Cold programming of epoxy-based shape memory polymer

doi:10.1016/j.istruc.2020.05.023

Cold programming of epoxy-based shape memory polymer

2021-02-01

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DOI：10.1016/j.istruc.2020.05.023

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Shape Memory Polymers (SMPs) are the class of smart materials that show ability to memorize different shapes and regain original shape. The conventional method is to heat SMP above its glass transition temperature (Tg) and deform it to obtain the desired shape. It reverts to original shape upon heating. This is known as hot programming. Recent advances in the programming of SMP have shown promising results of a new programming method also known as cold programming. The SMP is plastically deformed at a temperature below Tg to impart the desired shape. This paper aims at the experimental investigation of shape memory properties of Epoxy-based SMPs using the cold programming method. The polymers of Epoxy used in this work are Diglycidyl Ether of Bisphenol-A (DGEBA) and Neopentyl Glycol Diglycidyl Ether (NGDE). The mechanical properties like elastic modulus, tensile strength, and failure strain have been found for different ratios of DGEBA and NGDE at various temperatures. The Tg of different compositions has been measured using Differential Scanning Calorimetry (DSC). In this work, a candidate material has been identified based on its mechanical and shape memory properties. It has been demonstrated that important properties of material like glass transition temperature, elastic modulus, and strength can be tailored according to the need by changing the ratio of constituents. A dedicated experimental setup consisting of Uniaxial Tensile Machine (UTM), temperature control chamber, and a camera for Digital Image Correlation (DIC) has been used to carryout thermomechanical cycles of SMP. The parameters that affect the performance of cold programming like stress-relaxation time, structural relaxation time, and operating temperature have been studied. The stress-strain response for a complete shape memory cycle has been measured. Parameters determining the shape memory capabilities like shape fixity, recovery ratio, recovery speed of the material were evaluated. The merits and demerits of cold programming over other programming methods have been discussed by carrying out required experiments. The differences in both the programming methods and the underlying mechanism of shape memory effect have been discussed briefly in this paper. Present work is limited to the study of SMP for uniaxial tensile cases undergoing large deformation with small strain-rate and low rate of heating and cooling.

Keyword:

Smart materials

Shape memory polymers

Cold programming

Cold programming of epoxy-based shape memory polymer

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