Individual Particle Analysis Research Articles

The relationship between the inhalation bioaccessibility of potentially toxic elements in road dust from a heavily polluted industrial area and the source of their pollution

One of the sources of chronic exposure to potentially toxic elements (PTE), especially in polluted environments, is the inhalation of resuspended road dust (RD). The aim of this study is to assess the inhalation bioaccessibility of PTE in RD from highly polluted environments from mining/smelting industries and traffic, and to identify any correlations between the bioaccessibility fraction of PTE and the physicochemical characteristics of the particles. RD from the studied area contains extremely high total concentrations of Cr, V, and Mn, which are likely due to pollution from the smelting industry. Additionally, elevated total concentrations of other elements associated with traffic emissions including Zn, Cu, Pb, Sb, and Sn were also measured. The bioaccessibility of PTE was assessed using two synthetic extraction solutions - Gamble's solution (GS) and Artificial Lysosomal Fluid (ALF). The majority of elements showed negligible bioaccessibility in GS. However, quite high inhalation bioaccessibility was observed for Zn, Pb, Sb, Cd, and Mn in the ALF solution, with a mean bioaccessible fraction of 49, 51.5, 41, 50, and 40% respectively. The highest bioavailable fraction was measured for Cd (97%) in a sample collected near a steel production facility and for Pb (95%) in a sample collected near the highway. These results indicate that increased mobility of the elements in inhaled particles occurs only in the case of phagocytosis. The lowest inhalation bioavailability was measured for Cr (mean is 3%). Differential individual particle analysis revealed that about 60% of phases, mostly major (Cr,Ti,V)-bearing metallic alloys, silicates, oxides and sulphides, are stable in ALF solution, while 40% of phases, mostly (Fe,Ca,Mn)-bearing oxides, silicates, sulphides, metals and metallic alloys originating from steel production, ferrochrome, ferrosilicon and vanadium production and from traffic emissions have been heavily corroded or completely dissolved. The study provides valuable information to further assess health hazards from various emission sources.

Investigating nuisance dust complaints: Combining high frequency dust deposition records and source identification using integrated microanalytical techniques

While ducted dust emissions from industry are usually well regulated and controlled, fugitive dust emissions can be difficult to quantify or differentiate from off-site emissions, particularly where fugitive emissions are transient or intermittent. In this study, sources of nuisance dust were investigated using a novel dust deposition sampling methodology, followed by chemical and mineralogical analysis using optical microscopy, x-ray diffraction (XRD), scanning electron microscopy with energy dispersive x-ray spectrometry (SEM-EDS), and isotope ratio mass spectrometry analysis. Dust deposition over 24 h was collected on horizontally orientated 300 mm square glass panels at 6 sites in the region of interest. This method captured very small (<10 mg) masses of dust and could distinguish very small variations in dust deposition at different sites and on different days. Comparison samples collected from potential dust sources at a nearby lime manufacturing facility, and other potential fugitive dust sources in the region were differentiated using XRD mineralogy, visual appearance by optical microscopy and SEM-EDS analysis of individual particles. Comparison of selected dust samples to reference samples indicated most dust deposition at the study sites consisted of soil or sand. However, dust deposition at two sites was sometimes composed of a material that was similar in composition to lime that had been rehydrated to portlandite, but not yet fully carbonated to calcite. Subsequent analysis of δ13C and δ18O for selected dust samples from these two sites were consistent with rapid and recent carbonation of small particles in an alkaline environment, which could have occurred during the atmospheric release and transport of lime, and ruled out fugitive dust emission from lime stockpiles existing on site. Combining the information obtained from high frequency record of dust deposition with targeted mineralogical, isotopic and morphological examinations provided new insight into the source of fugitive dust emissions in this area.

Analysis of Individual Viral Particles by Flow Virometry.

This review focuses on the emerging field of flow virometry, the study and characterization of individual viral particles using flow cytometry instruments and protocols optimized for the detection of nanoscale events. Flow virometry faces considerable technical challenges including minimal light scattering by small viruses that complicates detection, coincidental detection of multiple small particles due to their high concentrations, and challenges with sample preparation including the inability to easily "wash" samples to remove unbound fluorescent antibodies. We will discuss how the field has overcome these challenges to reveal novel insights into viral biology.

