Size Distribution Research Articles

Study on Characterization of SrO Aerosols Generated by Optimized Thermal Plasma Torch Aerosol Generator

AbstractPlasma Torch Aerosol Generation System (PTAGS) has been employed to generate nano aerosols with desirable characteristics. The operational parameters of PTAGS installed in the aerosol test facility have been optimized, and aerosols are generated using non-radioactive SrO2 powder. The current-voltage characteristics, electro-thermal efficiency and torch power are studied as a function of the flow rate of the plasma-generating gas (mixture of argon and nitrogen) and the arc current of the plasma torch. The relation of arc characteristics is determined using the Nottingham formulation. Based on this, torch parameters evolved and optimized as 20 kW power, 70% electro-thermal efficiency, 25 L min− 1 flow rate of plasma forming gas, 5 mg min− 1 powder feed rate and for 4–5 min torch operation towards the generation of SrO nano aerosols to achieve 1012 m− 3 and ~ 25 mg m− 3 for the count and mass concentration of aerosol respectively. The initial size distribution of the aerosols is in the few tens of nanometre range (10–40 nm) with a mean diameter of 26 nm (σg = 1.45). Scanning Electron Microscope and Energy dispersive X-ray analysis revealed that the morphology of nano aerosols was nearly spherical and the formation of SrO nanoparticles. A set of PTAGS operational parameters has been standardized to perform further experiments related to reactor safety analysis. PTAGS shall be tuned for aerosol generation in a large facility to achieve the characteristics equivalent to reactor accidental conditions.

Coal Mine Dust Size Distributions, Chemical Compositions, and Source Apportionment

Current regulations mandate the monitoring of respirable coal mine dust (RCMD) mass and crystalline silica in underground coal mines to safeguard miner health. However, other RCMD characteristics, such as particle size and chemical composition, may also influence health outcomes. This study collected RCMD samples from two underground coal mines and performed detailed chemical speciation. Source apportionment was used to estimate RCMD and silica contributions from various sources, including intake air, fire suppression limestone dust, coal dust, diesel engine exhaust, and rock strata. The mine dust mass-based size distributions were comparable to those recorded over a decade ago, with a peak around 10 μm and the majority of the mass in the supermicron size range. The current mine conditions and mining practices do not appear to have significantly increased the generation of smaller particles. Limestone rock dust was prevalent in many locations and, along with coal dust, was the main contributor to RCMD at high-concentration locations. Silica accounted for over 10% of RCMD mass at several active mining locations, primarily from limestone and rock strata dust. Reducing the concentration of limestone dust and its silica content could reduce RCMD and silica levels. Further cleaning of the intake air could also improve the overall mine air quality.

Modeling the Production Process of Lignin Nanoparticles Through Anti-Solvent Precipitation for Properties Prediction

Global warming has recently intensified research interest in renewable polymer chemistry, with significant attention directed towards lignin nanoparticle (LNP) synthesis. Despite progress, LNP industrial application faces challenges: (1) reliance on kraft lignin from declining raw biomass processes, (2) sulfur-rich and condensed lignin use, (3) complex lignin macroparticles to LNP conversion, using harmful and toxic solvents, and, above all, (4) lack of control over the LNP production process (i.e., anti-solvent precipitation parameters), resulting in excessive variability in properties. In this work, eco-friendly LNPs with tailored properties were produced from a semi-industrial organosolv process by studying anti-solvent precipitation variables. Using first a parametric and then a Fractional Factorial Design, predictions of LNP sizes and size distribution, as well as zeta-potential, were derived from a model over beech by-products organosolv lignin, depending on initial lignin concentration (x1, g/L), solvent flow rate (x2, mL/min), antisolvent composition (x3, H2O/EtOH v/v), antisolvent ratio (x4, solvent/antisolvent v/v), and antisolvent stirring speed (x5, rpm). This novel chemical engineering approach holds promise for overcoming the challenges inherent in industrial lignin nanoparticle production, thereby accelerating the valorization of lignin biopolymers for high value-added applications such as cosmetics (sunscreen or emulsion) and medicine (encapsulation, nanocarriers), a process currently constrained by significant limitations.

