An experimental design methodology to evaluate the importance of different parameters on flocculation by polyelectrolytes

• Main Author: Pinheiro, Ineide
• Publication Date: 2013
• Other Authors: Ferreira, Paulo J., Garcia, Fernando A., Reis, Marco S., Pereira, Ana C., Wandrey, Christine, Ahmadloo, Hamideh, Amaral, José L., Hunkeler, David, Rasteiro, Maria G.
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://hdl.handle.net/10316/80330; https://doi.org/10.1016/j.powtec.2012.08.004
• topic: Flocculation; Partial least squares regression; Polyelectrolytes; LDS

Aggregation of particles is fundamental for improving the performance of many solid/liquid processes. Aggregation can be induced by different means, and one of the most common is based on the addition of polymeric additives, namely polyelectrolytes. In this work we have studied the flocculation of precipitated calcium carbonate (PCC), which is used as a filler in papermaking, and is induced by a range of cationic polyacrylamides with different structures, varying in molar mass and degree of branching. The flocculation process was monitored continuously using the LDS technique (laser diffraction scattering), which provides information about the size distribution and structure (fractal dimension) of the aggregates, for each sampling instant and, thus, about the kinetic curve for the flocculation process. This information has then been used to produce a model, based on an experimental design strategy, which allows us to relate flocculation efficiency with the PEL characteristics and concentration. The Partial Least Squares (PLS) regression method was selected to perform the regression, given the significant co linearity among the input variables. The results obtained lead us to conclude that the polymer intrinsic viscosity (related with the PEL molar mass and charge density, and supplying information about the volume of the polymer molecule in the solution) and the degree of branching are the parameters with a stronger influence on flocculation efficiency. The PLS models developed were also successfully validated using an independent data set, which provides confidence on their consistency and prediction accuracy.