Characterization of Respirable Coal Mine Dust Recovered from Fibrous Polyvinyl Chloride Filters by Scanning Electron Microscopy

The characterization of respirable dust on the basis of constituent fractions and particle sizes is increasingly of concern for evaluating exposure hazards. For high-resolution particle analysis, scanning electron microscopy with energy dispersive X-ray (SEM-EDX) can be an effective tool. However, it requires particles to be deposited on a smooth, uniform substrate such as a polycarbonate (PC) filter for optimal results. While direct sampling onto PC is possible, this is not the standard approach in many situations. For example, in coal mines, respirable dust samples have typically been collected onto polyvinyl chloride (PVC) filters because they are intended for gravimetric and/or infrared spectroscopy analysis. Such fibrous substrates are not ideal for SEM-EDX (or other microscopy), but an effective method to recover and redeposit the dust particles could render such samples suitable for the additional analysis. Here, we present a simple method and compare SEM-EDX results for paired samples analyzed directly on PC and following recovery from PVC and redeposition on PC. Both laboratory-generated dust samples (n = 10 pairs) and field samples of respirable coal mine dust (n = 44 pairs) are included in this study. Although some changes in particle size distributions were observed between samples analyzed directly and those that were recovered and redeposited prior to analysis, the results indicate the dust recovery method generally yields a representative sample in terms of mineral constituents. That said, results also highlighted the effects of high particle loading density on individual particle analysis. Considering all sample pairs, those with similar loading density between the directly analyzed and recovered sample tended to exhibit similar mineralogy distributions. This was generally the case for the lab-generated sample pairs, and the Freeman-Halton exact test of independence indicated that the samples in just three (of 10) pairs were in disagreement in terms of their mineralogy distributions. On the other hand, for the field samples, the directly analyzed sample often had higher loading density than the recovered sample; and the Freeman-Halton test showed that 25 (of 44) pairs were in disagreement. However, the effect of possible particle agglomeration on the directly analyzed samples cannot be ruled out—and exploration of this factor was beyond the scope of the current study.

Analysis and classification of individual ambient aerosol particles with field-deployable laser-induced breakdown spectroscopy platform

Analysis and classification of individual ambient aerosol particles with field-deployable laser-induced breakdown spectroscopy platform

Lipoprotein subclasses are associated with Hepatic steatosis: insights from the prospective multicenter imaging study for the evaluation of chest pain (PROMISE) clinical trial

ObjectivesTo determine the relationship between lipoprotein particle size/number with hepatic steatosis (HS), given its association with traditional lipoproteins and coronary atherosclerosis. MethodsIndividuals with available CT data and blood samples enrolled in the PROMISE trial were studied. HS was defined based on CT attenuation. Lipoprotein particle size/number were measured by nuclear magnetic resonance spectroscopy. Principal components analysis (PCA) was used for dimensionality reduction. The association of PCA factors and individual lipoprotein particle size/number with HS were assessed in multivariable regression models. Associations were validated in an independent cohort of 59 individuals with histopathology defined HS. ResultsIndividuals with HS (n=410/1,509) vs those without (n=1,099/1,509), were younger (59±8 vs 61±8 years) and less often females (47.6 % vs 55.9 %). All PCA factors were associated with HS: factor 1 (OR:1.36, 95 %CI:1.21–1.53), factor 3 (OR:1.75, 95 %CI:1.53–2.02) and factor 4 (OR:1.49; 95 %CI:1.32–1.68) were weighted heavily with small low density lipoprotein (LDL) and triglyceride-rich (TRL) particles, while factor 2 (OR:0.86, 95 %CI:0.77–0.97) and factor 5 (OR:0.74, 95 %CI:0.65–0.84) were heavily loaded with high density lipoprotein (HDL) and larger LDL particles. These observations were confirmed with the analysis of individual lipoprotein particles in PROMISE. In the validation cohort, association between HS and large TRL (OR: 8.16, 95 %CI:1.82–61.98), and mean sizes of TRL- (OR: 2.82, 95 %CI:1.14–9.29) and HDL (OR:0.35, 95 %CI:0.13–0.72) were confirmed. ConclusionsLarge TRL, mean sizes of TRL-, and HDL were associated with radiographic and histopathologic HS. The use of lipoprotein particle size/number could improve cardiovascular risk assessment in HS.

