Research in Solid-Liquid Separation

Publication Reference: 
14-06
Author Last Name: 
Somasundaran
Authors: 
P Somasundaran K.F.Tjipangandjara Yi-Bin Huang
Report Type: 
FRR - Final Report
Research Area: 
Wet Systems
Country: 
United States

EXECUTIVE SUMMARY

Removal of fines and ultrafines from sludges and such colloidal suspensions is often not easily achieved without flocculation using polymers. Even though the effectiveness of the polymers have been speculated in the past to depend on their conformation / orientation on the particles, there existed no information on the optimum conformation for flocculation nor reliable in-situ technique to directly monitor it. In this work, with the aim to improve quality of fines removal from liquids, conformation of polymers was investigated along with sedimentation and clarification. In addition, with a view to identify optimum flocc structures for solid-liquid separation and the mechanisms of flocc formation, structural characterization was done along with theoretical modelling of aggregation.

In order to identify methods to manipulate the adsorbed flocculent species for good flocculation, it was necessary first to identify their conformational behavior. For this purpose, we used fluorescence techniques and polymers with luminescent labels and compared their conformational behavior on the particles in suspension with its flocculation/sedimentation response. This approach led successfully to the conclusion that polymer conformation can be altered drastically by shifting the pH of the system or by adding other polymers or inorganics that can complex with it.

Characterization of floccs is a major hurdle in flocculation studies and in this regard we have adapted CAT SCAN techniques for characterizing sedimentation processes and flocc structure. Also, a Monte Carlo model was developed and applied successfully to simulate sedimentation of fine particles by considering sedimentation as a result of competition between gravitation and Brownian motion. In computer simulation of .aggregation, the diffusion-limited aggregation model has been modified to generate, for the first time, realistic sparse as well as dense floccs by varying the step size of random walks.