) instrument (LENZ) was developed at the Los Alamos Neutron Science Center. For the interest of measuring (n,p) and (n, α) reactions simultaneously, Pulse Shape Discrimination methods were investigated to identify different charged particles in the energy range of 3 - 20 MeV and improve signal-to-background ratios using Double-sided Silicon Strip Detectors and waveform digitizers. The risetime and pulse shape properties of detected charged particles were characterized for various silicon detector’s thickness with different orientations. During the post-processing of waveforms, we implemented different digital filters for effective particle identifications and improved energy- and timing- resolutions. We validated the optimized digital filters and pulse shape analyses, via measurements with 228 Th and 229 Th calibration sources, proton-induced reactions on a 7 LiF target, and neutron-induced reactions on CH 2 , Ta 2 O 5 , 58 Ni, and 6 LiF/ 59 Ni targets at the time-of-flight facility, LANSCE. In conclusion, the summary of effective thresholds and Figure of Merits on separating different charged particles is reported.
MiniFuel compacts containing 20 individual tristructural isotropic (TRISO)-coated fuel particles were characterized to provide supporting preirradiation characterization data. The preirradiated characterization data supports irradiation capsule design and safety analysis, as well as downstream postirradiation examination (PIE) for a planned MiniFuel irradiation to explore high particle powers. The analysis included dimensional inspection, x-ray radiography and tomography, as-fabricated defect fraction analysis, and a matrix impurity analysis.
This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of V ORO ++, enabling the analysis of systems with billions of particles on high-performance computer architectures.
In order to estimate the radiation shielding effectiveness of materials it is necessary to know cosmic ray particles are broken up as they pass though these materials. The breakup of cosmic ray particles is characterized by the nuclear fragmentation cross sections, i.e. an effective geometrical cross section assigned to each target nucleus that represents its apparent size for fragmenting the incident particle. The values of these cross sections depend on the details of nuclear physics and cannot be calculated from first principles owing to the many-body nature of the interactions. The only way to determine them is to measure them. Once a sufficient number of cross sections have been measured, the systematic nature of the interactions allows other cross-sections to be estimated. The number of cross sections that contribute to the estimation of shielding effectiveness is very large 10,000. Fortunately most make minor contributions. These can be estimated from nuclear systematics. Only those who's uncertainties make significant contributions to the error in the shielding effectiveness estimations need to be measured. In the past it has proven difficult to measure light fragment production cross sections from the interactions of heavy cosmic rays owing to the size of the detectors used. We have developed a highly pixilated silicon (Si) detector system that can individually identify these light fragments while making efficient use of costly accelerator time. This system is an outgrowth of detector technology developed under a CDDF and a Code S sponsored cosmic ray experiment.
An optical measurement technique known as Three-Dimensional Digital Particle Image Velocimetry (3-D DPIV) was used to characterize the tip clearance flow in NASA Glenn Research Center's low-speed axial compressor. 3-D DPIV is a technique in which a stereoscopic imaging system consisting of two cross-correlation cameras is used to record particles entrained in a flow as a laser light sheet is pulsed at two instances in time. Although 3-D DPIV has been used elsewhere, this is the first time it has been used to measure compressor tip clearance flows. In-house modifications of the DPIV system include the use of effective seeding technology and a novel system to perform a priori calibrations at all five measurement planes, greatly reducing facility run time. Computational fluid dynamics predictions, which are used to guide design changes toward improving the efficiency and operating range of turbomachinery, can be verified and improved by comparison with 3-D DPIV measurements of the actual tip clearance flow. This measurement campaign dealt with the characterization of the tip clearance vortex in the first stage of a four-stage axial compressor. The tip clearance vortex is formed in compressors operating with a clearance gap between the moving rotor blade tips and the stationary casing when a leakage flow, forced from the pressure side of the blade over the blade tip, forms a vortical structure on the suction side of the blade. 3-D DPIV is ideally suited to measure the clearance vortex for two reasons: (1) this technique captures the entire blade passage flow at one instant in time, so that wandering of the vortex during the measurement does not smear out velocity gradients in the flow field, and (2) the spanwise component of velocity changes sign across the vortex core, providing a more accurate measurement of the vortex location than was available with previous two-dimensional measurement approaches. These two attributes of the data will enable computational fluid dynamics researchers to validate their predictions to a level of accuracy not previously attainable. In an effort to understand the effects of this flow phenomenon on the operation of the low speed axial compressor, data were acquired at two mass flow coefficients: 0.395 (design operating point) and 0.35 (operating point just above stall). In order to identify the spatial extent, location, and magnitude of the tip clearance vortex for each mass flow condition, data were acquired at five equally spaced spanwise locations, from 90- to 100-percent span. The data presented shows a cross section of the tip clearance vortex at 94-percent span and a mass flow coefficient of 0.395, where the color contours represent the radial velocity component. The blue (flow towards the hub) and red (flow towards the casing) regions illustrate the extent of the tip clearance vortex. The interface between the blue and red regions delineates the location of the vortex core.