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Core-shell (CS) particles have been increasingly used for a wide range of applications due to their unique properties by merging individual characteristics of the core and the shell materials. The functionality of the designed particles is strongly influenced by their surface roughness. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task for Scanning Electron Microscopy (SEM).
The SEM images contain two-dimensional (2D) information providing contour roughness data only from the projection of the particle in the horizontal plane. This study presents a practical procedure to achieve more information by tilting the sample holder, hence allowing images of different areas of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, quasi three-dimensional (3D) information is obtained.
Three types of home-made particles were investigated: i) bare polystyrene (PS) particles, ii) PS particles decorated with a first magnetic iron oxide (Fe3O4) nanoparticle shell forming CS microbeads, iii) PS/Fe3O4 particles closed with a second silica (SiO2) shell forming core-shell-shell (CSS) microbeads. A series images of a single particle were taken with stepwise tilted sample holder up to 10° by an SEM with high-resolution and surface sensitive SE-InLens® mode.
A reliable analysis tool has been developed by a script in Python to analyze SEM images automatically and to evaluate profile roughness quantitatively, for individual core-shell microparticles. Image analysis consists of segmentation of the images, identifying contour and the centre of the particle, and extracting the root mean squared roughness value (RMS-RQ) of the contour profile from the particle projection within a few seconds.
The variation in roughness from batch-to-batch was determined with the purpose to set the method as a routine quality check procedure. Flow cytometry measurements provided complementary data. Measurement uncertainties associated to various particle orientations were also estimated.
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.
This study describes the motion of magnetizable particles of spherical shape with radius at most of 1 μm, also referred to as microbeads, immersed in a liquid under laminar flow conditions in a microfluidic channel. An external magnetic field is applied in part of the system such that it permeates the channel and is characterized by a spatially varying magnetic field, i.e., the gradient of the magnetic field is nonzero. The beads are superparamagnetic; hence they can reach high level of magnetization in the presence of a magnetic field, and this magnetization disappears when the field is zero. Therein lies the attractiveness of these microbeads and the potential for applications because their motion can be controlled using an external magnetic field. The motion is governed by several factors, including the magnetic force acting on microbeads (particles), the drag force due to viscosity, the interaction between particles and the fluid, as well as the interaction between particles themselves. For a single particle case, the trajectory of the motion is determined by balancing the drag and magnetic forces acting on the particle, a calculation that in general requires numerical integration. For a system consisting of an ensemble of interacting particles, several regimes of motion dominated by one of the factors are identified. Of particular interest are the systems dominated by the large number of particles in the ensemble, i.e., high particle concentration, in which cases the wake influences the flow downstream. This effect is qualitatively investigated by considering the Navier-Stokes equation with and without the magnetic force contribution.
Welcome to the poster Towards Determination of Surface Roughness from a SEM Image, a contribution from BAM in Berlin, Germany. This work is part of the MamaLoCA project, which aims to develop a biosensor for the detection of mycotoxins in cereals. Biosensors come in a great variety, one of which makes use of microscopic beads produced by homogenous coating of polystyrene microspheres. The beads are functionalized by decorating them with bioreceptors – in our case antibodies – which then specifically react with the analyte – in our case mycotoxins – and emit an electrical or optical signal. The functionalization of the beads depends on the surface roughness because this determines the amount and orientation of binders. In other words, the surface roughness affects the accessibility to the binding sites and influences device sensitivity, hence its quantitative determination is an important step in evaluating the quality of the biosensor in general.
The presented solution to the problem of the estimation of surface roughness relies in the repetitive characteristics on the surface of the beads. A SEM image of the bead shows a raspberry like microparticle with a variation of grayscale values, which arise from the secondary electron yield. The principle of the measurement measures the variation of grayscale values along a circumference of a circle centred in the centre of the particle and with an arbitrary radius. The grayscale value variation along the given circumference gives the so-called z-modulation or the lateral profile. By performing Fast Fourier Transform on this profile we obtain the power spectrum as a function of the spatial frequencies through which the grayscales vary. The maximal value for spatial frequency then reveals the most common feature along one given circumference. Surface roughness then is the feature frequency in the spatial domain. This calculation is repeated for several concentric circles with different radii over the particle.
The results for the same particle but recorded at two different accelerating voltages show that the applied method has a potential to reveal the roughness. Interpretation of results from an SE InLens SEM image obtained using 3 kV shows that surface roughness is about 21 nm, which is in a good agreement with an alternative method given in a different presentation. The results from the 10 kV are underestimated due to the loss of surface sensitivity on the SE InLens detection at high voltages.
In conclusion, this method shows promise in determining quantitatively the surface roughness from a single SEM image and its validation is being sought using 3D SEM images and AFM methods.
