An image segmentation method of pulverized coal for particle size analysis

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

<i>In-Silico</i>Validation and Development of Chlorogenic Acid (CGA) Loaded Polymeric Nanoparticle for Targeting Neurodegenerative Disorders

Background: Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. Objective: The current study is aimed at the in-silico validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. Methods: A successful in-silico validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis. Results & Conclusion: The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of −17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.

Electrochemical performance of a nickel-rich LiNi0.6Co0.2Mn0.2O2 cathode material for lithium-ion batteries under different cut-off voltages

A spherical-like Ni0.6Co0.2Mn0.2(OH)2precursor was tuned homogeneously to synthesize LiNi0.6Co0.2Mn0.2O2as a cathode material for lithium-ion batteries. The effects of calcination temperature on the crystal structure, morphology, and the electrochemical performance of the as-prepared LiNi0.6Co0.2Mn0.2O2were investigated in detail. The as-prepared material was characterized by X-ray diffraction, scanning electron microscopy, laser particle size analysis, charge–discharge tests, and cyclic voltammetry measurements. The results show that the spherical-like LiNi0.6Co0.2Mn0.2O2material obtained by calcination at 900°C displayed the most significant layered structure among samples calcined at various temperatures, with a particle size of approximately 10 μm. It delivered an initial discharge capacity of 189.2 mAh•g−1at 0.2C with a capacity retention of 94.0% after 100 cycles between 2.7 and 4.3 V. The as-prepared cathode material also exhibited good rate performance, with a discharge capacity of 119.6 mAh•g−1at 5C. Furthermore, within the cut-off voltage ranges from 2.7 to 4.3, 4.4, and 4.5 V, the initial discharge capacities of the calcined samples were 170.7, 180.9, and 192.8 mAh•g−1, respectively, at a rate of 1C. The corresponding retentions were 86.8%, 80.3%, and 74.4% after 200 cycles, respectively. © 2017, University of Science and Technology Beijing and Springer-Verlag Berlin Heidelberg.

Determining particle size distribution and refractive index in a two-layer tissue phantom by linearly polarized light

We report a new method for measuring particle size distribution （PSD） and refractive index of the top layer ill a two-layer tissue phantom simulated epithelium tissue by varying the azimuth angle of incident linearly polarized light. The polarization gating technique is used to decouple the single and multiple scattering components in the returned signal. The theoretical model based on Mie theory is presented and a nonlinear inversion method -floating genetic algorithm - is applied to inverting the azimuth dependence of component of polarization light baekscattered. The experiment results demonstrate that the size distribution and refractive index of the scatters of the top layer can be determined by measuring and analyzing the differential signal of the parallel and perpendicular components from a two-layer tissue phantom. The method implies to detect precancerous changes in human epithelial tissue.

Application of multi-phase particle swarm optimization technique to retrieve the particle size distribution

The multi-phase particle swarm optimization （MPPSO） technique is applied to retrieve the particle size distribution （PSD） under dependent model. Based on the Mie theory and the Lambert-Beer theory, three PSDs, i.e., the Rosin-Rammer （R-R） distribution, the normal distribution, and the logarithmic normal distribution, are estimated by MPPSO algorithm. The results confirm the potential of the proposed approach and show its effectiveness. It may provide a new technique to improve the accuracy and reliability of the PSD inverse calculation.

A NEW ALGORITHM OF RELAXATION METHOD FOR PARTICLE ANALYSIS FROM FORWARD SCATTERED LIGHT

A new algorithm of the relaxation method is developed for the inversion of forward scattered light to obtain the size distribution of spherical particles. Numerical tests are performed for a laser particle analyzer using the Mie theory and the diffraction approximation. The algorithm efficiency, in the presence of experimental noises, is studied. The results show that the technique is fast in convergence, stable against random noise and insensitive to the distribution of particles and the initial trial distribution.

Retrieval of spherical particle size distribution using ant colony optimization algorithm

The ant colony optimization （ACO） algorithm based on the probability density function is applied for the retrieval of spherical particle size distribution （PSD）. The spectral extinction data based on the Mie theory and the Lambert-Beer Law served as input for estimating five commonly use monomodal PSDs, i.e., Rosin- Rammer distribution, normal distribution, logarithmic normal distribution, modified beta distribution, and Johnson＇s SB distribution. The retrieval results show that the ACO algorithm has high feasibility and reliability, thus providing a new method for the retrieval of PSD.