Development and characterization of a high-performance single-particle aerosol mass spectrometer (HP-SPAMS)

Abstract. This study describes a high-performance single-particle mass spectrometry (HP-SPAMS) design in detail. The comprehensive improvements in the injection system, optical sizing system, mass spectrometry, and data acquisition system have improved particle detection efficiency and chemical analysis. The combination of an aerodynamic particle concentrator (APC) system and a wide range of aerodynamic lenses (ADLs) enables the concentration of particles in the 100–5000 nm range. Using an APC increases the instrument inlet flow by a factor of 3–5. The ion delayed-exaction technology of bipolar time-of-flight mass spectrometry improves the mass resolution by 2–3 times, allowing the differentiation of isobaric ions of different substances. Moreover, the four-channel data acquisition technology greatly enhances the dynamic range of mass spectrometry. The improved HP-SPAMS enhances the overall capability of the instrument in terms of particle detection number and scattering efficiency. Moreover, it improves accuracy and sensitivity for component identification of individual particles. The experimental performance of HP-SPAMS shows that the scattering efficiency of polystyrene latex microspheres is almost 70 %–100 % in the range of 300–3000 nm. Compared to the previous SPAMS, HP-SPAMS has a larger inlet flow rate and scattering efficiency and a higher laser frequency, which makes HP-SPAMS increase the effective number of particles detected and improve the temporal resolution of detection. For the analysis of individual particles, HP-SPAMS achieves an average mass spectral resolution of 2500 at m/z 208, which helps distinguish between most organic fragment ions and metal ions and facilitates the analysis of complex aerosol particles. For the analysis of individual particles, the increased resolution of the HP-SPAMS contributes to the differentiation of most organic fragment ions and metal ions and facilitates the evaluation of complex aerosol particles, in the case of atmospheric lead-containing particles. The improved detection efficiency and chemical analysis capability of HP-SPAMS will be of great importance for low-concentration aerosol detection and complex aerosol component analysis.

Research on Identification and Classification Methods for Soil Microplastics in Hyperspectral Detection

The pollution of microplastics in the environment has attracted worldwide attention, and research and reports on microplastic pollution in soil have gradually increased in recent decades. Currently, microplastic particles can be accurately detected through Raman spectroscopy or Fourier-transform infrared spectroscopy, allowing for individual particle analysis and visual identification of suspicious microplastic particles. However, analyzing a large number of particles using spectroscopic detection techniques is time-consuming, thus there is an urgent need to develop a new detection technology for rapidly and accurately determining and mapping the distribution of microplastics in soil. In this study, hyperspectral imaging technology was employed as a detection method to directly and effectively identify and classify microplastic pollutants in soil. The experimental setup utilized a hyperspectral imaging system with a wavelength range of 400-1000 nm. The experimental results demonstrate that hyperspectral imaging technology is a promising method for detecting microplastics, as it enables direct identification and visualization of microplastic particles on the surface of soil.

Detailed characterisation of precious metals and critical elements in anode slimes from the Olympic Dam copper refinery, South Australia

Together with silver (Ag) and gold (Au), which are almost always recovered, the impurity elements, arsenic (As), antimony (Sb), bismuth (Bi), tin (Sn), lead (Pb), selenium (Se) and tellurium (Te) are major components of anode slimes, a by-product of the electrorefining of impure copper. The Olympic Dam electrorefinery, South Australia, generates raw slimes (∼30 % Cu, 5–10 % Ag, 0.5–1 % Au, 3–4 % Bi, ∼2–3 % Sb, and 5–6 % As), which subsequently undergo decopperisation and then pH-neutralisation. Decopperisation involves treatment with steam and acid at 90 °C, giving a slime that contains ∼ 1 % Cu, 8–17 % Ag, ∼2% Au, ∼7% Bi, ∼4–5 % Sb, and ∼ 3 % As. pH-neutralisation is achieved by addition of NaOH and is the final step prior to cyanidation and precious metal recovery.Bulk chemical compositions, gross morphology and particle size distributions are complemented by high-magnification backscatter imaging and energy-dispersive X-ray analysis of individual particles in raw, decopperised, and pH-neutralised anode slimes. In a first micron-to-nanoscale approach, we use electron backscatter diffraction mapping to assess the crystallinity of individual component phases and a scanning transmission electron microscopy study on micron-sized slices extracted in-situ to confirm the crystal structure of a conspicuous BiAsO4 phase as rooseveltite. The results establish an in-depth understanding of element deportments in slimes and their evolution during sequential stages of treatment. Characterisation studies for Te, Se, Sb, Bi, and As are essential prerequisites for any design of metallurgical circuits for by-product recovery from anode slimes and/or electrolyte. This study aims to demonstrate that complementary cutting-edge microanalytical techniques widely used in mineralogy provide a level of detail essential when considering refinery slimes as a new source of critical commodities.

