| 1. |
- Eriksson Barman, Sandra, 1985, et al.
(författare)
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A three-dimensional statistical model for imaged microstructures of porous polymer films
- 2018
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 269:3, s. 247-258
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Tidskriftsartikel (refereegranskat)abstract
- A thresholded Gaussian random field model is developed for the microstructure of porous materials. Defining the random field as a solution to stochastic partial differential equation allows for flexible modelling of nonstationarities in the material and facilitates computationally efficient methods for simulation and model fitting. A Markov Chain Monte Carlo algorithm is developed and used to fit the model to three-dimensional confocal laser scanning microscopy images. The methods are applied to study a porous ethylcellulose/hydroxypropylcellulose polymer blend that is used as a coating to control drug release from pharmaceutical tablets. The aim is to investigate how mass transport through the material depends on the microstructure. We derive a number of goodness-of-fit measures based on numerically calculated diffusion through the material. These are used in combination with measures that characterize the geometry of the pore structure to assess model fit. The model is found to fit stationary parts of the material well. Lay description We develop a stochastic model for the pore structure of a polymer material which is used as coatings to control drug release from pharmaceutical tablets. The pore geometries of the coatings determine how quickly the drug is released. For instance, the drug transport through a coating with many bottlenecks will be slower compared to the transport through a coating with a lower number of bottlenecks. The model will in future work be used to analyze how the rate of transport of the drug through the coating depends on the distribution of bottlenecks and other characteristics of the pore geometry. In this article we present the model. Each stochastic simulation from the model gives a different pore structure, but with similar pore geometries. This randomness in the model captures that each coating is different. We develop an efficient mathematical algorithm to fit the model to microscopy images of the material. The algorithm uses the information in the microscopy images to find the parameters of the model that make the pore geometry of the microscopy images as similar as possible to the pore geometries of stochastic simulations from the model. To determine how similar the geometries are we use measures that summarize different properties of the pore geometries. We also derive a new measure which compares the results of numerically calculated transport through the pore structures. These measures show that the stochastic simulations from the model are similar to the microscopy images, and we conclude that the model fits the data well.
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| 2. |
- Häbel, Henrike, 1987, et al.
(författare)
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Colloidal particle aggregation in three dimensions
- 2019
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 275:3, s. 149-158
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Tidskriftsartikel (refereegranskat)abstract
- Colloidal systems are of importance not only for everyday products, but also for the development of new advanced materials. In many applications, it is crucial to understand and control colloidal interaction. In this paper, we study colloidal particle aggregation of silica nanoparticles, where the data are given in a three-dimensional micrograph obtained by high-angle annular dark field scanning transmission electron microscopy tomography. We investigate whether dynamic models for particle aggregation, namely the diffusion limited cluster aggregation and the reaction limited cluster aggregation models, can be used to construct structures present in the scanning transmission electron microscopy data. We compare the experimentally obtained silica aggregate to the simulated postaggregated structures obtained by the dynamic models. In addition, we fit static Gibbs point process models, which are commonly used models for point patterns with interactions, to the silica data. We were able to simulate structures similar to the silica structures by using Gibbs point process models. By fitting Gibbs models to the simulated cluster aggregation patterns, we saw that a smaller probability of aggregation would be needed to construct structures similar to the observed silica particle structure.
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| 3. |
- Häbel, Henrike, 1987, et al.
(författare)
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From static micrographs to particle aggregation dynamics in three dimensions
- 2016
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Ingår i: Journal of Microscopy. - : Wiley. - 1365-2818 .- 0022-2720. ; 262:1, s. 102-111
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Tidskriftsartikel (refereegranskat)abstract
- Studies on colloidal aggregation have brought forth theories on stability of colloidal gels and models for aggregation dynamics. Still, a complete link between developed frameworks and obtained laboratory observations has to be found. In this work, aggregates of silica nanoparticles (20 nm) are studied using diffusion limited cluster aggregation (DLCA) and reaction limited cluster aggregation (RLCA) models. These processes are driven by the probability of particles to aggregate upon collision. This probability of aggregation is one in the DLCA and close to zero in the RLCA process. We show how to study the probability of aggregation from static micrographs on the example of a silica nanoparticle gel at 9 wt%. The analysis includes common summary functions from spatial statistics, namely the empty space function and Ripley's K-function, as well as two newly developed summary functions for cluster analysis based on graph theory. One of the new cluster analysis functions is related to the clustering coefficient in communication networks and the other to the size of a cluster. All four topological summary statistics are used to quantitatively compare in plots and in a least-square approach experimental data to cluster aggregation simulations with decreasing probabilities of aggregation. We study scanning transmission electron micrographs and utilize the intensity - mass thickness relation present in such images to create comparable micrographs from three-dimensional simulations. Finally, a characterization of colloidal silica aggregates and simulated structures is obtained, which allows for an evaluation of the cluster aggregation process for different aggregation scenarios. As a result, we find that the RLCA process fits the experimental data better than the DLCA process.
