Estimating fractal dimension of microalgal flocs through confocal laser scanning microscopy and computer modelling

Flocculation followed by settling is gaining momentum as a means to concentrate microalgal biomass due to the low investment and operation costs of the process. Microalgal flocculation can be further optimized by knowing the relationship between the hydrodynamic conditions applied in the process and the geometric properties of the flocs, namely characteristic size and fractal dimension, Df, given that settling rate is highly dependent on these two parameters. Current methods to characterize the geometry of flocs rely on estimating the 2D fractal dimension from microscopic images, which may result in inaccuracies caused by the overlapping or superimposition of aggregate structures prompted when the image of a 3D object is projected a on the plane, and due to the fact that the estimation performed is dependent on the orientation of the particle during image acquisition. The present paper describes a new procedure to estimate Df of Chlorella sorokiniana aggregates by correlating the 2D fractal dimension of the real aggregates microscopic images with the 2D fractal dimensions of computer generated flocs of prescribed 3D geometry. This procedure avoids the inaccuracies entailed with floc imaging and those due to the random orientation of the floc during image acquisition.