The toxicity, climate impact, as well as the physical and chemical properties of ultra-fine soot particles emitted from combustion systems are strongly dependent on their size and morphology. Research attention has been paid in the last three decades to developing more accurate and capable methods to model soot particle coagulation in the presence of inception, surface growth, and oxidation, to predict particle size distribution as well as the detailed aggregate morphology of soot. While soot particle concentrations in hydrocarbon flames are primarily governed by soot kinetics, the morphology of soot particles is controlled by both soot kinetics and particle dynamics. Flame-generated soot particles are fractal aggregates formed by polydisperse and nearly spherical primary particles with a certain degree of overlapping. The properties of fractal aggregates, nanoparticle coagulation, and soot formation chemistry all play important roles in soot formation. This article reviews all these aspects but the focus is on recent progress in macro- and meso-scale modeling of soot particle aggregation in laminar sooting flames to avoid the complexities of turbulence. The reviewed macro-scale methods based on the population balance equation include the commonly used sectional methods and methods of moments. The main features of three recently developed state-of-the-art meso-scale methods, namely the event-driven Discrete Element Method, Monte Carlo Aggregation Code, and detailed stochastic population balance model are reviewed. To highlight the complexities of modeling the particle size distribution and detailed particle morphology without and with surface growth, numerical simulations of three test cases were conducted using the event-driven Discrete Element Method, the Monte Carlo Aggregation Code, and the two macro-scale methods. A detailed analysis of the results was presented to understand how different treatments of particle coagulation and surface growth in the two meso-scale methods affect the predicted particle size and morphology. The remaining challenges in modeling detailed soot particle morphology are outlined.

In nature, cells exist in three-dimensional (3D) microenvironments with topography, stiffness, surface chemistry, and biological factors that strongly dictate their phenotype and behavior. The cellular microenvironment is an organized structure or scaffold that, together with the cells that live within it, make up living tissue. To mimic these systems and understand how the different properties of a scaffold, such as adhesion, proliferation, or function, influence cell behavior, we need to be able to fabricate cellular microenvironments with tunable properties. In this work, the nanotopography and functionality of scaffolds for cell culture were modified by coating 3D printed materials (DS3000 and poly(ethylene glycol)diacrylate, PEG-DA) with cellulose nanocrystals (CNCs). This general approach was demonstrated on a variety of structures designed to incorporate macro- and microscale features fabricated using photopolymerization and 3D printing techniques. Atomic force microscopy was used to characterize the CNC coatings and showed the ability to tune their density and in turn the surface nanoroughness from isolated nanoparticles to dense surface coverage. The ability to tune the density of CNCs on 3D printed structures could be leveraged to control the attachment and morphology of prostate cancer cells. It was also possible to introduce functionalization onto the surface of these scaffolds, either by directly coating them with CNCs grafted with the functionality of interest or with a more general approach of functionalizing the CNCs after coating using biotin-streptavidin coupling. The ability to carefully tune the nanostructure and functionalization of different 3D-printable materials is a step forward to creating in vitro scaffolds that mimic the nanoscale features of natural microenvironments, which are key to understanding their impact on cells and developing artificial tissues.