Stationarity of the Special Relationship Between the Geographical Distribution of Body Size and Day Length in Japanese Adolescents: Spatial and Temporal Analysis Using a GTWR Model.

Northern Japanese children tend to have larger physiques; however, the underlying cause remains unknown. Previous geographical correlation analyses revealed an unusual trend; effective day length was negatively correlated with height and positively correlated with weight (adjusted for height). This paradoxical relationship suggests a thyroid hormone-like effect and possible photoperiodic response. This study aimed to determine whether this phenomenon remains consistent over time and across different regions of Japan. We used geographically and temporally weighted regression (GTWR) to examine whether the relationship between height and effective day length, which differs from the relationship between weight and effective day length, varies by location and time. GTWR models each observation point separately, allowing for spatial and temporal variations. The analysis included the average height and weight data of children and adolescents by prefecture from 1989 to 2019, along with effective day length considering illuminance above 5000 lx derived from the agrometeorological grid square data. Height was used as the dependent variable, whereas weight and effective day length were used as independent variables. For height estimation, the coefficients of weight and effective day length were consistently positive and negative, respectively, although the regression coefficients showed minor geographical and temporal variations. The opposite correlation between height and effective day length and that between weight and effective day length were consistent. This suggests that the phenomenon is more likely driven by environmental factors than by economic or genetic influences.

Impact of fluvial meander-belt sedimentary heterogeneity on the efficiency of low-enthalpy geothermal doublets: heat-transport simulations of forward stratigraphic models

In the present study, different geocellular models of meander-belt stratigraphic architectures were produced that are representative of the sedimentary products of sand-bed meandering rivers and their petrophysical heterogeneity. The static models were created combining a rule-based stratigraphic modelling approach with geostatistical modelling, and were applied in groundwater-flow and heat-transport simulations using MODFLOW-2005 and MT3D-USGS. Overall, histories of injected cold-water plume propagation were examined considering (i) three architectural frameworks as representative of different river morphodynamics, (ii) four scenarios of facies architecture, and (iii) alternative well layouts. The presence, size and spatial distribution of sedimentary heterogeneities related to river hydrodynamics, channel-form abandonment, or to modes of meander-transformation are seen to control the shape of the thermal plume, thereby affecting well-doublet performance. The considered scenarios of facies make-up for point-bar deposits have a modest influence on temperature decline near the abstraction well. The presence of sandstone beds in the lower heterolithic parts of abandoned-channel fill does not facilitate significant thermal-plume expansion beyond mud-plug. The effect of basal lags made of open-framework conglomerates on heat advection depends on their geometry, but is effectively negligible when it makes up less than 1% of deposits. Relatively thin mud drapes lying on point-bar accretion surfaces are seen to act as baffles to flow, but their impact is minimal in view of their small number. The study provides useful and novel insight on the potential impact of sedimentary heterogeneity in fluvial reservoirs, which can be applied to the design of well doublets, and highlights areas deserving further investigations.

Particle Size Inversion Based on L1,∞-Constrained Regularization Model in Dynamic Light Scattering

Dynamic light scattering (DLS) is a highly efficient approach for extracting particle size distributions (PSDs) from autocorrelation functions (ACFs) to measure nanoparticle particles. However, it is a technical challenge to get an exact inversion of the PSD in DLS. Generally, Tikhonov regularization is widely used to address this issue; it uses the L2 norm for both the data fitting term (DFT) and the regularization constraint term. However, the L2 norm’s DFT has poor robustness, and its regularization term lacks sparsity, making the solution susceptible to noise and a reduction in accuracy. To solve this problem, the Lp,q norm restrictive model is formulated to examine the impact of various norms in the DFT and regularization term on the inversion results. On this basis, combined with the robustness of DFT and the sparsity of regularization terms, an L1,∞-constrained Tikhonov regularization model was constructed. This model improves the inversion accuracy of PSD and offers a better noise-resistance performance. Simulation tests reveal that the L1,∞ model has strong noise resistance, exceptional inversion precision, and excellent bimodal resolution. The inversion outcomes for the 33 nm unimodal particles, the 55 nm unimodal, and the 33 nm/203 nm bimodal experimental particles show that L1,∞ reduces peak errors by at most 6.06%, 5.46%, and 12.12%/3.94% compared to L2,2, L1,2, and L2,∞ models, respectively. These simulations are validated by experimental data.

