(38g) In-Silico Tailoring Properties of Polylactide

Although significant progress has been recently made in the process-product development of bioplastics, they are still represented by only minute market share, mainly because of their higher cost and limited technical properties when compared to conventional petroleum-based polymers. Polylactic acid (PLA), or polylactide is a fully biodegradable thermoplastic polyester that is produced from renewable resources and offers significantly reduced carbon footprint when compared to its petroleum-based market competitors[1]. Nowadays, PLA is the most widely produced renewable and biodegradable polymer, having the third biggest market share among bioplastics[2], and steep increase in worldwide production capacity predicted for near future[3].

This contribution addresses development of multi-scale modeling platform as enabling technology for the simulation of PLA production and prediction of its rheological properties that affect the product processability and end-use-characteristics. The developed framework consists of three interconnected modules, starting with (i) macro-scale process simulator of PLA production by catalytic ring opening polymerization of lactide in a batch reactor, which provides dynamic evolution of important process characteristics (e.g., reaction mixture temperature, concentrations of reacting species) for (ii) micro-scale Monte Carlo (MC) simulation of polymer chains growth. MC simulation allows for prediction of important polymer characteristics such as full molecular weight distribution, and stores the information about the detailed microstructure of generated polymer chains for (iii) public domain software[4] enabling estimation of rheological properties of polymers with general branch-on-branch molecular structure. This approach allows for a direct mapping between the reaction conditions and application properties of PLA, and thereby opens the possibility for in-silico process optimization, virtual prototyping and tailoring of product properties.

During the development of the model-based enabling technology, attention was paid to the robustness and speed of the source codes (especially in the case of Monte Carlo simulation), so that they are suitable for potential use in the on-line model-based predictive control and optimization of PLA industrial production, enabling a big step towards economic and technological competitiveness of this promising biopolymer.

[1] A consortium led by E4tech (UK) Ltd (2015), From the Sugar Platform to biofuels and biochemicals â?? Final report for the European Commision Directorate-General Energy, Report No. ENER/C2/423-2012/SI2.673791.

[2] Sin L.T., Rahmat A.R., Rahman W.A. (2012), Polylactic Acid: PLA Biopolymer Technology and Applications, William Andrew.

[3] Carus M., Baltus W., Carrez D., Kaeb H., Ravenstijn J., Zepnik S. (2013), Market Study on Bio-based Polymers in the World â?? Capacities, Production and Applications: Satus Quo and Trends Towards 2020, nova-Institut GmbH

[4] Das C., Inkson N.J, Read D.J., Kelmanson M.A., McLeish T.C.B. (2006), J. Rheol., 50, 207-235.