Fischer–Tropsch synthesis on impregnated cobalt-based catalysts:New insights into the effect of impregnation solutions and pH value

The Co-based catalysts were prepared with different cobalt acetate solutions. Effects of pH value were studied deeply on Fischer–Tropsch synthesis (FTS) through a semi-batch reactor. Among all impregnation solutions (water, butanol, amyl alcohol, acetic acid, nitric acid and ammonium nitrate), the catalyst prepared by NH4NO3solution showed the highest catalytic activity due to its small particle size and high reduction degree. However, the catalyst with the smallest particle size derived from water as impregnation solution exhibited low activity as well as high methane selectivity since it was difficult to be reduced and inactive in FTS. According to FT-IR spectra results, the low intensity of absorbed CO on the catalyst prepared from water solution resulted in low FTS activity. Whereas, the high activity of catalysts prepared from NH4NO3solution could be explained by the high intensity of absorbed CO on the catalysts. The cobalt species on the catalysts prepared under lower pH conditions exhibited smaller particle size distribution as well as lower CO conversion than those prepared at higher pH value. © 2016 Science Press

Solvent-free synthesis of alumina supported cobalt catalysts for Fischer–Tropsch synthesis

A novel mechano-synthesis method has been elaborated in this work for the design of efficient cobalt-based Fischer–Tropsch catalysts. The process aims to reduce the total number of steps involved in the synthesis of solid catalysts and thus to avoid relevant toxic solutions generated during the catalyst preparation. The mechano-synthesis of the Co/Al2O3catalyst was processed in a low-energy vibratory micro mill and high energy planetary ball mill. Porous spherical γ-aluminas (1860 µm and 71 µm mean particle diameter) were used in this work as host compounds. Co3O4(3 µm mean particle diameter) has provided guest particles for mechano-synthesis. The catalysts were characterized by textural (surface area, porosity and particle size) and structural analyses (X-ray diffraction, TPR, SEM-EDX and microprobe). The microprobe images show deposition of Co3O4on the surface of the alumina and indicated no Co3O4diffusion inside the alumina pores. SEM-EDX mapping illustrated that cobalt coating tended to occur on surface of rounded shape of cracked alumina fragments. After milling, the crystallite size of Co3O4decreased to 15 nm from 30 to 50 nm. The TPR profiles indicated very low concentrations of inactive cobalt aluminate mixed compounds which are usually produced during the catalyst preparation by impregnation. In Fischer–Tropsch synthesis, the catalysts prepared using mechano-synthesis methods showed catalytic performance comparable to the catalysts prepared by impregnation. © 2016 Science Press

Study on the System for Separating Sulfurfrom Flue Gas and Dust

This paper describes the structure of the system for separating sulfur from flue gas and dust. In the paper, the velocities of turbulent flow and laminar flow inside the tower, the total of liquid membrance, and the additional flow of rotation fogged fluid are calculated, and the separation of rotation air-solid affected by tower is analyzed. The velocity distribution in quasi free vortex area is obtained from experiment. The minimum separated particle diameter is computed. The paper also studies the chemical reactions of flue gas containing sulfide with the dynamic fogged sulfur separating agent and discusses the main factors related to the effect of separating sulfur and dust. At last, the applications of separating sulfur in industrial stove and collecting dust in environmental engineering are introduced.

Synthesis and Characterization of <i>Citrus limonum</i>Essential Oil Based Nanoemulsion and Its Enhanced Antioxidant Activity with Stability for Transdermal Application

Lemon oil (LO), also known as Citrus limonum is a highly volatile essential oil (EO) with potential therapeutic properties like anti-oxidative, anti-proliferative, anti-fungal and anti-cancerous. However, the efficacy of LO is limited due to its physiological factors such as high volatility, poor stability (particularly sensitive to sunlight) and quick degradability upon exposure. To overcome these challenges, we formulated lemon oil loaded nanoemulsion system (LO-NE) (oil-in-water), using aqueous titration method. The formulation comprised of lemon oil (LO), Tween 80 and ethanol as oil, surfactant and co-surfactant phases respectively. The existence zone of NE was established by constructing pseudo-ternary phase diagrams using different concentrations of LO, surfactant and co-surfactant (Smix). The quantitative estimation of LO was performed using a high throughput gas chromatography, revealing the presence of various compounds like Limonene, Alpha-Pinene and Linalyl acetate followed by the estimation of total phenolics and flavonoid content. The characterization of LO-NE indicated the particle size of 60 ± 2.5 nm along with the polydispersity index of 0.125 and zeta potential of −14.9 mV. The size range of the NE particles dispersed in the colloidal system was further verified by TEM micrograph which shows size range between 46.2 - 104.7 nm. All the anti-oxidant assays outcomes exhibited the higher activity of LO-NE in comparison to LO alone with lower IC50 values. The release kinetics statistical data showed that LO-NE had a sustained release and followed the Higuchi’s model in comparison to burst release of LO alone. Lastly, the stability analysis of the optimised formulation (LO-NE) and LO was estimated through antioxidant assay and subjecting them for thermodynamic stability after 6 months. The results attained, showed higher stability and anti-oxidant capability of LO-NE than LO alone. The study suggested that formulated nanoemulsion can be effectively used as a highly efficacious biologically active alternative nanoformulation against many transdermal disorders.