Multidimensional characterization of particle morphology and mineralogical composition using CT data and R-vine copulas

Computed tomography (CT) can capture volumes large enough to measure a statistically meaningful number of micron-sized particles with a sufficiently good resolution to allow for the analysis of individual particles. However, the development of methods to efficiently investigate such image data and interpretably model the observed particle features is still an active field of research. When image data of particles exhibiting a wide range of shapes and sizes is considered, traditional image segmentation methods, such as the classic watershed algorithm, struggle to recognize particles with satisfying accuracy. Thus, more advanced methods of machine learning must be utilized for image segmentation to improve the validity of subsequent analyses. Moreover, CT data does not include information about the mineralogical composition of particles and, therefore, additional SEM-EDS image data has to be acquired. In this paper, micro-CT image data of a particle system mostly consisting of zinnwaldite–quartz composites is considered. First, an image segmentation method is applied which uses deep convolutional neural networks, in particular an adaptation of the U-net architecture. This has the advantage of requiring less hand-labeling than other machine learning methods, while also being more flexible with the possibility of transfer learning. Then, fully parameterized models based on vine copulas are designed to determine multivariate probability distributions of descriptor vectors for the size, shape, texture and composition of particles—allowing for the estimation and interpretable characterization of interdependencies between particle descriptors. For model fitting, the segmented three-dimensional CT data and co-registered two-dimensional SEM-EDS data are used. The models are applied to predict the mineralogical composition of particles, solely on the basis of particle descriptors observed in CT data.

Cryo-Electron Microscopy for Cancer

A review paper on cryo-electron microscopy (cryo-EM) is essential to assess the recent advancements in this revolutionary imaging technique. As cryo-EM continues to revolutionize structural biology, a comprehensive review can consolidate the knowledge, highlight technical challenges, and offer insights into future developments, promoting better understanding and wider adoption of this cutting-edge technology. The absence of a review paper on the recent innovative approach of applying cryo-electron microscopy for cancer research hinders knowledge dissemination and impedes potential breakthroughs. A comprehensive review would bridge the gap, elucidating the successes and challenges of cryo-EM in cancer studies, fostering collaboration, and inspiring further investigations to combat cancer effectively.” Cryo-electron microscopy enables examining biomolecular structures at almost atomic precision while capturing multiple dynamic states more than 30 years after developing the industry's preferred method for cryo-embedding biological macromolecules under their native conditions. Techniques and equipment have significantly improved. Advanced image-processing methods are employed in research to facilitate the study of biological macromolecular structures and analyze their dynamics; for this, cryo-EM is a potent tool. Cryo-EM must effectively investigate the cellular macromolecular structure, including dynamic analysis using cutting-edge image-processing methods. Modern Analysis of individual particles using electron tomography is even more easily applicable to the procedure. With the development of single particle analysis and electron tomography, it is now more broadly applicable. These techniques have increased the method's applicability even further. Due to its ease of use and capacity to produce intricate and sophisticated data that can be used to comprehend biological structures better, cryo-EM is currently a more well-liked and available research tool. As a result, it serves as a useful tool for both academic and industrial research. Protein complexes, molecular pathways, and viral structures have also been studied using cryo-EM. Due to its adaptability, it has become a useful tool for illness and drug development. Its low cost and simplicity of usage have also made it a crucial research tool.

