Shape memory polymers (SMPs) are an important class of smart materials. So far the focus of such polymers was to find suited triggers for various application fields. Thus, the potential of most of these macromolecular networks regarding their maximally storable strain capability was not explored. In this study, the polyethylenes HDPE, LDPE, and ethylene-1-octene (EOC) were systematically investigated with respect to their strain storage potential. To achieve maximum strains, the polymers were chemically cross-linked in such a way that they are at the borderline between thermoplastics and elastomers. All investigated polymers showed higher strain storage than literature reported systems and exhibited excellent shape memory parameters. The highest stored strain was found for networks of EOC with fully recoverable 1400%. Interestingly, this value could not be enlarged by using EOCs with higher molecular weight, which is probably due to increasing content of entanglements as confirmed by Mooney-Rivlin.

Shape memory polymers (SMPs) are an important class of smart materials. Usually, these polymers can be switched between two shapes. Recently, the possibility of switching more than two shapes was introduced for SMPs with relatively low strain storage capability. In this work, a lightly cross-linked polyethylene blend comprising 80 wt% EOC, 15 wt% LDPE, and 5 wt% HDPE is prepared in order to obtain a tunable multiple-shape memory polymer with high strain storage capacity. It is found that depending on the programming procedure, this SMP obtains a dual-, triple-, or quadruple-shape memory effect, with well-defi ned intermediate temporary shapes (retraction < 0.5% K −1 ) over a signifi cantly broad temperature range (up to 30 K), large storable strains (up to 1700%), and nearly full recovery of all shapes ( > 98.9%). transition range. [14][15][16][17][18] For instance, Xie [ 19 ] obtained a tunable multiple-shape memory for PFSA (perfl uorosulfonic acid ionomer), which possesses a broad glass transition from 55 to 130 ° C, by correlating certain temporary shapes to different temperatures within its glass transition range. Kolesov and Radusch [ 20 ] showed a triple-shape memory for cross-linked polyethylene blends of HDPE and two different ethylene-1-octene copolymers (EOC), by correlating different temporary shapes to distinct temperatures within a broad melting range. With this system, they were able to store strains of up to 100% with an intermediate shape at 44%. In general, multiple-shape memory polymers store strains of up to 240%, which limit the relative retraction response. We have recently found that the stored strain of PE-SMPs can be greatly enhanced by lowering the degree of cross-linking in a way that the resulting network is at the borderline between thermoplastics and elastomers. [ 21 ] In the present manuscript, this concept is extended to polyethylene blends in order to obtain a tunable multiple-shape memory polymer with large strain storage capability. Experimental Section MaterialsHigh density polyethylene (HDPE) (Lupolen 6021D, M w = 220 000 g mol −1 , PDI = 10, 0.5 branches per 1000 C atoms) [ 22 ]

In this work, syndiotactic polypropylene (sPP) as well as isotactic polypropylene (iPP) are cross-linked to gain a shape memory effect. Both prepared PP networks exhibit maximum strains of 700%, stored strains of up to 680%, and recoveries of nearly 100%. While x-iPP is stable for many cycles, x-sPP ruptures after the first shape-memory cycle. It is shown by wide-angle X-ray scattering (WAXS) experiments that cross-linked iPP exhibits homoepitaxy in the temporary, stretched shape but in contrast to previous reports it contains a higher amount of daughter than mother crystals.

Here we report on a novel type of smart material that is capable of specifically responding to the changing rate of an environmental signal. This is shown on the example of lightly cross-linked syndiotactic polypropylene that reacts to a temperature increase by adapting its shape change according to the applied heating rate. In general, a material with such properties can be used to predict a system failure when used in a defined environment and is therefore called "predictive material".

In this study, a material is designed which combines the properties of shape-memory and electroactive polymers. This is achieved by covalent cross-linking of polyvinylidene fluoride. The resulting polymer network exhibits excellent shape-memory properties with a storable strain of 200%, and fixity as well as recovery values of 100%. Programming upon rolling induces the transformation from the nonelectroactive α-phase to the piezoelectric β-phase. The highest β-phase content is found to be 83% for a programming strain of 200% affording a d33 value of -30 pm V(-1). This is in good accordance with literature known values for piezoelectric properties. Thermal triggering this material does not only result in a shape change but also renders the material nonelectroactive.