Modelling the dynamics of active matter

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Active matter is a term used to describe matter that is composed of a large number of self-propelled active `particles' that individually convert stored or ambient energy into systematic motion. The interaction of many of these individual active particles with each other or their environment can lead to complex collective dynamics. Biological examples include a flock of birds, a school of fish, or at smaller scales a suspension of bacteria or even the collective motion within a human cell. The study of such active matter is important in many bio-related applications including: the design of synthetic materials (bioengineering), models of population dynamics (bioremediation), the control of biofilm formation (biomedical), and alternative energy production (biofuels). Understanding the dynamics of active matter systems can ultimately lead to the careful design and control of synthetic active matter allowing for applications such as autonomous chemical sensing or the targeted delivery of payloads by synthetic autonomous active particles. The objective of this program is to develop a mathematical modelling and computational framework using fast numerical methods and machine learning to describe, and then design, dense active matter systems for applications ranging from health to energy. This includes scenarios where there are many interacting autonomous active particles exhibiting collective dynamics in fluid environments that may contain complex heterogeneous microstructure.