Processing-Property Relationships of Hemp Fibre
Thesis DisciplineMechanical Engineering
Degree GrantorUniversity of Canterbury
Degree NameMaster of Engineering
There is great interest in the plant Cannabis sativa (hemp) as a source of technical fibres for the reinforcement of polymers in composite materials due to its high mechanical properties. As a natural fibre hemp also offers biodegradabilty and is therefore an inexpensive and renewable alternative to glass fibres However, the environmental benefits of natural fibres cannot be fully exploited if the manufacturing of their composites involves polluting processing steps. Unfortunately, there is still a lack of environmetally sustainable processing methods yielding technical fibres of sufficient quality. Enzyme application as a biotechnological processing method is a good candidate for this aim and is therefore actively investigated at present. In this work the effects of a range of enzymes on the morphological, compositional and mechanical properties of hemp was investigated. The enzymes were firstly characterised and then applied to hemp fibre for differing periods of time. After visual inspection, a set of fibre samples were selected and subjected to further analysis by Fourier-Transform Infrared Spectroscopy (FTIR), tensile testing and scanning electron microscopy (SEM). The commercial formulation PectinexÂ® Ultra-SL emerged as the most efficient in terms of treatment time and fibre quality. The effectiveness of treatments was further investigated by developing a novel experimental method that correlates the adhesion forces measured by atomic force microscopy (AFM) on the fibre surface to the properties of the fibres or composites. In order to identify correlations between the adhesion forces and fibre or composite properties, hemp fibre was subjected to four distinctly different treatments to obtain significant differences between fibre properties. The fibres and composites were then analyzed using a combination of FTIR, tensile testing, 3-point bend testing, dynamic mechanical analysis (DMA) and SEM. Based on this comprehensive dataset the AFM data was correlated using the software SPSS. The information derived from AFM (adhesion forces and surface topology) was useful in the clarification of fibre modifications evoked by the treatments.