Modelling study on the three-dimensional neutron depolarisation response of the evolving ferrite particle size distribution during the austenite–ferrite phase transformation in steels

The magnetic configuration of a ferromagnetic system with mono-disperse and poly-disperse distribution of magnetic particles with inter-particle interactions has been computed. The analysis is general in nature and applies to all systems containing magnetically interacting particles in a non-magnetic matrix, but has been applied to steel microstructures, consisting of a paramagnetic austenite phase and a ferromagnetic ferrite phase, as formed during the austenite-to-ferrite phase transformation in low-alloyed steels. The characteristics of the computational microstructures are linked to the correlation function and determinant of depolarisation matrix, which can be experimentally obtained in three-dimensional neutron depolarisation (3DND). By tuning the parameters in the model used to generate the microstructure, we studied the effect of the (magnetic) particle size distribution on the 3DND parameters. It is found that the magnetic particle size derived from 3DND data matches the microstructural grain size over a wide range of volume fractions and grain size distributions. A relationship between the correlation function and the relative width of the particle size distribution was proposed to accurately account for the width of the size distribution. This evaluation shows that 3DND experiments can provide unique in situ information on the austenite-to-ferrite phase transformation in steels.     

初始模型对含噪动态光散射数据正则化反演结果的影响

分别采用最小模型矩阵、最平坦模型矩阵、最光滑模型矩阵作为初始化模型,对加入5种不同水平随机噪声的90nm窄单峰、90nm宽单峰和250nm窄单峰、250nm宽单峰颗粒体系的模拟分布进行了正则化反演,并对反演结果进行比较。结果表明:当噪声水平为0时,正则化初始模型的选择对反演结果没有明显影响。随着噪声水平的增加,采用三种初始化模型反演得到的峰值误差和粒度分布误差都随之变大,但采用最平坦模型和最光滑模型反演得到的峰值和粒度分布误差明显小于采用最小初始模型的反演误差。当噪声水平大于0.01时,选择最平坦初始模型获得的粒度分布结果优于采用最光滑初始模型和最小初始模型获得的结果,而采用最光滑初始模型反演得到的峰值优于最平坦初始模型和最小初始模型的反演峰值。因此,采用正则化算法处理含噪动态光散射数据时,为得到最优的粒度分布信息,宜采用最平坦初始模型,若需要获取最准确的峰值信息,则应选择最光滑初始模型。     

Determination of Particle Size,Core and Shell Size Distributions of Core–Shell Particles by Analytical Ultracentrifugation

In core–shell nanoparticle analysis, the determination of size distributions of the different particle parts is often complicated, especially in liquid media. Density matching is introduced as a method for analyzing core–shell nanoparticles using Analytical Ultracentrifugation (AUC), making it possible to obtain the core size distribution in liquid dispersions. For this approach, the density of the dispersion is adjusted to the density of the shell. Oil filled nanocapsules are utilized with component densities of around 1 g mL⁻¹ to demonstrate this technique. The shell size distribution is calculated supposing the particle size distribution as a convolution of the shell- and core size distributions. Finally, the distributions of core size, shell thickness, particle size, and particle density and thus particle composition are obtained. To clarify the effect of swelling, AUC measurements are combined with further size characterization methods like Particle Tracking Microscopy and Dynamic Light Scattering.     

Measurement of optical constants for dense media by low-coherence dynamic light scattering

We perform the optical constants measurements for different absorption dense media by low-coherence dynamic light scattering (DLS) technique. The estimated particle size is used to calculate the scattering coefficient of particles suspended in dense media. The path-length resolved intensity distributions of light backscattered from the absorbing dense media are investigated experimentally by virtue of path-length resolved performance in low-coherence DLS measurements. The absorption coefficient can be obtained by applying the measured path-length resolved intensity distributions to the modified Lambert-Beer law. As a result, we proposed a new low-coherence DLS technique in simultaneous measurement of the scattering and absorption coefficients of absorbing dense media.     