Enrichment of calcium in sea spray aerosol: insights from bulk measurements and individual particle analysis during the R/V Xuelong cruise in the summertime in Ross Sea, Antarctica

Abstract. Although calcium is known to be enriched in sea spray aerosols (SSAs), the factors that affect its enrichment remain ambiguous. In this study, we examine how environmental factors affect the distribution of water-soluble calcium (Ca2+) distribution in SSAs. We obtained our dataset from observations taken during the R/V Xuelong research cruise in the Ross Sea, Antarctica, from December 2017 to February 2018. Our observations showed that the enrichment of Ca2+ in aerosol samples was enhanced under specific conditions, including lower temperatures (&lt;-3.5 ∘C), lower wind speeds (&lt;7 m s−1), and the presence of sea ice. Our analysis of individual particle mass spectra revealed that a significant portion of calcium in SSAs was likely bound with organic matter (in the form of a single-particle type, OC-Ca, internally mixed organics with calcium). Our findings suggest that current estimations of Ca2+ enrichment based solely on water-soluble Ca2+ may be inaccurate. Our study is the first to observe a single-particle type dominated by calcium in the Antarctic atmosphere. Our findings suggest that future Antarctic atmospheric modeling should take into account the environmental behavior of individual OC-Ca particles. With the ongoing global warming and retreat of sea ice, it is essential to understand the mechanisms of calcium enrichment and the mixing state of individual particles to better comprehend the interactions between aerosols, clouds, and climate during the Antarctic summer.

Fresh organic and soot particles from crop straw burning: Morphology, composition and size distribution

Particulate matter from biomass burning is considered to be one of the major sources of air pollution in China. To examine the characteristics of the particles emitted from the burning of crop straw, an open burning experiment is designed. Individual particles are collected in the flaming and smouldering stages, and analysed by individual particle analyses represented by high‐resolution transmission electron microscopy equipped with the energy‐dispersive X‐ray spectrometer. Five types of particles are identified, namely, pure organic particle, organic particle‐K (OP‐K), tar ball, K‐rich and soot particles. Of these, the OP‐K particles have the highest relative number percentage in all analysed particles in both the flaming and smouldering stages. Interestingly, the microscopic morphology of organic particles is completely different in the flaming and smouldering stages, being near‐spherical in the flaming stage and gel‐like in the smouldering stage. According to the elemental compositions, most of OP‐K particles contained potassium compounds in the form of KCl and K2SO4. High combustion efficiency and temperature promote the formation of crystal structure, resulting in the onion‐like microstructure of soot particles. Apparently, the soot microstructure is a fingerprint feature that helps identify combustion sources. In addition, the particles emitted in the flaming stage are smaller than those in the smouldering stage, implying that high temperature combustion tends to be associated with high combustion efficiency. The relationship between burning temperatures and particle sizes can help to understand the emission of particles from crop straw burning and find new ways to solve the problems caused by straw burning. The results of this study can provide more detailed ‘fingerprint’ characteristics of the particulate matter emitted from biomass‐burning sources, and an understanding of their potential impact on the atmospheric environment.

Real-Time Assessment of the Size Changes of Individual Sub-Visible Protein Particles under Buffer Variations: A Microfluidic Study.

Protein particles in biological drugs can significantly impact drug efficacy and carry the risk of adverse effects. Despite advancements, the understanding and control of particle formation in biopharmaceutical manufacturing remain incomplete. Therefore, further investigation into protein particles is warranted, especially considering that novel formats of biological drugs may be more susceptible to aggregation and particle formation than conventional monoclonal antibodies. In this study, we introduce a microfluidic approach for the real-time analysis of individual sub-visible protein particles during buffer exchange. We find that the modulation of intermolecular forces, achieved by changing the buffer pH or urea concentration, leads to the reversible swelling and shrinkage of particles by up to 50%, which is a consequence of altered intermolecular distances. Additionally, we identify a discrepancy in the biophysical behavior of protein particles compared to monomeric protein. This finding highlights the limited predictive power of commonly applied biophysical characterization methods for particle formation in early formulation development. Moreover, the observed particle swelling may be associated with manufacturing deviations, such as filter clogging. These results highlight the importance of studying individual particles to gain a comprehensive insight into particle behavior and the impact of formulation variations in the biopharmaceutical industry.

Ultraviolet light scattering scanning flow cytometry in the characterization of submicron microparticles.

