Study on the Possibility of Statistical Particle Morphology Evaluation of Inorganic Fillers by Fully Automated Particle Image Analysis Method

This is the presentation manuscript for the 35th Annual Meeting of the Society of Plastic Molding Processing, which was recently held.

Authors: Takehiro Kajiwara, Hiroyuki Hamada, Daitoku Sasakura, Malvern Panalytical Business Unit, Spectris Ltd.

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1. Introduction

Fillers in plastics are particle or powdery substances added for the purpose of improving functionality or reducing costs. The functionalities exhibited by adding fillers are varied and include mechanical strength, thermal conductivity, heat resistance, conductivity, and electromagnetic wave shielding. The nature of these functionalities depends not only on the type of material used as a filler but also on the particle size and shape. Generally, the smaller the particle size, the larger the specific surface area, making it easier to exert the effect of the filler; however, it is said that handling becomes more challenging from the standpoint of dispersibility. When focusing on particle shape, fillers added to improve mechanical strength are often needle-like or plate-like, with smaller aspect ratios (short diameter axis / long diameter axis, where a smaller value indicates a more elongated shape) being more effective. Thus, evaluating and understanding particle size and shape of fillers is important for exerting the desired function.¹⁾

The Automated Particle Image Analysis (APIA) method is useful as a comprehensive evaluation method for particle morphology information. This method complies with ISO13322 and enables simultaneous analysis of particle size and shape. Traditionally, quantification of particle shape has relied on labor-intensive methods using microscopy, posing challenges in obtaining large volumes of particle information and causing errors or interpretation discrepancies dependent on the individual. These challenges are overcome by the APIA method. Specifically, by comprehensively and automatically analyzing particle morphology information in real-time, it becomes easy to acquire information on thousands to tens of thousands of particles and to compare and extract statistically significant information. This report explores the possibility of evaluating the particle morphology of fillers significant for plastic functionality using the APIA method.

2. Experimental Method

Calcium carbonate, commonly used as a filler added to plastics, was selected as the sample for examination, and two types of needle-shaped particles were evaluated. The Morphologi 4 (Malvern Panalytical) was used as the device based on the APIA method for particle morphology evaluation. The samples were dispersed on a glass plate using the device’s attached dry dispersion unit. Imaging was conducted using transmitted light and a 10x objective lens. After imaging, primary particles were selected based on shape, and analysis of more than 15,000 particles was conducted.

3. Results and Discussion

Particle Size Evaluation
The volume-based particle size distribution by circle equivalent diameter is shown in Fig.1, and the number-based particle size distribution in Fig.2. Comparing samples A and B, the volume-based particle size distribution showed that sample B was slightly smaller, with Dv50 being A: 15.04 μm, B: 11.04 μm. On the other hand, the number-based particle size distribution showed that sample B had less fine powder below 2 μm compared to sample A, with A: 17%, B: 6%. From these results, it is inferred that when adding samples A and B as fillers in plastics, sample B is easier to exert filler effects and easier to handle in terms of particle size.

Fig.1 Volume based Particle size distribution.

Fig.2 Number based Particle size distribution

Particle Shape Evaluation
A 2D scattergram with the volume-based particle size distribution by circle equivalent diameter on the x-axis and aspect ratio on the y-axis is shown in Fig.3. This result indicated that even with the same particle size, particles with different shapes were included.

Fig.3 2D Scattergram.

For each of samples A and B, particles larger than Dv10 (A: 8.02 μm, B: 6.40 μm) were extracted from the volume-based particle size distribution, and the aspect ratio distribution is shown in Fig.4. Comparing samples A and B, the aspect ratio for sample A was smaller, with averages A: 0.437, B: 0.512. This result indicated that more elongated particles are included in sample A. When adding samples A and B respectively to plastics as fillers to improve mechanical strength, sample A is inferred to exert a more effective impact from the perspective of particle shape.

Fig.4 Aspect ratio distribution.

As representative images of samples A and B, images near the mode of the volume-based particle size distribution and aspect ratio distribution are shown in Fig.5.

Fig.5 Image of CaCo₃

4. Conclusion

This report attempted to evaluate the particle morphology of calcium carbonate, widely used as a filler added to plastics, using the APIA method. As a result, comprehensive evaluation of particle morphology information such as particle size and shape was possible.

References: 1) J.M.Adams: Clay Minerals, 28, 509-530 (1993)

Source: The 35th Annual Meeting of the Society of Plastic Molding Processing, Manuscripts

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