Quantification of the pore size distribution (porosity profiles) in microfiltration membranes by SEM,TEM and computer image analysis

Transport properties of membranes are closely related to morphological properties like surface porosity and variation of their inner pore structure. Scanning electron microscopy (SEM) as well as transmission electron microscopy (TEM) are powerful tools to characterise the microscopical pore structure of membranes in a qualitative manner. In order to provide more quantitative data of surface and cross-sectional pores computer image analysis can be used. Parameters like ‘porous area fraction’ and ‘mean free path length’ have been selected to describe the pore distribution within porosity profiles in order to consider the effect that the pores within the cross-section are connected to each other.     

A coded support for use in analysis of aerosols by different spectroscopic methods

A device used for localization of solid atmospheric microparticles on silicon wafers is described. Dimensions of the device are 5.04 mm × 5.0809 mm. This support facilitates the analysis by other instruments of particles previously located by scanning electron microscopy (SEM). The area of the wafer is divided into tables and cells identified by microlithographic alphanumeric characters. These characters are made of an alloy of aluminium, silicon and copper which can be visualized by imaging secondary-ion mass spectrometry (SIMS). The quality of the image produced by SIMS is worse than that obtained with SEM, mainly because of the bigger diameter of the SIMS ion beam, but the symbols and patterns used are still easily legible. Examples are given of images obtained from SEM, SIMS and secondary electron ion-induced microscopy (SEIIM).     

Structural and electrical properties of crystals of substituted polyaniline

The simultaneous polymerization and crystallization of aniline has been reported earlier. In this article, the X‐ray crystal structure analysis, SEM morphological analysis and electrical properties of such crystals of oligo‐polyanilines are being reported. The structural analysis shows a pseudo‐orthorhombic lattice. The SEM images reveal flaky and triangular growth habit with granular overgrowths on the surface. The bulk conductivities achieved vary from 10^?5 S/cm to 10^?7 S/cm as the oxidant concentration is reduced from 5 to 0.1%. The temperature dependence showed a transition point upto which there is a decrease in current and above which the current increases. The ESR studies reveal polarons involved in charge conduction and their concentration is proportional to the oxidant concentration. The X‐ray patterns, conductivities, and ESR results have been correlated with the degree of polymerization results obtained from GPC studies. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 1127–1137, 2007     

On estimation of bias field in MRI images: polynomial vs Gaussian surface fitting method

Surface fitting is one of the well‐known retrospective methods for bias field estimation from magnetic resonance imaging (MRI) images. Bias field in MRI images is primarily caused because of radio frequency–coil nonuniformity, improper image acquisition process, patient movement, and so on. The bias field can be characterized by any slow variant and smooth function because of its slow variant nature. In this paper, we present a comparative study between polynomial and Gaussian surface fitting methods. In particular, we have used both the second‐ and third‐order polynomial functions to estimate the bias field. In this study, we approximate the bias field in two different ways. In the first method, the surfaces are fitted on the anatomical tissue regions individually and then fused to estimate the bias field. Conversely, in the second method, we have done the same over the entire image region. We have tested on three volumes of simulated and one volume of real‐patient MRI brain images and validated the results by both the qualitative and quantitative analyses. The quantitative analyses are presented in standard deviation and coefficient of joint variation. The analysis of the simulation results show that the Gaussian surface fitting method yields better results in both the cases, where the surface fitting is done on entire image and individual tissue regions.     

The distribution of particles characterized by size and free mobility within polydisperse populations of protein-polysaccharide conjugates, determined from two-dimensional agarose electropherograms

New approaches for the characterization of polydisperse particle populations are presented*. The investigated samples contain virus-sized protein-polysaccharide conjugates which had previously been prepared as immunogens against bacterial meningitis (Hib). The analysis is based on two-dimensional agarose electrophoresis (Serwer-type). This method, like the one of O'Farrell, achieves a separation according to size and charge. It relies on a different principle, however, and is applicable to nondenatured particles which are 100 to more than 1000 times larger in mass than regular uncrosslinked proteins. Data from stained gel patterns are evaluated by the computer program ELPHOFIT, which makes it possible to standardize the gel and to construct a nomogram which defines every position on the gel in terms of particle size and free mobility (related to surface net charge density). The output of ELPHOFIT, consisting of nomogram parameters, is transferred to the image processing program GELFIT. This software is used to evaluate the computer images obtained by digitizing the stained gel patterns: (i) The nomogram is electronically superimposed on the computer image. (ii) The gel pattern is transformed from a curvilinear to a rectangular coordinate system of particle size and free mobility. The center of gravity as well as density maxima are given in coordinates of particle size and free mobility. Ranges of grey levels can be accentuated by adding 16 pseudocolors. (iii) Using surface-stripping techniques, GELFIT provides an estimate for the number of major subpopulations within each preparation. (iv) Numerical values for the distribution of particle size and free mobility are determined. Using program IMAGE, the quantitative physical assessment of a given conjugate preparation is presented in the form of a computer-generated three-dimensional plot, the shape of which serves to identify and characterize the preparation visually. The data analysis based on digitized two-dimensional gel patterns is automated to an extent that a technician can perform routine evaluations. It uses the Macintosh II personal computer.     

