Chitosan nanocomposites mechanical properties play a major role in usage of such materials for specific areas of application, mostly in medicine and development of ecologically-friendly production. Computer-based predictive modelling of such composites will reduce costs of their development. In this paper, a multiscale approach for structural characterization and evaluation of mechanical properties is proposed based on hybrid coarse-grained/all atom molecular dynamics. Chitosan films and fibers are constructed and studied in silico as well as chitosan composites with different types of randomly distributed reinforcing fillers (graphene nanoparticles, graphene oxide nanoparticles, carbon nanotubes, chitin nanoparticles). Young's moduli are found for such composites, degrees of improvement of mechanical properties and size effects within the framework of proposed methodology are discussed.
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