TITLE:
Computational Screening of Thermoplastic Starch-Based Biopolymers Blends for Mixing Compatibility
AUTHORS:
Kambale Christian Katasohire
KEYWORDS:
Thermoplastic, Starch, Computational, Screening, Mixing, Compatibility
JOURNAL NAME:
Open Journal of Polymer Chemistry,
Vol.15 No.1,
November
14,
2025
ABSTRACT: Starch-based composites are among the most studied biomaterials considering their environmental and economic prospects. In this work, a comparative investigation of the mixing compatibility of two thermoplastic starch (TPS)-based blends was conducted. The compatibility investigation was executed with the help of the mixing task of the blends module from Material Studio 5.5 (Accelrys, Inc.). The module task of mixing provides the user with an accurate sampling of the mixing characteristics of the selected binary blends. The Blends module allows the screening for interaction energy between polymer and polymer, between polymer and solvent, as well as between solvent and solvent. The blending characteristics of TPS/Natural Rubber (NR) and TPS/Polycaprolactone (PCL) were studied by screening the monomers of each blend for mixing compatibility. The blending characteristics under study include binding energies distribution (Ebb, Ebs, Ess), Chi interaction parameter, and mixing energy (Emix). The outcome of the computational screening for the interaction energy between the monomer pairs of TPS/NR and TPS/PCL revealed that caprolactone had the best mixing capacity, illustrated by the similarity between binding energy distributions of the mixture, as well as by the minimal Chi parameter and lowest mixing energy. The TPS/NR blend, on the other hand, had the highest mixing energy and the highest Chi parameter. Moreover, its binding energy distribution displayed the smallest value of similarity. Thus, TPS/NR had the lowest blending capacity.