An improved pixel-based approach for analyzing images in two-dimensional gel electrophoresis

An improved pixel-based approach for analyzing 2-DE images is presented. The key feature of the method is to create a mask based on all gels in the experiment using image morphology, followed by multivariate analysis on the pixel level. The method reduces the impact of noise and background by identifying regions in the image where protein spots are present, but make no assumption on individual spot boundaries for isolated spots. This makes it possible to detect significant changes in complex regions, and visualize these changes over multiple gels in an easy way. False missing values and spot volumes caused by imposing erroneous spot boundaries are thus circumvented. The approach presented gives improved pixel-based information from the gels, and is also an alternative to existing methods for data-reduction, significance testing and visualization of 2-DE data. Results are compared with software using a common spot boundary approach on an experiment consisting of 35 full size gel images. Gel alignment is required before analysis.     

煤燃烧过程中表面结构变化的SEM图像分析

介绍了SEM图像分析的多种方法,并讨论了各自的描述能力,利用这些方法分析煤在燃烧各阶段SEM图像,通过研究得到煤在燃烧过程中表面分形维数的变化规律,同时可获得表面孔的某些参数变化历程。分析表明,淮南低变质煤在850℃燃烧过程中,煤焦颗粒表面的分维数有一个先变低后变高的过程,煤焦表面分维数在2.2至2.5区间内变化;同时孔径分布由近双曲线分布变化为近正态分布,孔油加权平均形状因子增加,在研究过程中发现,不同的计算方法会对图像的分形维数值产生影响,确定合适的计算方法是分形理论在煤燃烧领域中应用的关键。通过比较发现Xie法较为适合计算煤焦表面SEM图像。     

Two-dimensional electrophoresis analysis of proteomics based on image feature and mathematical morphology

Protein analysis techniques, including 2-D electro- phoresis, image analysis, biological mass spectrometry, database search, etc., are fundamental technologies of proteomics, a front area in biochemistry and life sci- ences[1―3]. Among them image analysi…     

Accuracy of electrospun fiber diameters: The importance of sampling and person-to-person variation

Potential sampling errors (regional variation) on an electrospun mat were explored and person-to-person (analyst affect) variation in image analysis of the fiber diameter were investigated via detailed statistical analyses. Scanning electron microscope (SEM) samples were prepared from the vertical midline of a single non-woven mat of electrospun polyethylene oxide. Thirteen analysts with identical training and instructions measured the diameters of the nanofibers from the six SEM images and statistical analyses were performed on the resulting data. The fiber diameters were significantly different in the lower region than the upper and center regions. Furthermore, the fiber diameters in the lower region—from micrographs taken only millimeters apart—were statistically different demonstrating a statistically significant regional variation in the sample. Furthermore, statistically significant variation between the analysts also was observed, with the average fiber diameter ranging from 166 nm to 276 nm.     

Fusion of 2-D SIMS Images Using the Wavelet Transform

 Secondary ion mass spectroscopy (SIMS) is a powerful method for element distribution examination of conducting and semi-conducting surfaces at high spatial resolution and with a high sensitivity. Routine surface analysis produces about 8 to 15 images in a short time, each of which displays the intensity distribution of one mass, thus generating a multispectral SIMS image. Formation of occlusions, segregations, and the overall location of the elements relative to each other, are difficult to recognise when looking at n separate 2-D images. Image fusion is a process whereby images obtained from various sensors, or at different moments of time, or under different conditions, are combined together to provide a more complete picture of the object under investigation. The process of combining SIMS images may be viewed as an attempt to compensate for the inherent effect of SIMS to channel the information obtained from the sample into different images, corresponding to different element phases. The wavelet transform is a powerful method for fusion of images. This work covers the use of wavelet based fusion algorithms on multispectral SIMS images, evaluating the performance of different wavelet based fusion rules on different type of image systems and comparing the results to conventional fusion techniques. An aim of this study is to increase the information, i.e. the number of masses, which can be merged into one image in order to enhance the perception and interpretation of the SIMS surface images.     

Orientation Imaging Microscopy for the Transmission Electron Microscope

The resolution limit of Orientation Imaging Microscopy in the Scanning Electron Microscope is between 20 nA and 80 nA depending on the basic resolution/beam current performance of the SEM, the sample atomic number and the level of residual strain within it. The newer technique of orientation imaging in the transmission electron microscope, TEM, improves on this resolution limit by a factor of five to ten. The new technique is based on a novel procedure for determining the crystallography of separate small volumes in the sample by examination of a large series of dark field images. Each image is recorded for a different diffraction condition. This is achieved by using a computer to direct the electron beam onto the same area of the sample so that it covers all directions within a cone of semi-apex angle 3 degrees. Analysis of the intensity of the same point in each of the dark field images permits reconstruction of a diffraction pattern for that point providing the data to calculate its crystal orientation. The process is repeated for each point in the image. The Orientation Image Micrograph is constructed from the orientations so determined. The technique is shown to be capable of producing orientation micrographs of high spatial resolution for unstrained samples. For highly strained samples difficulties are encountered in accurately indexing the complicated diffraction patterns that are observed. Methods to improve the indexing procedures involve determining the sub-cell structure first from a comparison of patterns from adjacent pixels and then summing all patterns belonging to a single sub-cell. The resultant improvement in pattern quality permits more reliable determination of orientation. Examples of this procedure are taken from studies of deformed aluminum.     