Particle Size Distributions Based on a Multipopulation Genetic Algorithm Used in Multiwavelength Lidar

Aerosols influence the radiation budget of the Earth’s atmospheric system. Aerosol particle size distribution is one of the major parameters used for characterizing aerosol influence on radiative forcing. The optical and microphysical properties of aerosol particles over Yinchuan, China, were measured with a multiwavelength lidar developed at Beifang University of Nationalities using backscatter and extinction coefficients at wavelengths of 1064, 532, and 355 nm. These data were used to retrieve particle size distributions. Given the disadvantages of the traditional regularization method, the innovative multipopulation genetic algorithm (MPGA) was used to retrieve the particle size distribution from the lidar data. To verify the feasibility of using the MPGA on multiwavelength lidar data, experiments were carried out under different atmospheric conditions, including a background sunny day, a cloudy day, and a foggy day. The particle size distributions obtained from the multiwavelength lidar data were compared with results retrieved from direct irradiance data from a sun photometer. Results showed that the MPGA is suitable for retrieving particle size distributions from multiwavelength lidar data.     

Influence of synthesis parameters on iron nanoparticle size and zeta potential

Zero valent iron nanoparticles are of increasing interest in clean water treatment applications due to their reactivity toward organic contaminants and their potential to degrade a variety of compounds. This study focuses on the effect of organophosphate stabilizers on nanoparticle characteristics, including particle size distribution and zeta potential, when the stabilizer is present during nanoparticle synthesis. Particle size distributions from DLS were obtained as a function of stabilizer type and iron precursor (FeSO₄·7H₂O or FeCl₃), and nanoparticles from 2 to 200 nm were produced. Three different organophosphate stabilizer compounds were compared in their ability to control nanoparticle size, and the size distributions obtained for particle volume demonstrated differences caused by the three stabilizers. A range of stabilizer-to-iron (0.05–0.9) and borohydride-to-iron (0.5–8) molar ratios were tested to determine the effect of concentration on nanoparticle size distribution and zeta potential. The combination of ferrous sulfate and ATMP or DTPMP phosphonate stabilizer produced stabilized nanoparticle suspensions, and the stabilizers tested resulted in varying particle size distributions. In general, higher stabilizer concentrations resulted in smaller nanoparticles, and excess borohydride did not decrease nanoparticle size. Zeta potential measurements were largely consistent with particle size distribution data and indicated the stability of the suspensions. Probe sonication, as a nanoparticle resuspension method, was minimally successful in several different organic solvents.     

Measuring sub nanometre sizes using dynamic light scattering

Dynamic light scattering (DLS) measures time-dependent fluctuations in the scattering intensity arising from particles undergoing random Brownian motion. Diffusion coefficient and particle size information can be obtained from the analysis of these fluctuations. This paper discusses the factors which will influence the lower size limit of DLS and reports the use of sucrose as a test sample to probe this lower limit of the technique. Hydrodynamic diameter values of less than 1 nm are obtained by the use of 173° backscatter detection that is applied to increase the sensitivity of DLS. The peak means (with standard deviations) obtained for the intensity and volume data from a series of sucrose concentrations, ranging from 5 to 35% w/v, were measured as D_I,Mean = 0.82 nm (0.11 nm) and D_V,Mean = 0.62 nm (0.05 nm), respectively. These sucrose results suggest that sub nanometer measurements are achievable with a precision of 0.1 nm. Evidence to support these size results for sucrose is discussed.     

Real‐Time Measurement of the Size Distribution of Diesel Exhaust Particles using a Portable 4‐stage Electrical Low Pressure Impactor

For this study, a 4 stage electrical low pressure impactor was designed to measure the real‐time size distribution of diesel particulate matter (DPM). For the performance evaluation, sodium chloride (NaCl) particles and dioctyl sebacate (DOS) particles were used. After evaluating the collection efficiency of each stage of the impactor, the size distributions of test particles were estimated using electrical current data and their inversion algorithm, and this was found to agree with the results obtained by a scanning mobility particle sizer (SMPS). For measurement of DPM, a common‐rail direct injection (CRDI) diesel engine, for engine speeds of 1,200 rpm and 1,500 rpm at 2.7 kgf·m, was used. Therefore, it was found that the size distribution of the DPM could be easily obtained, with the currents measured by the impactor and the data inversion algorithm, in less than 5 seconds. Furthermore, the effective density of the DPM could be obtained using the calculated results and the SMPS data.     

