I published a new preprint with my PhD supervisor titled Detailed modelling of aerosol growth dynamics.

In it, we present a review of developments in detailed population balance modelling of particles formed in combustion/aerosol processes. Morphologically and chemically complicated particles are formed via chemical and physical processes arising in industry and the natural world, and their properties can have significant implications for end-product quality, human health, and the environmental. Numerical methods of varying complexity are developed and applied to better understand the way particles form and grow under relevant conditions, and to support experimental observations of particle structure.

Our review focuses on stochastic/Monte Carlo methods, which are best suited to simultaneous, extensive characterisation of both chemistry and particle geometry in organic and inorganic systems, with other population balance modelling strategies discussed to contextualise the stochastic approach. Monte Carlo methods enable the use of high-dimensional particle models to resolve the typically fractal-like, complex aggregate structure of particles produced by flame synthesis; however, they can be computationally costly as many simulated particles are required to provide statistical resolution of broad particle size distributions and highly polydisperse particle systems. In addition, good coupling to (turbulent) transport is an open challenge.