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| 4. |
- Koeck, P. J. B.
(författare)
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Improved Zernike-type phase contrast for transmission electron microscopy
- 2015
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 259:1, s. 74-78
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Tidskriftsartikel (refereegranskat)abstract
- Zernike phase contrast has been recognized as a means of recording high-resolution images with high contrast using a transmission electron microscope. This imaging mode can be used to image typical phase objects such as unstained biological molecules or cryosections of biological tissue. According to the original proposal discussed in Danev and Nagayama (2001) and references therein, the Zernike phase plate applies a phase shift of /2 to all scattered electron beams outside a given scattering angle and an image is recorded at Gaussian focus or slight underfocus (below Scherzer defocus). Alternatively, a phase shift of -/2 is applied to the central beam using the Boersch phase plate. The resulting image will have an almost perfect contrast transfer function (close to 1) from a given lowest spatial frequency up to a maximum resolution determined by the wave length, the amount of defocus and the spherical aberration of the microscope. In this paper, I present theory and simulations showing that this maximum spatial frequency can be increased considerably without loss of contrast by using a Zernike or Boersch phase plate that leads to a phase shift between scattered and unscattered electrons of only /4, and recording images at Scherzer defocus. The maximum resolution can be improved even more by imaging at extended Scherzer defocus, though at the cost of contrast loss at lower spatial frequencies. Lay description Zernike phase contrast has been recognized as a means of recording high-resolution images with high contrast using a transmission electron microscope. This imaging mode can be used to image specimens such as unstained biological molecules or sections of biological tissue. According to the original proposal, the Zernike phase plate applies a phase shift of /2 to all scattered electron beams outside a given scattering angle and an image is recorded at or close to focus. The resulting image will be an almost perfect representation of the specimen up to a maximum resolution determined by the energy of the electrons and certain optical parameters of the microscope. In this paper, I present theory and simulations showing that this maximum resolution can be increased considerably without loss of contrast by using a Zernike phase plate that leads to a phase shift between scattered and unscattered electrons of only /4, and recording images somewhat out of focus.
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| 5. |
- Koeck, P. J. B., et al.
(författare)
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Limitations of the linear and the projection approximations in three-dimensional transmission electron microscopy of fully hydrated proteins
- 2015
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 259:3, s. 197-209
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Tidskriftsartikel (refereegranskat)abstract
- We establish expressions for the linear and quadratic terms in the series expansion of the phase and the phase and amplitude object description of imaging thin specimens by transmission electron microscopy. Based on these expressions we simulate the corresponding contributions to images of unstained protein complexes of varying thickness and arrive at an estimate for how much each term contributes to the contrast of the image. From this we can estimate a maximum specimen thickness for which the weak phase and the weak amplitude and phase object approximation (and therefore linear imaging) is still reasonably accurate. When discussing thick specimens it is also necessary to consider limitations due to describing the image as a filtered projection of the specimen, since the different layers of the specimen are not imaged with the same defocus value. We therefore compared simulations based on the projection approximation with the more accurate multislice model of image formation. However, we find that the errors due to nonlinear image contributions are greater than those due to the defocus gradient for the defocus values chosen for the simulations. Finally, we study how the discussed nonlinear image contributions and the defocus gradient affect the quality of three-dimensional reconstructions. We find that three-dimensional reconstructions reach high resolution when at the same time exhibiting localized systematic structural errors. Non-Technical Abstract Cryo transmission electron microscopy and three-dimensional reconstruction can be used to determine a three-dimensional model of a protein molecule. In the mathematical methods used for three-dimensional reconstruction assumptions are made about a linear relationship between the images recorded in the electron microscope and the objects being imaged. In this paper we investigate with computer simulations at what specimen thickness these assumptions start breaking down and what sort of errors can be expected in the three-dimensional reconstructions when the assumptions are not valid anymore.
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| 6. |
- Longfils, Marco, 1990, et al.