基于超声回波重组相位分析的颗粒粒径测量方法

将超声波作用于沉降的颗粒时,由于颗粒的移动,超声回波会出现相位差异。该文通过对测量杯中某一确定深度处的回波信号进行相位分析和重组,发现重组后信号的频率可以计算出粒径;并分别对两种不同粒径分布的聚甲基丙烯酸甲酯(PMMA)微球悬浮液进行了超声波信号采样重组和去噪的实验,实验结果经小波时频方法分析后,证实了颗粒粒径分布与重组信号频率构成的确存在很高的相关性。     

Characterization challenges for a cellulose nanocrystal reference material: dispersion and particle size distributions

Cellulose nanocrystals (CNCs) have high aspect ratios, polydisperse size distributions, and a strong propensity for aggregation, all of which make them a challenging material for detailed size and morphology characterization. A CNC reference material produced by sulfuric acid hydrolysis of softwood pulp was characterized using a combination of dynamic light scattering (DLS), atomic force microscopy (AFM), transmission electron microscopy, and X-ray diffraction. As a starting point, a dispersion protocol using ultrasonication was developed to provide CNC suspensions with reproducible size distributions as assessed by DLS. Tests of various methods for AFM sample preparation demonstrated that spin coating on a positively charged substrate maximizes the number of individual particles for size analysis, while minimizing the presence of agglomerates. The effects of sample-to-sample variability, analyst bias, and sonication on size distributions were assessed by AFM. The latter experiment indicated that dispersion of agglomerates by sonication did not significantly change the size distribution of individual CNCs in suspension. Comparison with TEM data demonstrated that the two microscopy methods provide similar results for CNC length (mean ~?80 nm); however, the particle width as measured by TEM is approximately twice that of the CNC height (mean 3.5 nm) measured by AFM. The individual crystallite size measured by X-ray diffraction is intermediate between the two values, although closer to the AFM height, possibly indicating that laterally agglomerated CNCs contribute to the TEM width. Overall, this study provides detailed information that can be used to assess the factors that must be considered in measuring CNC size distributions, information that will be useful for benchmarking the performance of different industrially sourced materials.     

基于颗粒粒度信息分布特征的动态光散射加权反演

宽分布和双峰分布颗粒的准确反演是动态光散射技术至今未能有效解决的难题,尤其峰值位置比小于2:1且含有大粒径颗粒(350 nm)的双峰分布.造成这一难题的主要原因包括:1)单角度测量数据的粒度信息含量不足;2)常规反演方法对测量数据的噪声抑制以及粒度信息利用缺乏针对性.对测量数据(即光强自相关函数)的研究发现,数据噪声主要分布在长延迟时段,而粒度信息集中分布在衰减延迟时段.基于此,本文提出了采用粒度信息分布为底数、调节参数为指数的权重系数对自相关函数进行加权反演的约束正则化方法.由于采用了与粒度信息分布一致的权重系数,该方法既充分利用了衰减延迟时段的粒度信息,又有效地抑制了长延迟时段的数据噪声.不同噪声水平下,宽分布和双峰分布颗粒体系的反演结果表明,与常规反演方法相比,这一方法可以获得更为准确的宽分布和近双峰分布的反演结果.     

Determination of Particle Size Distribution by the analysis of intensity-constrained multi-angle photon correlation spectroscopic data

Laser light scattering (LLS), especially dynamic laser light scattering (DLS), also known as photon correlation spectroscopy (PCS), is a well established method for particle size distribution analysis. It usually involves a Laplace inversion of the field autocorrelation function. However, the resolution is limited because of the ill-conditioned nature of this Laplace inversion. No unique solution exists when noise is present on the data. In contrast with this ill-conditioned nature, the angular dependence of scattered (static) intensities is precisely not ill-conditioned, which allows the resolution of the ill-conditioned inversion of DLS data to be improved. In order to characterize samples with more complicated size distributions, an intensityconstrained multi-angle PCS data analysis program has been developed, which is an alternative way of normalizing the field correlation function to that reported by Cummins and Staples [12]. In this program, the field autocorrelation function is normalized to the scattering intensity by using a predetermined coherent factor at each angle, which provides an additional constraint on the Laplace inversion of multi-angle PCS data analysis. The alternative analysis improves the resolution of PCS and provides a more reliable particle size distribution than single-angle data analysis. Both simulated and measured LLS data are used to illustrate its application, resolution and limitations.     

