Sensing Dense Particulate Materials

Thousands of years ago, early Mesopotamian people discovered that a mixture of mud and straw creates strong durable buildings, what we call today a composite material. Composites are far better than the sum of their parts, for example they can be stronger and cheaper. Similar experiments with mixing fluids and gases led to the discovery of complex fluids. Composites, complex fluids, and powders can all be examples of particulate materials. These materials led to advances in food science and healthcare (emulsions, colloids, powders); automobile, aerospace, and construction (composites, cement), among many others.

Although these materials are highly valuable, we do not have accurate and simple ways to measure their structure. This is due to their complex microstructure, which is a random mix of different types of particles. However, measuring is the first step to automation and perfecting any product.

When using a powder for a chemical reaction, or producing an emulsion, the particles will constantly change size and properties. To automate these processes, we need to monitor the particle properties. In many cases the particle properties are simply unknown. For example, the pores (which are a type of particle) in bones. Measuring these pores would help diagnose and treat osteoporosis.

The end goal is to develop new sensing methods for dense particulates using ultrasound. To achieve this the first step is to understand how a sound wave reflects from these materials? To develop new sensing methods requires a team with engineers and mathematicians working together to develop: the maths of sound waves, consider how these sensors will be installed in industry, and use machine learning to deal with the complex microstructure of particulate materials.