Effect of anisotropic thermal expansion on the torsional actuation of twist oriented polymer fibres. (27th October 2017) - Aziz, Shazed; Naficy, Sina; Foroughi, Javad; Brown, Hugh R.; Spinks, Geoffrey M.
Abstract: Torsional actuation of twisted polymer fibres is the basis for high performance tensile actuation when these fibres are formed into coils. The thermally-induced torsional actuation of twisted polyamide-6 fibres can be predicted by a single helix approximation when the measured diameter and length direction thermal expansion coefficients are known. The single helix model illustrates the sensitivity of the magnitude of torsional actuation to the volume expansion anisotropy for a given volume change. The applicability of the model has been further assessed by investigating three polymer fibres that display different thermal expansion anisotropies. Commercially available polyethylene, polypropylene and polyamide-6 fibres were twisted to the maximum extent without coiling and then heat treated to fix the twisted structure. Heating the twisted fibres between 26 and 62 °C resulted in a partial untwist which was reversed during cooling. The single-helix model of the twisted fibres was used to accurately predict the torsional stroke based on the measured fibre length and diameter change during heating. Comparative torsional stroke of twisted polyamide-6, polyethylene and polypropylene was explained in terms of materials thermo-physical properties. Generated blocked torques was also correctly predicted by the single-helix model when combined with the measured fibre torsional stiffness. Variances between torsional stiffnesses were found to be dependent of different anisotropic thermal properties of tested fibres. Graphical abstract: Highlights: Heat-induced torsional actuation has been measured for 3 different polymer fibres. Torsional stroke, torque generated and torsional stiffnesses have been measured. Fibre diameter and length changes have been measured. Torsional stroke can be predicted using the single helix model. Torque generated can be predicted based on torsional stroke and stiffness.