(författare)
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Single particle raster image analysis of diffusion
- 2017
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 266:1, s. 3-14
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Tidskriftsartikel (refereegranskat)abstract
- As a complement to the standard RICS method of analysing Raster Image Correlation Spectroscopy images with estimation of the image correlation function, we introduce the method SPRIA, Single Particle Raster Image Analysis. Here, we start by identifying individual particles and estimate the diffusion coefficient for each particle by a maximum likelihood method. Averaging over the particles gives a diffusion coefficient estimate for the whole image. In examples both with simulated and experimental data, we show that the new method gives accurate estimates. It also gives directly standard error estimates. The method should be possible to extend to study heterogeneous materials and systems of particles with varying diffusion coefficient, as demonstrated in a simple simulation example. A requirement for applying the SPRIA method is that the particle concentration is low enough so that we can identify the individual particles. We also describe a bootstrap method for estimating the standard error of standard RICS.
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| 7. |
- Longfils, Marco, 1990, et al.
(författare)
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Single particle raster image analysis of diffusion for particle mixtures
- 2018
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 269:3, s. 269-281
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Tidskriftsartikel (refereegranskat)abstract
- Recently we complemented the raster image correlation spectroscopy (RICS) method of analysing raster images via estimation of the image correlation function with the method single particle raster image analysis (SPRIA). In SPRIA, individual particles are identified and the diffusion coefficient of each particle is estimated by a maximum likelihood method. In this paper, we extend the SPRIA method to analyse mixtures of particles with a finite set of diffusion coefficients in a homogeneous medium. In examples with simulated and experimental data with two and three different diffusion coefficients, we show that SPRIA gives accurate estimates of the diffusion coefficients and their proportions. A simple technique for finding the number of different diffusion coefficients is also suggested. Further, we study the use of RICS for mixtures with two different diffusion coefficents and investigate, by plotting level curves of the correlation function, how large the quotient between diffusion coefficients needs to be in order to allow discrimination between models with one and two diffusion coefficients. We also describe a minor correction (compared to published papers) of the RICS autocorrelation function. Lay description Diffusion is a key mass transport mechanism for small particles. Efficient methods for estimating diffusion coefficients are crucial for analysis of microstructures, for example in soft biomaterials. The sample of interest may consist of a mixture of particles with different diffusion coefficients. Here, we extend a method called Single Particle Raster Image Analysis (SPRIA) to account for particle mixtures and estimation of the diffusion coefficients of the mixture components. SPRIA combines elements of classical single particle tracking methods with utilizing the raster scan with which images obtained by using a confocal laser scanning microscope. In particular, single particles are identified and their motion estimated by following their center of mass. Thus, an estimate of the diffusion coefficient will be obtained for each particle. Then, we analyse the distribution of the estimated diffusion coefficients of the population of particles, which allows us to extract information about the diffusion coefficients of the underlying components in the mixture. On both simulated and experimental data with mixtures consisting of two and three components with different diffusion coefficients, SPRIA provides accurate estimates and, with a simple criterion, the correct number of mixture components is selected in most cases.
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| 8. |
- Peña Fernández, Marta, et al.
(författare)
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Optimization of digital volume correlation computation in SR-microCT images of trabecular bone and bone-biomaterial systems.
- 2018
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 272:3, s. 213-228
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Tidskriftsartikel (refereegranskat)abstract
- A micromechanical characterization of biomaterials for bone tissue engineering is essential to understand the quality of the newly regenerated bone, enabling the improvement of tissue regeneration strategies. A combination of microcomputed tomography in conjunction with in situ mechanical testing and digital volume correlation (DVC) has become a powerful technique to investigate the internal deformation of bone structure at a range of dimensional scales. However, in order to obtain accurate three-dimensional strain measurement at tissue level, high-resolution images must be acquired, and displacement/strain measurement uncertainties evaluated. The aim of this study was to optimize imaging parameters, image postprocessing and DVC settings to enhance computation based on 'zero-strain' repeated high-resolution synchrotron microCT scans of trabecular bone and bone-biomaterial systems. Low exposures to SR X-ray radiation were required to minimize irradiation-induced tissue damage, resulting in the need of advanced three-dimensional filters on the reconstructed images to reduce DVC-measured strain errors. Furthermore, the computation of strain values only in the hard phase (i.e. bone, biomaterial) allowed the exclusion of large artefacts localized in the bone marrow. This study demonstrated the suitability of a local DVC approach based on synchrotron microCT images to investigate the micromechanics of trabecular bone and bone-biomaterial composites at tissue level with a standard deviation of the errors in the region of 100 microstrain after a thorough optimization of DVC computation. LAY DESCRIPTION: Understanding the quality of newly regenerated bone after implantation of novel biomaterials is essential to improve bone tissue engineering strategies and formulation of biomaterials. The relationship between microstructure and mechanics of bone has been previously addressed combining microcomputed tomography with in situ mechanical testing. The addition of an image-based experimental technique such as digital volume correlation (DVC) allows to characterize the deformation of materials in a three-dimensional manner. However, in order to obtain accurate information at the micro-scale, high-resolution images, obtained for example by using synchrotron radiation microcomputed tomography, as well as optimization of the DVC computation are needed. This study presents the effect of different imaging parameters, image postprocessing and DVC settings for as accurate investigation of trabecular bone structure and bone-biomaterial interfaces. The results showed that when appropriate image postprocessing and DVC settings are used DVC computation results in very low strain errors. This is of vital importance for a correct understanding of the deformation in bone-biomaterial systems and the ability of such biomaterials in producing new bone comparable with the native tissue they are meant to replace.