Ultraviolet lasers are commonly used in flow cytometry to excite fluorochrome molecules with subsequent measurement of the specific fluorescence of individual cells. In this study, the performance of the ultraviolet light scattering (UVLS) in the analysis of individual particles with flow cytometry has been demonstrated for the first time. The main advantage of the UVLS relates to the improvement of the analysis of submicron particles due to the strong dependence of the scattering efficiency on the wavelength of the incident light. In this work, submicron particles were analyzed using a scanning flow cytometer (SFC) that allows measurements of light scattering in an angle-resolved regime. The measured light-scattering profiles of individual particles were utilized in solution of the inverse light-scattering problem to retrieve the particle characteristics using a global optimization. The standard polystyrene microspheres were successfully characterized from the analysis of UVLS which provided the size and refractive index (RI) of individual beads. We believe that the main application of UVLS relates to the analysis of microparticles in a serum, in particular in the analysis of chylomicrons (CMs). We have demonstrated the performance of the UVLS SFC in the analysis of CMs of a donor. The RI versus size scatterplot of CMs was successfully retrieved from the analysis. The current set-up of the SFC has allowed us to characterize individual CMs starting from the size of 160 nm that provides determination of the CM concentration in a serum with flow cytometry. This feature of the UVLS should help with the analysis of lipid metabolism measuring RI and size map evolution after lipase action.

Smart Iterative Analysis Tool for the Size Distribution of Spherical Nanoparticles.

The size of nanoparticles is a critical parameter with regard to their performance. Therefore, precise measurement of the size distribution is often required. While electron microscopy (EM) is a useful tool to image large numbers of particles at once, manual analysis of individual particles in EM images is a time-consuming and labor-intensive task. Therefore, reliable automatic detection methods have long been desired. This paper introduces a novel automatic particle analysis software package based on the circular Hough transform (CHT). Our software package includes novel features to enhance precise particle analysis capabilities. We applied the CHT algorithm in an iterative workflow, which ensures optimal detection over wide radius intervals, to deal with overlapping particles. In addition, smart intensity criteria were implemented to resolve common difficult cases that lead to false particle detection. Implementing these criteria enabled an effective and precise analysis by minimizing detection of false particles. Overall, our approach showed reliable particle analysis results by resolving common types of particle overlaps and deformation with only negligible errors.

Analysis of Size Distribution, Chemical Composition, and Optical Properties of Mineral Dust Particles from Dry Deposition Measurement in Tenerife: Determined by Single-Particle Characterization

In this paper, individual particle analysis by automated scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) was used to assess the size-resolved information of composition, size distribution, complex refractive index, and mixing state of mineral dust aerosol particles collected using different passive and active samplers. In the study, over 120,000 particles from 53 samples were analyzed. Results show that dust particles are the dominating mineral particle type during this campaign, comprising different classes of silicates, Si-rich (quartz-like), Ca-rich (calcite-like), CaMg-rich (dolomite-like), and CaS-rich (gypsum-like). The results also show that there is no significant difference in composition between suspended and deposited dust particles. By using the particle composition, the size-resolved complex refractive index of dust particles was calculated. The real part of the refractive index varied between 1.71 and 1.53 for wavelengths in the range of 370 to 950 nm. The imaginary part of the refractive index, determined mostly by iron oxide, varied between 3.28×10−4 and 7.11×10−5 for wavelengths ranging from 250 nm to 1640 nm. In addition, the refractive index values showed a slight decrease with increasing particle size. We also analyzed the potential for buffering of the acid mobilization of iron by other dust compounds. For particles which contain both iron (Fe) and (unprocessed) calcium (Ca), acids that are able to dissolve insoluble Fe particles can react with the Ca particles before reacting with Fe, but eventually, with longer processing time, the Fe particles could be processed. By analyzing the ratio of sulfate mass to the total aerosol mass of individual particles, the mixing state of sulfate particles to the total dust particles was investigated. The analysis showed that the finer dust particles were associated with higher content of sulfate, while the coarse dust particles correspond to lower sulfate contents, revealing that only fine mode sulfate is more internally mixed with mineral dust aerosol particles.

Analytical performance of single particle aerosol mass spectrometer for accurate sizing and isotopic analysis of individual particles