Comminution Energy Based on Particle Size Distribution and Crushing Mechanism During Coal and Gas Outburst

Comminution Energy Based on Particle Size Distribution and Crushing Mechanism During Coal and Gas Outburst

The role of refractive indices in measuring mineral dust with high-spectral-resolution infrared satellite sounders: application to the Gobi Desert

Abstract. Mineral dust significantly influences the Earth's climate system by affecting the radiative balance through the emission, absorption and scattering of solar and terrestrial radiation. Estimating the dust radiative effect remains challenging due to the lack of detailed information on the physical and chemical properties of dust. High-spectral-resolution instruments in the infrared (IR) spectrum, such as the Infrared Atmospheric Sounding Instrument (IASI), have demonstrated the ability to quantify these aerosol properties. A crucial parameter for characterizing mineral dust from space is the complex refractive index (CRI), as it links the dust's physical and chemical properties to its optical properties. This paper examines the impact of six prior laboratory CRI datasets to improve the characterization of dust microphysical properties using IASI. The CRIs include older measurements obtained through the classical pellet method, commonly employed in mineral dust applications, as well as newer datasets that incorporate the latest advancements in laboratory measurement techniques for aerosol generation. These datasets are tested on IASI measurements during a dust storm event over the Gobi Desert in May 2017. We evaluate the sensitivity of IASI to different CRI datasets using the Atmospheric Radiation Algorithm for High-Spectral Resolution Measurements from Infrared Spectrometer (ARAHMIS) radiative transfer algorithm and explore the datasets' impact on retrieving size distribution parameters by mapping their spatial distributions. The results indicate that the laboratory CRI datasets decrease the total error in the covariance matrix by 30 %. In addition, we assess the ability to accurately reconstruct IASI detections and the extent to which we can retrieve the microphysical properties of dust particles. The choice of CRI significantly impacts the accuracy of dust detection and characterization from satellite observations. Notably, datasets that incorporate recent aerosol generation techniques with higher spectral resolution and samples from the case study region show improved compatibility with IASI observations. The outcomes of this research emphasize two key points: the crucial link between chemical composition of dust and its optical properties and the importance of considering the specific composition of the CRI dataset for improved retrieval of the microphysical parameters. Furthermore, this study highlights the critical role of ongoing enhancements in CRI measurement approaches, as well as the potential of high-spectral-resolution infrared sounders for aerosol atmospheric investigation and for understanding the radiative impacts of sounders.

AAV1.tMCK.NT-3 gene therapy improves phenotype in Sh3tc2-/- mouse model of Charcot-Marie-Tooth type 4C

Abstract Charcot-Marie-Tooth type 4C (CMT4C) is associated with mutations in the SH3 domain and tetratricopeptide repeats 2 (SH3TC2) gene, primarily expressed in Schwann cells (SCs). Neurotrophin-3 (NT-3) is an important autocrine factor for SC survival and differentiation, and it stimulates neurite outgrowth and myelination. In this study, scAAV1.tMCK.NT-3 was delivered intramuscularly to four-week-old Sh3tc2−/− mice, a model for CMT4C, and treatment efficacy was assessed at six months post-gene delivery. Efficient transgene production was verified with the detection of NT-3 in serum from the treated cohort. NT-3 gene therapy improved functional and electrophysiological outcomes including rotarod, grip strength, and nerve conduction velocity. Qualitative and quantitative histopathological studies showed that hypomyelination of peripheral nerves and denervated status of neuromuscular junctions at lumbrical muscles were also improved in the NT-3 treated mice. Morphometric analysis in mid sciatic and tibial nerves showed treatment-induced distally prominent regenerative activity in the nerve, and an increase in the estimated SCs density. This indicates that SC proliferation and differentiation, including the promyelination stage, are normal in the Sh3tc2-/- mice, consistent with the previous findings that Sh3tc2 is not involved in early stages of myelination. Moreover, in size distribution histograms the number of myelinated axons within the 3-6 µm diameter range increased, suggesting that treatment resulted in continuous radial growth of regenerating axons over time. In conclusion, this study demonstrates the efficacy of AAV1.NT-3 gene therapy in the Sh3tc2−/− mouse model of CMT4C, the most common recessively inherited demyelinating CMT subtype.

Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions

Abstract A comprehensive understanding of snowfall microphysics is crucial for enhancing the accuracy of remote sensing snowfall retrievals. However, variations in regional and seasonal snow particle size distributions (PSDs) contribute substantial uncertainty. Here, we examine snowfall PSDs from across the Northern Hemisphere, applying Principal Component Analysis (PCA) to disdrometer observations with the aim of identifying dominant modes of variability across varying regional climates. The PCA revealed three Empirical Orthogonal Functions (EOFs) that account for a combined 95% of the variability across the dataset, which are attributed to latent linear embeddings of snowfall intensity (EOF1), snowfall character (EOF2) and snowfall regime (EOF3). Examining point clusters with the highest combined EOF values reveals six distinct modes of variability (i.e., Principal Component [PC] groups) with unique PSD traits. These groups are then correlated with environmental factors using data from collocated vertically pointing radar, surface meteorology, and reanalysis to assist in assigning physical attributes. The first and second PC groups, linked to EOF1’s intensity embedding, are described by their PSD intercepts, snowfall rates, and reflectivity and Doppler velocity values, representing low and high intensity snowfall modes, respectively. The third and fourth PC groups, associated with EOF2’s character embedding, are defined by temperature, fall speed, and density, indicative of cold, fluffy snowfall and warm, dense snowfall, respectively. The fifth and sixth PC groups, related to EOF3’s regime embedding, are distinguished by their PSD slope, snowfall rate, and reflectivity profiles, signifying shallow, weak convective systems with small particles, and deep, stratiform snowfall events with large aggregates, respectively.

Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data

Abstract. Arctic sea ice cover evolves seasonally from large plates separated by long, linear leads in the winter to a mosaic of smaller sea ice floes in the summer. The interplay between physical and thermodynamic mechanisms during this process ultimately creates the observed sea ice floe size distribution (FSD), which is an important metric for characterizing the sea ice cover and assessing model performance. Historically, the FSD has been studied at fixed locations over short periods, leaving a gap in our understanding of the spatial and temporal evolution of the FSD at large scales. Here, we present an automated framework for image segmentation, allowing the identification and labeling of individual ice floes in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Using this algorithm, we automatically process and segment 4861 images, identifying more than 9.4 million floes over 23 years. The extracted characteristics of the floes – including area, perimeter, and orientation – evolve throughout the spring and summer in the Beaufort Sea. We find seasonal patterns of decreasing mean floe areas, increasing FSD power law slopes, and increasing variability in the floe orientation as the summer progresses.

How ultrasonication treatment drives the interplay between lysinoalanine inhibition and conformational performances: A case study on alkali-extracted rice residue protein isolate.

