William Heeschen

A quantitative image analysis method for the determination of cocontinuity in polymer blends

Abstract A new morphological parameter, ‘CoContinuity’, has been developed and implemented for quantitative measurement of morphology in cocontinuous blends of polymers. The basis of the CoContinuity is the extent to which the phases of a polymer blend mutually surround each other. A secondary parameter, ‘CoContinuity Balance’, is also presented to describe quantitatively the relative contribution of each phase to the CoContinuity. Both of these functions are dimensionless and scale-invariant, thus allowing objective comparisons of dissimilar systems. An example is given where the functions faithfully describe the evolution of a polycarbonate/poly(styrene- co -acrylonitrile) (PC/SAN) blend of varying phase ratio as the system progresses from discrete domains of the SAN phase in a matrix of PC, through a cocontinuous morphology of SAN and PC, and finally ends up as a mixture of discrete domains of PC in a matrix of SAN.

Three-dimensional characterization of pigment dispersion in dried paint films using focused ion beam-scanning electron microscopy.

The combination of integrated focused ion beam-scanning electron microscope (FIB-SEM) serial sectioning and imaging techniques with image analysis provided quantitative characterization of three-dimensional (3D) pigment dispersion in dried paint films. The focused ion beam in a FIB-SEM dual beam system enables great control in slicing paints, and the sectioning process can be synchronized with SEM imaging providing high quality serial cross-section images for 3D reconstruction. Application of Euclidean distance map and ultimate eroded points image analysis methods can provide quantitative characterization of 3D particle distribution. It is concluded that 3D measurement of binder distribution in paints is effective to characterize the order of pigment dispersion in dried paint films.

Feature Article: Tapping Mode Atomic Force Microscopy of Surface Morphology of Polymer Blends

Application of tapping mode atomic force microscopy (TMAFM) phase imaging techniques to characterize the morphology of polymeric blends is reviewed. The basic principle of TMAFM phase imaging capability is introduced. A summary of phase contrast applications for various polymeric blend systems such as rubber-rubber, plastic-rubber, and plastic-plastic blends is extensively discussed. The review shows that AFM is a very useful technique in probing micro-phase dispersion, compatibility between blend components, and local mechanical properties in polymeric blend systems.

Wet film dimensions of capsule walls during dip coating.

ABSTRACT The objective of the present study was to improve our understanding of the relationships between wet film dimensions, dip sequences, and the physico-chemical properties of the dip solutions as they pertain to the dip-coating process for the manufacture of hard-shell capsules. To achieve this objective, it was necessary to develop a technique to quantify wet film dimensions. A further objective was to develop a predictive model for dip coating with hydroxypropyl methylcellulose (HPMC) solutions. It is hoped that the information contained in this article on significant variables controlling wet film thickness will help manufacturers develop consistent manufacturing controls and processes.

Analysis of x-ray tomography data of an extruded low density styrenic foam: an image analysis study

Extruded styrenic foams are low density foams that are widely used for thermal insulation. It is difficult to precisely characterize the structure of the cells in low density foams by traditional cross-section viewing due to the frailty of the walls of the cells. X-ray computed tomography (CT) is a non-destructive, three dimensional structure characterization technique that has great potential for structure characterization of styrenic foams. Unfortunately the intrinsic artifacts of the data and the artifacts generated during image reconstruction are often comparable in size and shape to the thin walls of the foam, making robust and reliable analysis of cell sizes challenging. We explored three different image processing methods to clean up artifacts in the reconstructed images, thus allowing quantitative three dimensional determination of cell size in a low density styrenic foam. Three image processing approaches - an intensity based approach, an intensity variance based approach, and a machine learning based approach - are explored in this study, and the machine learning image feature classification method was shown to be the best. Individual cells are segmented within the images after the images were cleaned up using the three different methods and the cell sizes are measured and compared in the study. Although the collected data with the image analysis methods together did not yield enough measurements for a good statistic of the measurement of cell sizes, the problem can be resolved by measuring multiple samples or increasing imaging field of view.

Silver Nanowire Diameter and Yield Characterization by High-Throughput SEM and Image Analysis

An interconnected random network of nano-sized metal wires can be used as a Transparent Conductive Material [1]. TCMs are widely used in electronic devices from TVs and solar panels to touch screen applications such as tablets and phones. Potential advantages of such TCMs over incumbent indium tin oxide are lower sheet resistance at equal or better optical properties, low temperature deposition on polymer or other flexible substrates, cost advantages from capital expenditure reductions, and high throughput when applied by roll-to-roll coating. A scalable hydrothermal synthesis for silver nanowires (AgNW) was developed [2,3] necessitating the efficient and statistically rigorous characterization of wire dimensions and wire-to-particle yield in order to track synthesis and purification developments.

Image Texture Analysis and Application to Acicular Mullite Porous Ceramic Microstructure

Acicular mullite porous ceramic [1,2] can display a range of microstructures, impacted by elemental formulation, raw materials, and processing conditions. The microstructure in turn impacts performance metrics such as strength, modulus and back pressure for filtration applications. During research and development and later during scale-up and production, assessment of microstructure was done in a completely subjective manner; a small group of experienced individuals assessed SEM images. The goal of the project described here was to develop an objective way to quantify aspects of this microstructure. The approach was to apply computational image analysis to SEM images. A set of 32 samples that displayed a range of microstructures were used (Fig. 1).

Evaluation of Methods for Quantification of Transmission Electron Microscopy (TEM) Dispersions

Transmission electron microscopy (TEM) micrographs are routinely used to evaluate the dispersion of insoluble additives in polymeric systems. For routine TEM analysis, many analysts have relied on a visual analysis of the TEM micrographs to estimate the quality of the additive dispersion. When comparing large numbers of TEM micrographs, the ability to determine or estimate the dispersion quality is often difficult. The objective of this study was to develop a method to quantify dispersions observed in TEM micrographs that both enables a numerical “ranking” to be assigned to individual dispersions as well as enables tabulation of a multitude of images acquired over time. Several methods were reviewed and applied to a set of TEM dispersion images acquired of an insoluble additive in polystyrene.