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Automated Image Analysis of Polymer Beads and Size Distribution Ann Jasmine Jose,† Lu Shin Wong,‡ James Merrington,‡ and Mark Bradley*,‡ Asahi Kasei Satellite Laboratory, School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom, and School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom
Size analysis of polymer beads is currently carried out using instruments such as Coulter counters. Here, image analysis software was used to analyze digital pictures of polymer beads and determine size profiles. Analysis was automated to provide high throughput scanning of images, and results compared favorably with traditional laser diffraction measurements. The technique also enabled the roundness of the beads to be measured in order to assess the bead quality after polymerization and physical manipulation. This method enabled automated and high throughput characterization of beads. Introduction
Experimental Section
Resin beads for solid-phase synthesis are usually synthesized by suspension polymerization,1 a method that produces polymer beads with a broad distribution of sizes, typically 25-500 µm, although other methods such as emulsion2,3 and dispersion4 polymerization can be used to give a much more homogeneous distribution of beads. The size characteristics of a batch of beads are an important determinant of the beads’ properties and their potential application. Thus, in solid-phase synthesis, the size of a bead affects its reaction kinetics,5,6 while in chromatography, it affects the separation characteristics of the column.7,8 A review published in 1995 discusses many techniques that have been developed for particle size analysis,9 although not all are applied in the area of polymer particle analysis. Typical physical methods employed include sieving, sedimentation, and centrifugation, although measurements on polymer bead particles are carried out using radiation scattering techniques such as laser diffraction spectroscopy (LDS).10,11 However, these methods may require the use of expensive equipment, most of which only cover a limited size range and are not capable of providing any additional information regarding the shape or condition of the beads. Moreover, analyses with these traditional techniques are conducted on a suspension of the particles in a range of solvents, from water to hexane, and the carrier fluid often interacts with the bead, introducing an inherent modification of the size measurements. In this study, digital images of beads from a variety of sources were analyzed using versatile image processing software to measure the size profile of polymer beads. The approach of using image analysis is often employed in the field of biology and medicine for the microscopicinvestigationofcellsandtissuestructures.12-15 It has also been applied in metallurgy and materials science for the study of the microstructures of various materials.9,16 However, it has not been previously used to investigate and analyze resin beads.
Equipment and Materials. A Leica Leitz DM 1L inverted configuration microscope, coupled to a Nikon single lens reflex D1 digital camera, set to a resolution of 2.6 Mpixels (2000 × 1300 pixels), was used to acquire the optical transmittance and fluorescence microscopy photos in JPEG format. The scanning electron microscopy (SEM) images, in TIFF format, were obtained on a Philips XL 30 scanning electron microscope under a high vacuum. Typically, a thin layer of a well-mixed representative portion of the sample was spread onto a flat surface (e.g., glass slide or an SEM target stub) prior to analysis and was coated with a layer of gold to a depth of approximately 20 nm under vacuum prior to observation. Laser scattering measurements were made with a Coulter LS 230 particle size analyzer. Cross-linked hydroxymethyl functionalized polystyreneco-divinylbenzene (PS-DVB) resin beads of 2% were obtained from Novabiochem. Synthesis of 2-Hydroxyethyl Acrylate (HEA) Polymer Particles. A mixture of HEA (1.96 g) and cross-linker ethylene glycol dimethylacrylate (1.1 g) with benzoyl peroxide (0.1 g) was added to toluene (3 mL) and stirred to give a homogeneous organic phase. Poly(vinyl acetate) [0.6% (w/w)] and sodium dodecyl sulfate [0.25% (w/w)] were dissolved in water (60 mL). The organic phase was emulsified with the aqueous phase using an ultrasonic disrupter. The second and third portions of the emulsions were added after 1-h intervals in the same way. The mixture was stirred until the emulsified organic phase formed stable spherical droplets. The temperature was then increased to 70 °C and polymerization carried out for 15 h. The resulting beads were purified by centrifugation (4000 rpm, 15 min), washed several times with water (3 × 50 mL) and methanol (3 × 50 mL), and dried in vacuo. Image Acquisition and Analysis. All images were taken of the dry beads, with care taken to minimize aggregation. Images of the dry beads were also obtained by SEM at 50× and 500× magnification. For PS-DVB beads, optical microscopy images of dry beads were obtained at 40× and 100× magnification. In all cases, the intention was to obtain high-quality digital images with high contrast and resolution. The scale (in micrometers) of the images was calibrated using a microscope graticule for each magnification.
* To whom correspondence should be addressed. Tel.: +44 (0)23 80593466. Fax: +44 (0)23 80596766. E-mail: mb14@ soton.ac.uk. † Asahi Kasei Satellite Laboratory. ‡ School of Chemistry.
10.1021/ie0495123 CCC: $30.25 © 2005 American Chemical Society Published on Web 09/17/2004
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Figure 1. Image analysis of dry beads: SEM (left) and optical (right) microscopy. Beads identified by Image-Pro Plus are circled in red. Table 1. Comparison of Size Characteristics of PS-DVB Using Various Techniquesa optical microscopy (40× mag.)
mean size (µm) SD (µm) a
transmittance (n ) 380)
fluorescence (n ) 419)
SEM (50× mag.; n ) 75)
LDS (in water)
manufacturer’s specifications
114.7 18.5
117.6 20.1
119.1 20.7
115.2 23.7
75-150 ND
n ) number of beads measured. ND ) not determined.