Lysinoalanine (LAL) formed during alkaline extraction of rice residue protein (RRPI), which limited its application in the food industry. In this study, the influence of ultrasonication parameters (acoustic power density, ultrasound duration, and ultrasound temperature) on the inhibition of LAL formation and conformational attributes of RRPI during alkaline extraction was elucidated. The results suggested that the acoustic power density substantially modified the chemical interaction forces between RRPI molecules. At a power density of 60W/L, the ionic bonds (14.37%) and hydrophobic interactions (49.28%) reached the maximum, while hydrogen bonds (15.29%) and disulfide bonds (21.06%) reached the minimum. Moreover, acoustic power density at 60W/L caused a decrease of 18.02% and 12.2% in α-helix, and β-turn, respectively, shifting toward β-sheet, random coil, with an increase of 7.31% and 36.16%. Following ultrasonication, the protein particle size distribution curve shifted in the direction of smaller particle size, forming a relatively concentrated and uniform protein distribution. Sonication power, temperature, and time decreased the absolute value of Zeta potential. Furthermore, significant destruction in microstructure was elicited by sonication, which made the structure looser and more microparticles. Pearson correlation analysis suggested that the inhibition in the levels of LAL was most influenced by the increase of sulfhydryl groups and Zeta potential, as well as the reduction of α-helix content, in which the alteration of the total sulfhydryl group content had a great impact on the Zeta potential and the free sulfhydryl group. The principal component analysis demonstrated a notable correlation between the total sulfhydryl group and both the Zeta potential and free sulfhydryl group of RRPI.

The Formation of Porous Silicon Using Vertical Photoelectrochemical Method with Laser Energy Variation

Due to its notable characteristics, porous silicon (PSi) has become the main focus in silicon upgrades for optoelectronics, medical, and sensor applications. Here, successful vertical photoelectrochemical fabrication of PSi based on crystalline silicon n-type wafers with orientation (100) has been accomplished. Silicon surfaces were anodized for 10 min in a solution of hydrofluoric acid and ethanol at a ratio of 1:3 and a current density of 4 mA/cm2 under laser illumination. Illumination sources were red, green, and purple laser beams with energies of 1.91 eV, 2.33 eV, and 3.06 eV, respectively, conducted to observe the effects on PSi microstructures and optical properties. The pores formed on the silicon surface were characterized via SEM, XRD, FTIR, and UV-Vis DRS Spectrophotometer. SEM analysis showed pore size distributions of 2.130, 3.353, and 1.078 mm for PSi samples with red, green, and purple lasers, respectively. XRD investigation revealed diffraction angles of 33.14° and 69.47° belonging to (211) and (422) planes, respectively, corresponding to the PSi. For samples of silicon and PSi with red, green, and purple lasers, the crystallite size and crystallinity were 168.55 nm and 44.80%, 25.02 nm and 17.12%, 29.19 nm and 23.56%, and 145.05 nm and 35.17%, respectively. FTIR observation confirmed that the PSi surface contained chemical bonds of Si-Si, Si-H, Si-H2, Si-O-Si, and C=O. UV-Vis DRS examination revealed the reflectance spectrum oscillation, indicating that lasers caused pore formation in PSi with bandgap energies of between 1 and 2 eV.

Numerical simulation for spray spatial distribution of swirl nozzle and its target dustfall area prediction.

The droplet breakup and distribution of the internal flow field and external spray field of a nozzle were obtained under different pressures. The thickness of the liquid film increased with pressure as a quadratic function. The maximum value of 0.281mm at 2MPa decreased to 0.172mm at 10MPa, equivalent to 38.8% decrease. The MATLAB was used to obtain the particle size distribution characteristics of the droplets under different pressures. At 2MPa, droplet breakup dominated the axial interval [0-700mm]. With the increase of pressure, D50 distribution as a whole continues to decrease, 2-6MPa change, the particle size reduction is larger, every increase of 2MPa reduced by about 15%. 6-10MPa change, the particle size reduction is smaller, every increase of 2MPa reduced by about 8%. A model to predict the optimal dust reduction areas under varying pressures was developed. The prediction results indicate that at pressures of 5MPa and 9MPa, the target dust removal areas were [344mm, 710mm] and [424mm, 942mm] along the axial direction, respectively.