Use of imaging multivariate analysis to improve biochemical and anatomical discrimination in desorption electrospray ionisation mass spectrometry imaging

Desorption electrospray ionisation (DESI) mass spectrometry images usually contain a large amount of information that can be difficult to interpret in an objective manner. We explore the use of imaging multivariate analysis (MVA) on DESI images of protein spots and rat brain sections to automatically assign peaks and improve discrimination of spatially important features. DESI parameters were optimised on an ion trap mass spectrometer for (a) consistent imaging of dried single and mixture spots of insulin, myoglobin and BSA from a Permanox slide, and (b) to produce a MS image of rat brain coronal section at 100 μm resolution. Multivariate curve resolution (MCR), an imaging MVA technique was applied to these images after appropriate data binning. MCR analysis on DESI images of protein mixture spots allowed the multiply charged peaks of a number of proteins to be distinctly separated. Application of MCR to a DESI image of a rat brain coronal section deconvoluted the image into components that showed biologically important features. Further application of MCR to a subsection of the image produced a component that clearly separated out the substantia nigra region, which allowed us to produce a biochemical anatomy for this area of the brain. We have demonstrated the ability of imaging MVA to automatically and objectively analyse DESI images of standardised and complex biological samples, and have shown its capacity for detailed spatial profiling of biomolecules in specific morphological regions. We propose the routine use of this technique for future DESI imaging experiments.     

Measuring acoustic energy density in microchannel acoustophoresis using a simple and rapid light-intensity method

We present a simple and rapid method for measuring the acoustic energy density in microchannel acoustophoresis based on light-intensity measurements of a suspension of particles. The method relies on the assumption that each particle in the suspension undergoes single-particle acoustophoresis. It is validated by the single-particle tracking method, and we show by proper re-scaling that the re-scaled light intensity plotted versus re-scaled time falls on a universal curve. The method allows for analysis of moderate-resolution images in the concentration range encountered in typical experiments, and it is an attractive alternative to particle tracking and particle image velocimetry for quantifying acoustophoretic performance in microchannels.     

Effects of ozone in surface modification and thermal stability of SEBS block copolymers

SEBS block copolymers were treated under mild conditions in an ozone atmosphere, producing very slightly chemically-modified surfaces. The thermal stability was analysed by chemiluminescence and related to morphological changes observed by AFM. The intrinsic thermal stability was diminished by ozone exposure, but the oxidation induction times were delayed which indicates an enhancement of thermal stability under oxidative conditions. Also, chemiluminescence analysis showed the presence of a typical order-disorder transition at temperatures around 120 °C. Two different sets of samples which showed different morphological patterns were imaged by AFM. The effects of micro-domain separation and inter-domain structure on thermal properties are discussed and explained by a coarsening of the internal interface induced by ozone. A detailed 2D Fourier transformed analysis of AFM images allowed us to identify a regular wrinkled nano-pattern induced by uniaxial strain combined with ozone treatment, offering new opportunities in applications ranging from organic electronics to bio-patterning.     

扫描电镜用于PTFE拉伸微孔膜的形态结构研究--研制中PTFE拉伸微孔膜的SEM鉴定

运用扫描电镜(SEM)图像研究了聚四氟乙烯(PTFE)粉料经过推挤、辊压和拉伸得到的微孔膜的形态结构,观察到膜是由网状纤维及由它所连接的结点所组成.单相和双向拉伸显著影响到膜结构的改变,而未经热处理的拉伸膜的丝状纤维在放置中收缩改变了膜的微孔形态结构,但在孔径测定中没有显著变化.认为纤维丝是PTFE粉料在推挤和辊压中形成的结点在拉伸中伸展引出的并产生孔隙,而由于从SEM仅能观察到1 nm深度的膜表面层,厚度达数十微米多孔膜的孔径分布应是很错杂的.     

Denoising and multivariate analysis of time‐of‐flight SIMS images

Time‐of‐flight SIMS (ToF‐SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF‐SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF‐SIMS image data. Three established denoising algorithms—down‐binning, boxcar and wavelet filtering—were applied to ToF‐SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component score images and the ability of the principal components to explain the chemistries responsible for the image contrast. All filtering methods were found to improve the performance of PCA for all image datasets studied by improving capture of image features and producing principal component score images of higher quality than the unfiltered ion images. The loadings for filtered and unfiltered PCA models described the regions of chemical contrast by identifying peaks defining the regions of different surface chemistry. Down‐binning the images to increase pixel size and signal was the most effective technique to improve PCA performance. Copyright © 2003 John Wiley & Sons, Ltd.