On-line full scan inspection of particle size and shape using digital image processing

An on-line full scan inspection system is developed for particle size analysis. A particle image is first obtained through optical line scan technology and is then analyzed using digital image processing. The system is composed of a particle separation module, an image acquisition module, an image processing module, and an electric control module. Experiments are carried out using non-uniform 0.1 mm particles. The main advantage of this system consists of a full analysis of particles without any overlap or miss, thus improving the Area Scan Charge Coupled Device （CCD） acquisition problems. Particle size distribution, roundness, and sphericity can be obtained using the system with a deviation of repeated precision of around ±1%. The developed system is shown to be also convenient and versatile for any particle size and shape for academic and industrial users.

Optimization of regularization parameter of inversion in particle sizing using light extinction method

In particle sizing by light extinction method, the regularization parameter plays an important role in applying regularization to find the solution to ill-posed inverse problems. We combine the generalized cross-validation （GCV） and L-curve criteria with the Twomey-NNLS algorithm in parameter optimization. Numerical simulation and experimental validation show that the resistance of the newly developed algorithms to measurement errors can be improved leading to stable inversion results for unimodal particle size distribution.

New algorithm and system for measuring size distribution of blood cells

In optical scattering particle sizing, a numerical transform is sought so that a particle size distribution can be determined from angular measurements of near forward scattering, which has been adopted in the measurement of blood cells. In this paper a new method of counting and classification of blood cell, laser light scattering method from stationary suspensions, is presented. The genetic algorithm combined with nonnegative least squared algorithm is employed to inverse the size distribution of blood cells. Numerical tests show that these techniques can be successfully applied to measuring size distribution of blood cell with high stability.

IN-LINE PARTICLE SIZING FOR PROCESS CONTROL IN NEW DIMENSIONS

The combination of laser diffraction with upstream sampling realized a break-through for the in- and on-line particles size analysis in industrial applications. Today, the combination of representative sampling, dry dispersion, particle size analysis by laser diffraction and integrated feedback of the sample is well accepted in many industrial applications. No more interactions of the user are required, and for standard applications the on-line monitoring of particle sizes became nearly as simple as the monitoring of any other process parameter. The increase of inspection interval from 24-hour operation to months has increased user confidence in this technology, and industries with more demanding measurement requirements are seeking to benefit from this performance. This challenge could not be solved with simple scale-ups or scale-downs. New solutions had to be found for the sampling system, the measuring sensor, the adaptation to the environmental conditions and the processing of fast growing volume of data.

FUNDAMENTALS OF TRANSMISSION FLUCTUATION SPECTROMETRY WITH VARIABLE SPATIAL AVERAGING

Transmission signal of radiation in suspension of particles performed with a high spatial and temporal resolution shows significant fluctuations, which are related to the physical properties of the particles and the process of spatial and temporal averaging. Exploiting this connection, it is possible to calculate the particle size distribution (PSD) and particle concentration. This paper provides an approach of transmission fluctuation spectrometry (TFS) with variable spatial averaging. The transmission fluctuations are expressed in terms of the expectancy of transmission square (ETS) and are obtained as a spectrum, which is a function of the variable beam diameter. The reversal point and the depth of the spectrum contain the information of particle size and particle concentration, respectively.

Synthesis and optical properties of PbMoO_4 nanoplates

Nanometer sized lead molybdate （PbMoO4） plates are prepared through conventional hydrothermal together with sonochemical methods. The plates are then characterized using field-emission scanning electron microscopy, X-ray diffractometry, Fourier transform infrared （FTIR） spectrometry, photoluminescence spectrometry, and ultraviolet-visible （UV-VIS） spectrometry. The results indicate that the nanoplates have a characteristically narrow particle size distribution and their tetragonal scheelite-type structure is confirmed by both X-ray diffractometry and FTIR spectrometry. When the nanoplates are compared with the corresponding bulk crystals, blue shifts in their photoluminescence peaks, wider optical band gaps, and the broadening of the X-ray diffractometer peaks are observed. These can be ascribed to the decrease in crystal size.