Sediment load with metallurgical slag admixture under diverse morphological conditions along submerging karst stream

This study investigates the clastic fluvial sediments of the Jedovnický submerging stream in the section between the Jedovnice village and Křtinský stream (Moravian Karst, Czechia). A total of 28 samples were collected to analyze clast composition, slag content, grain size, and roundness. The sediment primarily consists of allochthonous Lower Carboniferous material (greywackes, clayey shales) with varying amounts of metallurgical slag, occasionally mixed with autochthonous deposits such as rockfall accumulations and tailings from the excavation of connecting adits. The slag content fluctuates, peaking downstream of the erosive section of the Rudické propadání cave, near the Stará řeka passage connection. Grain size distribution is influenced by both surface and cave morphology, as well as hydraulic conditions. The alternation between erosive and depositional zones, along with the unique karstic and speleorelief features, plays a crucial role in clast mobilization. These features include ponors, erosive and paragenetic corridors, sumps, and rockfalls. Fine particle accumulations are particularly noticeable in front of sumps or dams. Throughout the studied section, the proportion of coarse particles (>10 mm and 5–10 mm) gradually decreases, while finer particle content increases toward the resurgence. The roundness of Carboniferous sediments remains relatively constant, although it is significantly influenced by the presence of well-rounded, weak and ductile slag clasts. Overall, both the slag content and the proportion of well-rounded and rounded clasts in the coarser fractions (>10 mm and 5–10 mm) show a decreasing trend toward the resurgence.

Use of lignocellulose-degrading enzyme bio-cemented soils in the construction industry

In their activity, termites break down biomass into glucose, forming cementitious compounds. This results in rainfall-resistant mounds for their shelters, which interests the construction industry. This study explored the potential application of the abundant naturally bio-cemented termite mound soils in highway construction. Experimental investigations compared these mound soils to surrounding soils, revealing that mound soils are 68.2% finer in particle size distribution and have 81.4% lower organic content. Atterberg limits indicated 14.6% higher plasticity and a 5.3% increase in specific gravity for mound soils. Atomic Absorption Spectroscopy (AAS) showed no significant difference in chemical composition. Proctor tests indicated that the compaction characteristics of the soils were comparable, confirming their engineering viability without modifications. Mound soils exhibited a twofold increase in Unconfined Compressive Strength (UCS) and a 33.9% increment in California Bearing Ratio (CBR) strength. One-way ANOVA tests confirmed these differences with p-value ranges of 0.0056-0.0361 below the 0.05 significance threshold. The study advocates utilising eco-friendly naturally bio-cemented mound soils in highway construction, meeting minimum standards. Mound soils from one acre can construct up to 2,500m highway, optimising resource use, promoting sustainability by repurposing natural materials, and significantly reducing carbon emissions. Further research on soil improvement using lignocellulose-degrading enzymes is recommended.

Paclitaxel loaded Capmul MCM and tristearin based nanostructured lipid carriers (NLCs) for glioblastoma treatment: screening of formulation components by quality by design (QbD) approach.

Paclitaxel (PTX), a naturally occurring diterpenoid isolated from Taxus brevifolia, is a first-line drug for the treatment of glioblastoma; however, it suffers from the disadvantages of poor water solubility and nonspecific biodistribution, which cause serious side effects in the human body. The marketed formulation suffers from serious side effects, such as allergic reactions, neutropenia, and neuropathy, which require safe and effective formulations of PTX. In the present study, PTX was entrapped in a solid-liquid lipid mixture with the aid of a surfactant using a modified solvent evaporation technique. Higher entrapment of the impressive stability of the formulation was achieved by employing quality design-based strategies. Optimized levels by employing a numerical optimization technique for each factor, that is, surfactant concentration (X1), lipid concentration (X2), and amount of organic solvent (X3) were 0.3%, 0.76% & 8.3 ml respectively. The resultant formulation exhibited a particle size of 121.44 nm, entrapment efficiency of 94.27%, and zeta potential of -20.21 mV with unimodal size distribution. A reduction in the % crystalline index from 48 to 3.4% ensured the amorphous form of the entrapped drug inside the formulation, which precludes the fear of leakage and instability of the formulation. Cell line studies conducted on U87MG Cell lines also suggested that the NLC of paclitaxel are more effective than those of pure PTX. In summary, PTXNLC seem to be a superior alternative carrier system for the formulation industry to obtain higher entrapment with excellent stability.