Table 2. Resolution and Degree of Error of Various Image Acquisition Techniques error a b c d e f
image acquisition technique
image resolution (pixels)
image magnification
scale (pixels/µm)
pixels
µm
optical, transmittance optical, transmittance optical, fluorescence optical, fluorescence SEM SEM
2000 × 1600 2000 × 1600 2000 × 1600 2000 × 1600 712 × 484 712 × 484
40× 100× 40× 100× 50× 500×
1.19 2.97 1.19 2.97 0.29 2.88
(4 (4 (2 (2 (2 (2
(3.4 (1.4 (1.7 (0.7 (6.9 (0.7
The picture files were then transferred to Image-Pro Plus 4.5 (Media Cybernetics, Silver Spring, MD) for processing. The software was instructed to count the number of “objects” in the image, in this case the number of particles. The software identified objects within the image by the difference in pixel intensity termed “thresholding”. The software was allowed to automatically determine the optimum intensity range to be used by selecting the option “Automatic Bright Objects”, which identified the lighter colored particles on a dark background. The identified particles were then electronically filtered to exclude any particles of an area < 100 µm2 for PS-DVB or < 1 µm2 for pHEA. A second filter of roundness was applied to exclude particles of a roundness index greater than 1.2. The roundness index used by the software is described as
roundness index ) (perimeter of the object)2/(4π × area of the object) The selected beads were counted and the area and diameter were calculated by the Image-Pro Plus software, as were the mean size values. This series of graphical manipulations was recorded as a “macro”, which was when executed, processing each the images automatically. The data were then exported to Excel and Origin Pro 6.1 (OriginLab, Northampton, MA) for the plotting of size distribution histograms with the calculated best-fit distributions. Results and Discussion Particle Size Analysis. Initially, commercially available PS-DVB beads, used in solid-phase organic syn-
thesis, were investigated. Images of these beads were then processed using image analysis software ImagePro Plus, which identified and located individual resin beads while excluding aggregates and debris (Figure 1). Each image was taken from independent samples of each polymer to give a very reliable representation, and by pooling a large number of these independent images, good statistical significance was achieved. Information regarding the size characteristics of the beads were then extracted automatically using the “macro” program to provide statistically significant data sets. The results were found to be in good agreement with those obtained by LDS (Table 1). It was noted that the particle sizes were more accurately described by a skewed Extreme distribution (sometimes also known as the Fisher-Tippett distribution or log-Weibull distribution)17 rather than a symmetrical Gaussian distribution (Figure 2). For transmittance microscopy, a Gaussian fit gave a R2 value of 0.929, while the Extreme fit gave a value of 0.947. From the measurements of the beads, the perimeter of the particles was automatically identified by the software based on pixel intensity values within the border region (Figure 3). The degree of error in this method of analysis was estimated by examining the possible variation in this region. In Figure 3, the error is (4 pixels on either side of the calculated perimeter, thus allowing the error for the image acquisition technique to be calculated (Table 2). Higher resolution and higher magnification provided images with much more clearly defined borders and a lower level of error. Although the SEM was able to
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Figure 2. Distribution graphs comparing the image analysis of PS-DVB beads against LDS measurements. TEM at 40× magnification (left) and SEM at 50× magnification (right).
Figure 3. Automatic thresholding of microscopy image (40× magnification) of a resin bead: (a) image background; (b) bead interior; (c) calculated perimeter; (d) green markers indicate the extremes of the border region. Table 3. Comparison of the Size Characteristics of pHEA Beads Using SEM and LDSa mean size (µm) SD a
SEM (500× mag.; n ) 295)
LDS
8.3 1.9
12.3 6.0
n ) number of beads measured.
provide images with strong contrast between the background and bead, the image resolution was poor. At 50× magnification (Table 2, entry e), this resulted in a higher degree of error compared with the optical images (Table 2, entries a and b). In general, however, the degree of error was lower at higher magnifications, and the SEM images (Table 2, entry f) produced the smallest error. This analytical technique was then applied to much smaller (∼10 µm) pHEA beads. SEM images of these beads were analyzed (Table 3 and Figure 4). Again it was observed that an Extreme distribution was a better fit to a Gaussian distribution in describing these particles, with an R2 value of 0.919 and 0.907, respectively. Interestingly, image analysis suggested a much narrower size distribution compared to LDS measurements. This is believed to be due to the presence of particle aggregates, which were included by LDS measurements but excluded by the image analysis software when identifying beads. To exclude the possibility of particle concentration affecting the LDS results, pHEA beads analysis at very low, ideal, and high concentrations in comparison gave similar results (Figure 4) and suggests that the difference observed between image analysis and LDS could be the result of actual particle aggregates or because of the nonrobust mathematical algorithms employed in the instrument software18 rather than an artifact of analyzing concentrated particle suspensions.