The commercial Hexin Single particle aerosol mass spectrometer (SPAMS) has been widely used for environmental aerosol monitoring and source apportionment. However, particle size measurement is easily affected by environment pressure fluctuation and sampling orifice clogging. The capability for quantitative analysis is poor, and few isotope measurement has been reported. This paper aims to evaluate the analytical performance of SPAMS and extend its application. First, the flight time of standard particles having different densities and sizes was measured under various conditions (aerodynamic lens upstream pressure and carrier gas). We proposed a universal method for particle size calibration, measurement and correction, taking into account the effects of lens geometry (acceleration nozzle diameter), particle parameters (density, diameter, and shape factor), and operating conditions (lens upstream pressure and carrier gas). Then, isotope measurement was performed when introducing a solution droplet containing a single element. Metal oxide and metal cluster ions were observed in the mass spectrum, indicating incomplete ionization of the sample droplet. The mass discrimination effect was carefully evaluated to correct the measured isotope ratio. Results show that the achievable accuracy of the corrected isotope ratio for elements investigated was 5%. The instrumental performance was relatively poor for elements having great ionization potential or bond energy. Finally, Ag/Eu2O3 suspension and yellow cake/ethanol suspension were analyzed for size, elemental and isotopic analysis. We confirmed that the mass discrimination effect during suspension introduction could be corrected using the mass discrimination correction factor obtained during solution introduction. The Ag, Eu and U in these suspension particles were all found to be at natural abundance. The uranium in the yellow cake was identified as sodium duranyate (Na2U2O7) with volumetric equivalent diameter of approximately 65 nm. The work presented here is beneficial for instrument improvement and wide application.

Deep Learning-Based Segmentation of 3D Volumetric Image and Microstructural Analysis

As a fundamental but difficult topic in computer vision, 3D object segmentation has various applications in medical image analysis, autonomous vehicles, robotics, virtual reality, lithium battery image analysis, etc. In the past, 3D segmentation was performed using hand-made features and design techniques, but these techniques could not generalize to vast amounts of data or reach acceptable accuracy. Deep learning techniques have lately emerged as the preferred method for 3D segmentation jobs as a result of their extraordinary performance in 2D computer vision. Our proposed method used a CNN-based architecture called 3D UNET, which is inspired by the famous 2D UNET that has been used to segment volumetric image data. To see the internal changes of composite materials, for instance, in a lithium battery image, it is necessary to see the flow of different materials and follow the directions analyzing the inside properties. In this paper, a combination of 3D UNET and VGG19 has been used to conduct a multiclass segmentation of publicly available sandstone datasets to analyze their microstructures using image data based on four different objects in the samples of volumetric data. In our image sample, there are a total of 448 2D images, which are then aggregated as one 3D volume to examine the 3D volumetric data. The solution involves the segmentation of each object in the volume data and further analysis of each object to find its average size, area percentage, total area, etc. The open-source image processing package IMAGEJ is used for further analysis of individual particles. In this study, it was demonstrated that convolutional neural networks can be trained to recognize sandstone microstructure traits with an accuracy of 96.78% and an IOU of 91.12%. According to our knowledge, many prior works have applied 3D UNET for segmentation, but very few papers extend it further to show the details of particles in the sample. The proposed solution offers a computational insight for real-time implementation and is discovered to be superior to the current state-of-the-art methods. The result has importance for the creation of an approximately similar model for the microstructural analysis of volumetric data.

Comparison of AMS, TIMS, and SIMS techniques for determining uranium isotope ratios in individual particles.

The determination of isotope ratios in individual uranium particles is very important for nuclear safeguards. In this work, accelerator mass spectrometry (AMS), thermal ionization mass spectrometry (TIMS), and secondary ion mass spectrometry (SIMS) were applied to isotope ratio analysis of individual uranium particles and compared in terms of background, measurement accuracy, and efficiency. Several individual uranium particles (1-7μm) from certified reference materials were used as samples. The results show that the average values of blank counting rate of 235 U for AMS, FT-TIMS (FT: fission track), SEM-TIMS (SEM: scanning electron microscope), and SIMS were 7.3, 7.8, 2.7 and 2.2cps, respectively. The relative error of 234 U/235 U and 234 U/236 U isotope ratios of the particles from U200 for AMS were within 10% and 20%, whereas the results of FT-TIMS and SIMS were within 5% and 10%, respectively. The relative error and external precision of 234 U/238 U and 235 U/238 U of the particles from U850 for the method of AMS, SEM-TIMS, and SIMS were within 10% and 5%, respectively. For 236 U/238 U, the average values of the relative error and external precision measured by AMS were within 5%, which measured by SEM-TIMS and SIMS were all within 10%. AMS has advantages in measuring 236 U/238 U. The measurement time of AMS and SEM-TIMS was shorter than that of FT-TIMS and longer than that of SIMS. It is considered that AMS and SEM-TIMS have a certain development prospect, and it is necessary to research deeply.