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This study is a review of published literature that discusses the utilization of biochar and plastics as filler and matrix, respectively, in a composite material. These composites, referred to as biochar-filled plastic composites (BFPCs), play a significant role in the production of environmentally friendly materials. This paper provides an overview of BFPCs, their properties (mechanical, rheological, morphological, electrical, and thermal properties), fabrication techniques, and prospects and challenges associated with their development. Even though there have been previous studies on BFPCs, none of these studies have discussed the drawbacks and potential associated with the development of BFPCs. Biochars’ small weight makes them a more appealing option than traditional mineral fillers when it comes to reducing vehicle weight. Due to their superior mechanical and thermal qualities, as well as their low carbon footprint, biochar-filled plastic composites (BFPCs) play a significant role in the production of environmentally friendly materials. It was observed that either melt extrusion or injection moulding are usually used to fabricate BFPC. It was observed that the properties of BFPCs are influenced by several factors such as the type and concentration of plastic, method of fabrication, the biochar content, mixing uniformity of the mixture, wetting, and particle dispersion. Challenges of BFPCs were also discussed, such as the issue of particle agglomeration and poor interfacial bonding at high biochar concentrations in the composite. Composites made from recycled polymers or biodegradable polymers can be developed to improve the composites' overall sustainability.

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In this study, we investigate the thermal stabilities, thermo-kinetic, and thermodynamic behaviours of Corn Cob (CC), Husk (CH), Leaf (CL), and Stalk (CS) during pyrolysis using the Thermogravimetric Analysis (TGA) at a single heating rate of 10 °C/min. Thermo-kinetics and thermodynamic parameters were evaluated for two temperature regions, region I (100–350 °C) and region II (350–500 °C) by employing the Coats–Redfern (CR) integral method to fit the TGA data to sixteen kinetic models. Results showed that diffusion models (D1, D1, D3, and D1) best suited the decomposition of CC, CH, CL, and CS in region I with Ea values of 109.90, 186.01, 129.4, and 78.7 kJ/mol respectively. Similarly, D1, third order model (F3), D3, and nucleation model (P4) with Ea values of 68.50 (CC), 177.10 (CH), 62.10 (CL), and 127.70 (CS) kJ/mol respectively best described residues’ decomposition in region II. Furthermore, kinetic parameters were used to compute the thermodynamic parameters; change in enthalpy (∆H), Gibbs free energy (∆G), and change in entropy (∆S) values for both regions. To study the pyrolytic behaviours of the residues, Artificial Neural Network (ANN) was employed to develop models to predict weight losses in samples by determining the coefficient of determination (R 2) and minimum Mean Square Error (MSE). Results showed ANN as a very important tool for predicting the pyrolytic behaviours of corn residues and other biomass samples.

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