Figure 4. Distribution analysis of pHEA beads by light scattering measurements compared to SEM image analysis. Table 4. Size and Roundness Characteristics of Macroporous PS-DVB Beadsa
mean roundness index percentage of beads with a roundness index e 1.2 (%) a
unaltered beads (n ) 51)
stirred beads (n ) 64)
1.17 85
1.22 61
n ) number of beads measured.
Roundness Index Analysis. The software’s roundness index filter could also be used to segregate the beads in order to determine the degree of nonuniformity of bead samples. To investigate the degree of damage caused by prolonged stirring to polymer beads, macroporous PS-DVB beads were stirred overnight and compared to unaltered beads. A roundness index value of 1.2 was applied because it was found to be optimal for separating well-formed round beads from damaged beads. Prolonged stirring damaged the beads with more cracked or broken beads observed in the images, and the roundness index increased by 0.05, while the percentage of beads in the sample with an index of less than 1.2 dropped by 24% (Table 4), suggesting that this is a powerful method for rapidly assessing the degree of particle breakage following application. Conclusions It has been demonstrated that it is possible to determine the size distribution of beads using auto-
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mated image analysis processing, in a rapid and reliable manner, and the “roundness” of a population of beads could also be assessed. To further improve accuracy, images of higher resolution, as well as higher microscopic magnification, could be used. Digital cameras with larger pixel arrays and larger sample sizes would reduce any further error. This method has key advantages over existing techniques; namely, it looks at only single isolated beads rather than aggregates, while beads in any form can be examined with or without any suspending solvent. Additionally, image analysis is applicable to particles of any size, provided good resolution images can be obtained for the samples of interest. In the case of particles in the 100-nm range, SEM or transmission electron microscopy (TEM) images would be suitable for analysis. Acknowledgment The authors thank Asahi-KASEI and EPSRC for funding. Literature Cited (1) Munzer, M.; Trommsdorff, E. In Polymerisation Processes; Schildknecht, C. E., Ed.; Wiley: New York, 1977; p 106. (2) Pichot, C. Microspheres, Microcapsules and Liposomes; Wiley: New York, 1999; p 125. (3) Gardon, J. L. In Polymerisation Processes; Schildknecht, C. E., Ed.; Wiley: New York, 1977; p 143. (4) Sandler, S. R.; Karo, W. Polymer Synthesis and Characterisation; Academic Press: London, 1998; p 29. (5) Rapp, W. Resins. Methods Organic Chemistry (HoubenWeyl), 4th ed.; Supplemental Series E22a; Thieme Publishers: New York, 2002; p 672. (6) Groth, T.; Grøtli, M.; Meldal, M. Diffusion of reagents in macrobeads. J. Comb. Chem. 2001, 3, 461.
(7) Mikesˇ, O. In Liquid Column Chromatography: A Survey of Modern Techniques and Applications; Deyl, Z., Macek, K., Jana´k, J., Eds.; Elsevier: Amsterdam, The Netherlands, 1975; p 69. (8) Vespalec, R.; Krejcˇ´ı, M. In Liquid Column Chromatography: A Survey of Modern Techniques and Applications; Deyl, Z., Macek, K., Jana´k, J., Eds.; Elsevier: Amsterdam, The Netherlands, 1975; p 283. (9) Barth, H. G.; Flippen, R. B. Particle size analysis. Anal. Chem. 1995, 67, 257R. (10) Allen, T. Particle size measurement, 4th ed.; Chapman and Hall: London, 1990. (11) Rawle, A. Basic principles of particle size analysis. Surf. Coat. Int., Part A 2003, 86 (A2), 58. (12) Furtado, A.; Henry, R. Measurement of green fluorescent protein concentration in single cells by image analysis. Anal. Biochem. 2002, 310, 84. (13) Wexler, E. J.; Peters, E. E.; Gonzales, A.; Gonzales, M. L.; Slee, A. M.; Kerr, J. S. An objective procedure for ischemic area evaluation of the stroke intraluminal thread model in the mouse and rat. J. Neurosci. Methods 2002, 113, 51. (14) Carai, A.; Diaz, G.; Santa Cruz, R.; Santa Cruz, G. Computerized quantitative color analysis for histological study of pulmonary fibrosis. Anticancer Res. 2002, 22, 3889. (15) Johnson, I.; Harman, M.; Forrow, D.; Norris, M. An assessment of the feasibility of using image analysis in the oyster embryo-larval development test. Environ. Toxicol. 2001, 16, 68. (16) Tansel, B.; Nagarajan, P. Water Environment Federation and Purdue University Industrial Wastes Technical Conference, St. Louis, MO, 2002. (17) Johnson, N. L.; Kotz, S.; Balakrishnan, N. Continuous Univariate Distributions; John Wiley: New York, 1994; p 628. (18) Etzler, F. M. Polym. Mater. Sci. Eng. 2002, 87, 335.
Received for review June 6, 2004 Revised manuscript received July 23, 2004 Accepted July 27, 2004 IE0495123