Sizing Polydisperse Dispersions by Focused Beam Reflectance and Small Angle Static Light Scattering

In this work, two different methods for particle characterization, namely focused beam reflectance and small angle static light scattering, are quantitatively compared. The results are presented in the form of moment ratios of the particle size distribution, i.e., the number weighted diameter, D_1/0, and the volume weighted diameter, D_4/3, for a broad range of particle size distributions ranging from 20 to 400 μm. Various aqueous dispersions including narrow, broad, and bimodal particle size distributions of spherical shaped ceramic beads were used in the comparison. It was found that the moment ratios obtained by focused beam reflectance measurements and small angle static light scattering correlate well, in the case of spherical particles. Furthermore, it was found that the D_1/0 values obtained by focused beam reflectance measurements are more sensitive to the presence of a small fraction of fine particles in a bimodal distribution than those obtained by small angle static light scattering.     

Particle agglomeration and properties of nanofluids

The present study demonstrates the importance of actual agglomerated particle size in the nanofluid and its effect on the fluid properties. The current work deals with 5 to 100 nm nanoparticles dispersed in fluids that resulted in 200 to 800 nm agglomerates. Particle size distributions for a range of nanofluids are measured by dynamic light scattering (DLS). Wet scanning electron microscopy method is used to visualize agglomerated particles in the dispersed state and to confirm particle size measurements by DLS. Our results show that a combination of base fluid chemistry and nanoparticle type is very important to create stable nanofluids. Several nanofluids resulted in stable state without any stabilizers, but in the long term had agglomerations of 250 % over a 2 month period. The effects of agglomeration on the thermal and rheological properties are presented for several types of nanoparticle and base fluid chemistries. Despite using nanodiamond particles with high thermal conductivity and a very sensitive laser flash thermal conductivity measurement technique, no anomalous increases of thermal conductivity was measured. The thermal conductivity increases of nanofluid with the particle concentration are as those predicted by Maxwell and Bruggeman models. The level of agglomeration of nanoparticles hardly influenced the thermal conductivity of the nanofluid. The viscosity of nanofluids increased strongly as the concentration of particle is increased; it displays shear thinning and is a strong function of the level of agglomeration. The viscosity increase is significantly above of that predicted by the Einstein model even for very small concentration of nanoparticles.     

Experimental and numerical study of the evolution of soot primary particles in a diffusion flame

The evolution of primary soot particles is studied experimentally and numerically along the centreline of a co-flow laminar diffusion flame. Soot samples from a flame fueled with C₂H₄ are taken thermophoretically at different heights above the burner (HAB), their size and nano-structure are analysed through TEM. The experimental results suggest that after inception, the nascent soot particles coagulate and coalesce to form larger primary particles (?～?5 to 15 nm). As these primary particles travel along the centreline, they grow mainly due coagulation and condensation and a layer of amorphous hydrocarbons (revealed by HRTEM) forms on their surface. This amorphous layer appears to promote the aggregation of primary particles to form fractal structures. Fast carbonisation of the amorphous layer leads to a graphitic-like shell around the particles. Further graphitization compacts the primary particles, resulting in a decrease of their size. Towards the flame tip the primary particles decrease in size due to rapid oxidation. A detailed population balance model is used to investigate the mechanisms that are important for prediction of primary particle size distributions. Suggestions are made regarding future model development efforts. Simulation results indicate that the primary particle size distributions are very sensitive to the parameterization of the coalescence and particle rounding processes. In contrast, the average primary particle size is less sensitive to these parameters. This demonstrates that achieving good predictions for the average primary particle size does not necessarily mean that the distribution has been accurately predicted.     

