A Basic Guide to Particle Analysis-1

by Seungji Kim, Tuesday, 27th November 2012

A Basic Guide to Particle Characterization

Introduction
  The purpose of this guide is to provide basic education on key particle characterization techniques currently used in industrial and academic fields. It is intended for those seeking to broaden their knowledge of particle characterization, particles, or this field without prior knowledge of particle analysis theory or measurement. This guide is not only an easy reference to help determine the most suitable particle characterization technology for the reader’s needs, but also covers basic particle characterization introductions, theory, and measurements.
What is a Particle?
  At the most basic level, a particle can be defined as an individual subportion of material. For the purposes of this guide, we will limit the definition of particles to include solid particles, liquid droplets, or gas bubbles with physical dimensions ranging from smaller than 1 nanometer to several millimeters.

The most common types of materials composed of particles are as follows:

• Powders and granules (e.g., pigments, cement, pharmaceutical ingredients)
• Suspensions, emulsions, and slurries (e.g., vaccines, milk, mining mud)
• Aerosols and sprays (e.g., inhalers for asthma patients, crop protection sprays)
Why Measure Particle Characteristics?
 There are two main reasons why particle characterization is commonly used across industries.

1. Product Quality Control Improvements
With intensified global economic competition, improvements in product quality control bring real economic benefits such as:
• Adding higher premiums to products
• Reducing customer rejection rates and loss of orders
• Demonstrating compliance in regulated markets
2. Enhanced Understanding of Products, Ingredients, and Processes
In addition to product quality control, understanding how particle characteristics affect the product, ingredients, and processes can help:
• Improve product performance
• Adjust manufacturing and supply issues
• Maximize the efficiency of manufacturing processes
• Increase production volume or yield
• Stay ahead of the competition.
What Critical Particle Characteristics Should Be Measured?
  Alongside chemical composition, the properties of particulate materials are often influenced by the physical characteristics of the constituent particles. This can impact a wide range of material properties, such as reaction and dissolution rates, how easily components flow and mix, or compressibility and abrasion. From a production and development perspective, some of the most important physical characteristics to measure include:
• Particle size
• Particle shape
• Surface characteristics
• Mechanical properties
• Charge characteristics
• Microstructure

  Depending on the material of interest, some or all of these physical characteristics might be important and can even interrelate (e.g., surface area and particle size). For the purpose of this guide, we will focus intensively on the two most crucial and easy-to-measure characteristics – particle size and shape.
Particle Characteristics

Particle Size

  The most critical physical characteristic of particulate samples is particle size. Particle size measurements are routinely performed across a wide array of industries and can often be an essential parameter in the manufacture of many products. Particle size directly influences the following material properties:

• Reactivity or dissolution rate (e.g., catalysts, pill formulations)
• Stability in suspension (e.g., sediments, paints)
• Delivery efficiency (e.g., inhalers for asthma patients)
• Texture and feel (e.g., food ingredients)
• Appearance (e.g., powder coatings and inks)
• Flowability and handling (e.g., granules)
• Viscosity (e.g., nasal sprays)
• Packing density and porosity (e.g., ceramics)

  Measuring particle size and understanding how it affects products and processes can play a crucial role in the success of many manufacturing industries.

How to Define Particle Size?

  Particles are three-dimensional objects, and a one-dimensional metric such as radius or diameter does not fully describe a particle unless it is a perfect sphere (e.g., emulsions or bubbles).

  To simplify measurement processes, it is often convenient to define particle size using the concept of equivalent spheres. In such cases, particle size is defined as the diameter of an equivalent sphere having the same properties, such as volume or mass, as the actual particle. It is important to understand that different measurement techniques use different models of equivalent spheres and thus do not necessarily provide precisely the same results for particle diameter.


  The concept of equivalent spheres applies very well to regularly shaped particles. However, it may not always be suitable for irregularly shaped particles, such as needles or plates, where at least one dimension differs significantly from others.

 

 

   For the example of rod-shaped particles depicted above, a volume-equivalent sphere would have a particle diameter of 198μm, which would not be an accurate description in terms of physical dimensions. However, we can also define the same particle as a cylinder with a length of 360μm and a width of 120μm having the same volume. This approach allows for a more accurate description of particle size and better understanding, for instance, during processing or handling operations.

 

  Many particle size measurement techniques are based on the concept of simple one-dimensional equivalent measurements of spheres, which is often fully adequate for essential applications.

 

 

Particle Size Distribution

  If a sample intended for characterization is not in the form of a completely simple dispersion, that is, not all single particles have exactly the same dimensions, the sample will have a statistical distribution of particles of different sizes. It is usual to represent these distributions as frequency distribution curves or cumulative (undersize) distribution curves.

Weighted Distributions
Particle size distributions can be expressed in different ways concerning weighting of individual particles, and the method of weighting will depend on the measurement principle used.
Number Weighted Distribution
  A number weighted distribution is given in counting techniques such as image analysis, in which each particle is given the same weight regardless of size. This is most often used where knowing the absolute number of particles is important (e.g., foreign particle detection) or where high resolution on a per-particle basis is required.

Volume Weighted Distribution
  Static light scattering techniques such as laser diffraction provide a volume-weighted distribution. Here, the contribution of each particle in the distribution relates to its volume (the same as mass if the density is uniform), so the relative contribution will be proportional to the cube of its size. This means that the distribution represents the composition of the sample in terms of volume/mass and thus is highly valuable commercially with potential cost implications.

Intensity Weighted Distributions
  Dynamic light scattering techniques provide intensity-weighted distributions. In this distribution, the contribution of each particle relates to the intensity of light scattered by that particle.

  For example, when using the Rayleigh approximation, the relative contribution for very small particles will be proportional to the sixth power of their size. It’s important to be aware that very different particle size results may be obtained depending on the type of distribution being measured and recorded when comparing particle size data measured using different techniques.

    The example below shows this clearly for a sample composed of the same number of particles with diameters of 5nm and 50nm.

    In number-weighted distribution, the presence of the finer 5nm particles is emphasized, with the two types of particles given equal weight, whereas, in intensity-weighted distribution, the larger 50nm particles generate a signal a million times higher. The volume-weighted distribution is intermediate between the two.
 
   Examples of number, volume, and intensity-weighted particle size distributions for the same sample

    It’s possible to convert particle size data from one type of distribution to another, but specific assumptions need to be made about the shape and physical characteristics of the particles. For instance, a volume-weighted particle size distribution measured by image analysis should not be expected to necessarily agree exactly with one measured by laser diffraction.
Distribution Statistics
“There are three kinds of lies: lies, damned lies, and statistics.”-Twain, Disraeli

    To simplify the interpretation of particle size distribution data, a variety of statistical parameters can be calculated and recorded. The choice of the most appropriate statistical parameter for a given sample depends on how the data is to be used and what it is to be compared to. For example, if you wish to record the most common particle size within a sample, you might choose from the following parameters:

• Mean – The ‘average’ size of the population
• Median – The size below/above which lies 50% of the population
• Mode – The size with the highest frequency

   As often happens in many samples where the shape of the particle size distribution is skewed, these three values may not be exactly the same, as illustrated below.

Average

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