Deakin-Coventry Cotutelle - 4D Shape Memory Composite Materials

Since Toyota announced its initial promising results on polymer nanocomposite materials there has been ongoing research and development in this field. The introduction of novel nanomaterials and the excellent qualities achieved by adding relatively low percentages to the raw polymer has made a significant interest of the scientific community worldwide to them ^[1]. As a result of this interest, nanocomposites have become more popular with manufacturers across a wide range of industries, such as automotive, aerospace, and solar energy ^[2][3].

Laser welding technology (LWT) has emerged as one of the most promising technologies for joining thermoplastic materials in recent years because of its numerous advantages, including no surface pre-treatment and organic solvents requirements, low and well-localized mechanical load, energy input in a tightly localized area, high automation degree, good precision control, clean procedure without microparticles generation, no ejection of the melt, and scalability in addition of nanocomposites [3][4]. Automotive, electronic components, and sterile manufacturing (medical devices, food packaging) industries all benefit from LWT's high accuracy and precise handling capabilities where joined components required ^[4].

This proposal aims to study the behaviour of soft and hard composite shape memory polymer (SMP) materials, particularly poly (lactic acid) (PLA) and different Polyamide66 (PA66) PLA-PA66 fabricated via LWT. Different nanocomposites will be studied for their prospective use in automotive and electrical components for the effects of nanoclay percentage on the performance of their soft hard smart composite structures with shape memory effect. The resulting joins will be analysed in terms of their morphing behaviour, shear, and peeling tests. Influence of sepiolite nanoclay on the properties of the resulting join between PLA and different PA66/nanoclay nanocomposites will be studied in this work. The resulting welding will be characterized based on shape memory behaviour and mechanical properties by performing peeling and shearing tests, as well as the morphology weld seam analysis by scanning electron microscopy. High speed imaging of the process will support the interpretation of the trends and help with a better understanding of the laser welding process of these new shape memory materials. Using an infrared camera to measure temperature during the process will provide us with accurate temperature history data that can be used for further analysis. The influence of process parameters on the response variations will be studied by analysis of variance (ANOVA) using the design of experiments method (DOE). Statistical modeling and optimization will be a valuable tool to evaluate the process parameters effects and their interaction effects.

_{References
[1] Mohd, N. A.; Ismail, H.; Rusli, A. Polym. Plast. Technol. Eng. 2017, 1, 1.
[2] Hasanzadeh, R.; Azdast, T.; Doniavi, A.; Babazadeh, S.; Lee, R. E.; Daryadel, M.; Shishavan, S. M. Int. J. Eng. 2017, 30, 143.
[3] Navas‐Martos, F. J., Yebra‐Rodríguez, Á., & La Rubia, M. D. (2018). J. A. Polym. Sci. 2018, 135(36), 46638.
[4] Visco, A. M.; Brancato, V.; Torrisi, L.; Cutroneo, M. Int. J. Polym. Anal. Charact. 2014, 19, 489.}