A particle roughness analysis tool, based on electron microscopy images (SEM and TEM). The influence of various parameters on the calculated roughness was also investigated: the setting of the proper threshold, accelerating voltage, etc. The samples were gradually tilted to extend imaging information of more than only one projection. Furthermore, the measurement uncertainty of the profile roughness of particles associated to various orientations was estimated.
Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) are frequently used for analytical purposes in research and industry, but they seldom are part of the chemistry Curriculum or laboratory exercises. This case study paper describes the combined application of LIBS and PCA during a research internship for an undergraduate student. The instructional method applied was based on a one-on-one mentorship, in which case the learner was engaged in a Research work. The learning activities included theoretical introductions to the LIBS and PCA methods, numerical simulation, experiments, and data analysis.
The study covered three main topics: analysis of LIBS spectra, application of PCA for clustering, and use of PCA for experimental design. The realization of the study was instructive for all parties involved: from the mentorship point of view, it is concluded that the topics can be covered during an internship or developed into a one semester long research-based module of a chemistry program or a final year project. The student, on the other hand, developed profound technical skills in performing experiments and using PCA software for data analysis.
CS particles show unique properties by merging individual characteristics of the core and the shell materials. An alteration particularly in their surface roughness affects the final performance of the particles in the targeted application. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task employing microscopic techniques being scarce and showing large differences in terms of methodology and results.
In our previous work, we have reported a systematic study with a reliable analysis tool, which evaluates profile roughness quantitatively, for individual core-shell microparticles using electron microscopy (EM) images of both types, Scanning Electron Microscopy (SEM) and transmission mode SEM (or TSEM). The SEM images contain two-dimensional (2D) information, therefore, provide profile roughness data only from the projection in the horizontal plane (in other words, from the “belly”) of a spherical particle. The present study offers a practical procedure to give access to more information by tilting the sample holder and hence allowing images of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, extended information on surface roughness of the particle can be extracted. Thus, instead of obtaining 2D information from a single SEM image, three-dimensional (3D) information is obtained from 2D projections recorded at different particle orientations.
A novel technique based on laser induced plasma imaging is proposed to measure residual pressure in sealed containers with transparent walls, e.g. high voltage vacuum interrupter in this paper. The images of plasma plumes induced on a copper target at pressure of ambient air between 10−2Pa and 105Pa were acquired at delay times of 200ns, 400ns, 600ns and 800ns. All the plasma images at specific pressures and delay times showed a good repeatability. It was found that ambient gas pressure significantly affects plasma shape, plasma integral intensities and expansion dynamics. A subsection characteristic method was proposed to extract pressure values from plasma images. The method employed three metrics for identification of high, intermediate and low pressures: the distance between the target and plume center, the integral intensity of the plume, and the lateral size of the plume, correspondingly. The accuracy of the method was estimated to be within 15% of nominal values in the entire pressure range between 10−2Pa and 105Pa. The pressure values can be easily extracted from plasma images in the whole pressure range, thus making laser induced plasma imaging a promising technique for gauge-free pressure detection.
Spatial Heterodyne Spectroscopy (SHS) is a spectrometric technique that combines both dispersive and interferometric features into a customizable instrument. The Basis of SHS is a Michelson interferometer with its mirrors replaced by diffraction gratings and with no moving parts. The output signal from SHS is the interferogram, which is recorded with a 1D or 2D pixel array detector. The spatial periodicity of the fringes on the interferogram is a function of the wavelength of the diffracted light. Using the Fast Fourier Transform, the original optical spectrum that enters SHS is retrieved. The light that is analyzed by SHS can come from a variety of sources. In our work, we used Raman scattering and Laser-Induced Plasma to perform quantitative and qualitative analyses. Figure 1 compares the performance of the SHS with that of high Resolution echelle and portable low-resolution asymmetrically crossed Czerny-Turner spectrometers (OO in Fig.1). The analyzed light came from the plasma induced on a stainless-steel reference material. The SHS exhibits the resolution comparable to that of the echelle spectrometer used, about 8000. Due to a high throughput of the SHS (theoretically, ~200 times higher than that of grating instruments), the number of spectra needed to be accumulated for comparable signal-to-noise ratios is much smaller than in the case of the echelle and comparable to OO spectrometers.
Examples of Raman SHS applied to several pure liquids are given in Fig. 2. Raman SHS was used in three different settings: (i) for classification of six types of oils, (ii) for univariate/multivariate analysis of binary mixture cyclohexane-isopropanol, and (iii) for multivariate analysis of glycerol solution in water. For the last two settings, chemometric analysis of the spectra yielded linear calibration plots over the range 1-90% of concentrations of isopropanol in cyclohexane, and 0.5-10% of glycerol in water.