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| 9. |
- Pingel, Torben, 1984, et al.
(författare)
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Revealing local variations in nanoparticle size distributions in supported catalysts: a generic TEM specimen preparation method
- 2015
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Ingår i: Journal of Microscopy. - : Wiley. - 1365-2818 .- 0022-2720. ; 260:2, s. 125-132
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Tidskriftsartikel (refereegranskat)abstract
- The specimen preparation method is crucial for how much information can be gained from transmission electron microscopy (TEM) studies of supported nanoparticle catalysts. The aim of this work is to develop a method that allows for observation of size and location of nanoparticles deposited on a porous oxide support material. A bimetallic Pt-Pd/Al2O3 catalyst in powder form was embedded in acrylic resin and lift-out specimens were extracted using combined focused ion beam/scanning electron microscopy (FIB/SEM). These specimens allow for a cross-section view across individual oxide support particles, including the unaltered near surface region of these particles. A site-dependent size distribution of Pt-Pd nanoparticles was revealed along the radial direction of the support particles by scanning transmission electron microscopy (STEM) imaging. The developed specimen preparation method enables obtaining information about the spatial distribution of nanoparticles in complex support structures which commonly is a challenge in heterogeneous catalysis. Lay Description Catalysis is important in our everyday lives, whether it is for the production of chemicals and food or for cleaning the exhaust gas of cars, ships and power plants. Therefore it is crucial to get a better understanding of the structure and properties of the catalysts involved, which often are in the form of nanoparticles. Electron microscopy has proven to be a powerful tool to investigate these nanoparticles, and especially transmission electron microscopy (TEM) has been used to investigate the smallest structures, down to single atoms. Although the TEM is very capable of imaging even the smallest structures, the specimens in question need to be very thin, of the order 100 nanometres, which can make the specimen preparation demanding, since the nanoparticles are mostly supported on much larger porous alumina particles. We have developed a new specimen preparation method using a focused ion beam, which allows obtaining TEM specimens of these catalysts in a very controlled manner, compared to previous procedures which involved crushing the catalyst powder in a mortar to obtain small pieces. With these specimens, we could in the TEM analysis investigate the spatial distribution of nanoparticles within the alumina support structure, and we observed a different nanoparticle size distribution for different parts of the support, namely the outer edge and the interior. This was never before observed using specimens obtained from the conventional crushing method.
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| 10. |
- Röding, Magnus, 1984, et al.
(författare)
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Massively parallel approximate Bayesian computation for estimating nanoparticle diffusion coefficients, sizes and concentrations using confocal laser scanning microscopy
- 2018
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Ingår i: Journal of Microscopy. - : Wiley. - 1365-2818 .- 0022-2720. ; 271:2, s. 174-182
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Tidskriftsartikel (refereegranskat)abstract
- We implement a massively parallel population Monte Carlo approximate Bayesian computation (PMC‐ABC) method for estimating diffusion coefficients, sizes and concentrations of diffusing nanoparticles in liquid suspension using confocal laser scanning microscopy and particle tracking. The method is based on the joint probability distribution of diffusion coefficients and the time spent by a particle inside a detection region where particles are tracked. We present freely available central processing unit (CPU) and graphics processing unit (GPU) versions of the analysis software, and we apply the method to characterize mono‐ and bidisperse samples of fluorescent polystyrene beads.
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