A Study of the Potential of Solidago virgaurea Extract as a Raw Material for Cosmetic Macroemulsions

The use of Solidago virgaurea extract as a raw material for cosmetics production fits the eco-tendency prevalent in the cosmetic industry for many years now perfectly. The study reported in this paper included an evaluation of the potential of the above-mentioned plant extract as a natural cosmetic ingredient applied in the form of cosmetic macroemulsions. The physicochemical parameters (pH, viscosity, particle size distribution) and physical stability (multiple light scattering) of the cosmetic formulations containing Solidago virgaurea (1.0 wt.%) were studied. An in vivo study was carried out on a group of 20 female volunteers. The results showed a high compatibility of the tested extract with the other components in the macroemulsion in the form of a serum for the body, which was the formulation containing Sorbitan Stearate as an emulsifier. Analysis of the results revealed a relation between the compatibility of the investigated herbal extract with the components of the cosmetic base and the effectiveness of this extract as an active substance. As a result of an improvement in the application parameters, an over 70% increase in the level of epidermis moisturization was observed along with other beneficial changes in the parameters of skin macrorelief and topography.

Deep Learning-Based In Situ Micrograph Synthesis and Augmentation for Crystallization Process Image Analysis

Deep learning-based in situ imaging and analysis for crystallization process are essential for optimizing product qualities, reducing experimental costs through real-time monitoring, and controlling the process. However, large and high-quality annotated datasets are required to train accurate models, which are time consuming. Therefore, we proposed a novel methodology that applied image synthesis neural networks to generate virtual information-rich images, enabling efficient and rapid dataset expansion while simultaneously reducing annotation costs. Experiments were conducted on the L-alanine crystallization process to obtain process images and to validate the proposed workflow. The proposed method, aided by interpolation augmentation and data warping augmentation to enhance data richness, utilized only 25% of the training annotations, consistently segmenting crystallization process images comparable to those models utilizing 100% of the training data annotations, achieving an average precision of nearly 98%. Additionally, based on the analysis of Kullback–Leibler divergence, the proposed method demonstrated excellent performance in extracting in situ information regarding aspect ratios and crystal size distributions during the crystallization process. Moreover, its ability to leverage expert labels with a four-fold enhanced efficiency holds great potential for advancing various applications in crystallization processes.

Microplastic pollution unveiled: the consequences of small unregulated dumping in villages, spanning from soil to water.

Microplastic contamination in soil ecosystems is a major environmental concern in the world. The current study aims to explore the extent of microplastic pollution in unregulated village dumpsites in India, focusing on the movement of these pollutants from soil to aquatic environments. Soil samples from eight distinct sites (A to H) in six villages were analyzed for various properties, including pH, bulk density, porosity, water retention capacity, hydraulic conductivity, and particle size distribution. The attenuated total reflection-Fourier-transform infrared spectroscopy (ATR-FTIR) method was used to identify prevalent plastic types. The research classifies microplastics by their shape and color, identifying a wide range of particles such as sheets, fibers, foams, fragments, and films. The study also examines the presence and concentration of microplastics in both soil and sediment samples. It was found that PE and PP microplastics are significantly present across different size fractions. Sample A contains a variety of items in the 1-5mm size range, mainly PE, while the 0.3-1mm fraction is largely PP. Samples B to H are mostly composed of PE microplastics in different forms. Sample F is unique with a mix of PE, EPS, and a higher amount of red and blue foam particles in the 0.3-1mm fraction. Microplastics were quantified using stereomicroscopy, revealing concentrations between 80 and 840 numbers per kilogram in soil and 20 to 60 numbers per kilogram in sediments. The findings emphasize the widespread nature of microplastic pollution across ecosystems and the importance of developing effective strategies for monitoring and mitigating their impact on environmental health and human well-being.