A comparison of atomic force microscopy (AFM) and dynamic light scattering (DLS) methods to characterize nanoparticle size distributions

This paper compares the accuracy of conventional dynamic light scattering (DLS) and atomic force microscopy (AFM) for characterizing size distributions of polystyrene nanoparticles in the size range of 20–100 nm. Average DLS values for monosize dispersed particles are slightly higher than the nominal values whereas AFM values were slightly lower than nominal values. Bimodal distributions were easily identified with AFM, but DLS results were skewed toward larger particles. AFM characterization of nanoparticles using automated analysis software provides an accurate and rapid analysis for nanoparticle characterization and has advantages over DLS for non-monodispersed solutions.     

Synthesis of magnetic nanoparticles: effects of polyelectrolyte concentration and pH

This study refers to the effect of sodium polyacrylate concentration (1 to 5 mass %) and pH (10 to 12) on the synthesis of magnetic nanoparticles (magnetite?Cmaghemite) and their characterization by Mössbauer spectroscopy. The magnetic particles were obtained by coprecipitation method using iron chloride (II) and iron chloride (III) as precursor reagents and sodium polyacrylate as stabilizing agent. All samples showed Mössbauer broad resonance lines in typical doublet and sextets patterns of magnetite or maghemite with corresponding wide particle size distributions. The stability of magnetic particles was carried out by measuring particle sizes with dynamic light scattering (DLS). The z-average values for magnetic particles were in the range 24 to 590 nm and no significant change in size was observed on aging by leaving this material in air for 20 days. X-ray diffraction patterns showed characteristic peaks of the spinel structure and have an increase in their broadening as the pH decreases, effect that is dominated by the decrease in crystallite sizes. The nanoparticles showed to be magnetic at pH 12 and at room temperature.     

Appearance of an artifact peak in the particle size distribution measured by DLS at low concentrations

The dynamic light scattering (DLS) method allows the determination of the particle size distribution of suspensions. At high dilutions, an artifact peak appears in the size distribution, which does not correspond to actual particles, but is caused by crossing the scattering volume boundaries by individual particles. The parameters of this peak are analyzed, the causes of its appearance and its effect on determined particle sizes are studied.     

Inverse problem for particle size distributions of atmospheric aerosols using stochastic particle swarm optimization

As a part of resolving optical properties in atmosphere radiative transfer calculations, this paper focuses on obtaining aerosol optical thicknesses (AOTs) in the visible and near infrared wave band through indirect method by gleaning the values of aerosol particle size distribution parameters. Although various inverse techniques have been applied to obtain values for these parameters, we choose a stochastic particle swarm optimization (SPSO) algorithm to perform an inverse calculation. Computational performances of different inverse methods are investigated and the influence of swarm size on the inverse problem of computation particles is examined. Next, computational efficiencies of various particle size distributions and the influences of the measured errors on computational accuracy are compared. Finally, we recover particle size distributions for atmospheric aerosols over Beijing using the measured AOT data (at wavelengths λ=0.400, 0.690, 0.870, and 1.020 μm) obtained from AERONET at different times and then calculate other AOT values for this band based on the inverse results. With calculations agreeing with measured data, the SPSO algorithm shows good practicability.     

Size Determination of Au Aerosol Nanoparticles by Off-Line TEM/STEM Observations

Determination of particle size distributions of Au aerosol nanoparticles has been performed by a TEM/STEM investigation. The particles are generated by an evaporation/condensation method and are size-selected by differential mobility analyzers (DMA) based on their electrical mobility. Off-line TEM measurements resulted in equivalent projected area diameters assuming that the particles are spherical in shape. In this paper critical factors such as magnification calibration, sampling, image analysis, beam exposure and, particle shape are treated. The study shows that the measures of central tendency; mean, median and mode, are equal as expected from a narrow size distribution. Moreover, the correlation between TEM/STEM and DMA are good, in practice 1:1. Also, STEM has the advantage over TEM due to enhanced contrast and is proposed as an alternative route for determination of particle size distributions of nanoparticles with lower contrast.