Modeling: New algorithm closely describes dynamics of polymer melt
A new model that predicts how complex, branched polymers flow will enable companies to develop new plastics more efficiently and to process materials more easily than ever before.
Until now, polymer scientists have been able to simulate only how simplistic, molten polymers move. The new computational technique, developed by a team of researchers in Europe, closely accounts for the flow of real, tangled polymers, such as low-density polyethylene (LDPE) (Science, DOI: 10.1126/science.1207060).
Combining a decades-old “tube model” that defines how far polymer chains can move sideways during flow with a mathematical algorithm that predicts the distribution of polymer chain sizes and shapes in a given reaction mixture, the researchers designed an industry-ready tool that can calculate the dynamics of branched-polymer melts. They tested their model on LDPE, a popular material for plastic bags.
The real advance that made this computational feat possible, says Daniel J. Read, a research team member at the University of Leeds, in England, is the “priority distribution” used in the calculation. That’s a “posh” term, he says, for describing how far polymer segments that are tangled up in the mixture will stretch before going with the flow. To determine the distribution, he adds, “we work out how forces are transmitted from the outside of a hugely branched molecule to the inside.” The feat is similar to predicting the outcome of a tug-of-war game with a highly branched piece of rope.
The researchers’ method “provides a major step toward finally unraveling the LDPE tangle,” says Ronald G. Larson, a chemical engineer at the University of Michigan, in a commentary associated with the team’s report. But whether it can predict LDPE properties such as diffusion and adhesion remains to be seen, he adds.
Even though there are always further questions to answer, says team leader Tom C. B. McLeish of Durham University, in England, “it will be very exciting” in the meantime to watch whether industry can use this predictive tool to speed up the development of new materials, such as biopolymers.