Mixing is an important component of most processing operations. Blending and compounding also play a major role in the development of new materials. Thus better understanding of mixing phenomena and development of new criteria to assess mixing quality are of paramount importance. In previous work we have defined dispersive and distributive mixing criteria for process control and optimization and for machine scale-up. However, we expect additional fundamental insight and enhanced applicability can be gained by defining a new complex mixing index based on entropy, which synthesizes both dispersive and distributive mixing components. Entropy is a rigorous measure of disorder or system homogeneity used in several sciences such as statistical mechanics and information theory. This new index can be applied in a variety of technologies in polymer processing including fabrication of nanocomposite materials. Furthermore, understanding the influence of machine geometry and processing conditions on mixing as reflected through correlations between flow features and the new complex mixing index can point out to new directions in equipment design. The proposed mixing characterization methodology can be applied in other engineering processes beyond the polymer processing industry.
This research is an interdisciplinary effort involving a chemical engineer whose expertise lies in polymer processing and a physicist with expertise on statistical mechanics. This collaboration between Case Western Reserve University and Cleveland State University will enable application of concepts from theoretical physics to problems relevant to the manufacturing engineering community. Moreover, such collaborative efforts have also an educational impact with the potential of inducing student interest for interdisciplinary research projects dealing with complex problems. Students at both the graduate and undergraduate levels will benefit from this collaborative research project.
