DEVELOPMENT OF HIGH-PERFORMANCE SHAPE MEMORY POLYMER COMPOSITES FROM RECYCLED POLYLACTIC ACID REINFORCED WITH GRAPHENE, GRAPHITE AND CORN SILK NANOFILLERS

The increasing volume of plastic waste from additive manufacturing and the demand for sustainable engineering materials have intensified efforts to repurpose post-consumer polylactic acid (PLA). However, recycled PLA (rPLA) remains underutilised due to diminished functional efficiency in high-performance uses. This study reinforces rPLA with graphene, graphite, and corn silk ash (CSA) nanoparticles to enhance its mechanical, thermal, and shape-memory behaviour for sustainable applications. PLA waste was obtained from failed 3D-printed parts, graphite was recovered from spent lithium-ion battery electrodes, and graphene nanoparticles (99.9% purity, 1.5 nm) were sourced from Nanografi Nano Technology, USA. Corn silk fibres were calcined at 400 °C to produce CSA. The shredded rPLA was melted at 196 °C, and each filler was incorporated at 1.0, 1.5, and 2.0 wt% using melt blending. Composite samples were examined using scanning electron microscope, energy-dispersive x-ray spectroscopy, and x-ray diffraction; tensile strength, micro-hardness, and thermomechanical shape-memory performance were evaluated. SEM showed homogeneous dispersion of graphene and CSA in PLA. EDX confirmed characteristic carbon-rich spectra for graphite composites and silicon and calcium peaks indicating CSA incorporation. XRD revealed increased crystallinity at 1.5 wt% for all fillers, with graphene composites exhibiting the sharpest diffraction peaks. Tensile strength increased from 0.068 MPa for rPLA to 1.541 MPa, 0.657 MPa, and 0.486 MPa for 1.5 wt% graphene, 1.5 wt% graphite, and 2.0 wt% CSA, respectively. Graphite improved hardness to 28.30, 28.70, and 26.90 HRB at 1.0, 1.5, and 2.0 wt%, while graphene and CSA did not. Shape-recovery time improved from 120 s (rPLA) to 25 s, 27 s, and 53 s at 2.0 wt% graphene, graphite, and CSA, respectively. Graphene, graphite, and CSA nanofillers markedly enhanced rPLA structural and shape-memory performance, with 1.5 wt% graphene providing the most balanced improvement. It is recommended to investigate hybrid reinforcement systems.