The planar elongational melt rheology and structural properties of dendrimers and hyperbranched polymers of different molecular weights (generations 1-4) and their linear counterparts have been studied using nonequilibrium molecular dynamics simulation techniques in the isothermal-isobaric ensemble. The extensional viscosity showed three distinctive regions against strain-rate, including an initial Newtonian region at low strain-rates, followed by a thickening behavior at medium strain-rates and terminated with a thinning region at very high strain-rates, in agreement with the Sarkar and Gupta model [J. Rein. Plast. Comp. 20, 1473-1484]. In addition, a structural analysis was performed to study the size, shape, and spatial distributions within globular dendrimers and hyperbranched polymer molecules under planar elongational flow (PEF). Ratios of the eigenvalues of the gyration tensor showed that contrary to shear flow, under PEF even at low strain rates, dendrimers and hyperbranched molecules have ellipsoidal conformations and change to a much more flattened prolate shape at higher strain rates. In combination with the eigenvalue ratios, the distribution of monomers from the central core of the molecules showed that the thickening region occurs due to branches being stretched, and terminal thinning behavior stems primarily from flow-induced alignment and finite extensibility effects. V
Shape memory elastomers (SMEs) are a class of intelligent materials characterized by their ability to deform and recover shapes under applied force and external stimuli. Heat and ultraviolet radiation are examples of the most common external stimuli. With the emerging prevalence of internet of things devices and the ensuing need for smart materials and structures, SMEs provide significant opportunities to support the development of novel applications in robotics, remotely actuated systems, and packages, including those promised for the space industry. To harness the immense potential in the emerging applications of these materials, one approach is the systematic multi‐scale modeling coupled with artificial intelligence‐assisted design leading to the development of next‐generation intelligent systems. This review covers several aspects of the synthesis/materials chemistry and applications of SMEs with a view towards enabling such an approach. The synthesis procedures emphasizing dynamic covalent bond reactions are reviewed. Then, liquid crystalline elastomers are introduced as a specific elastomeric material class that exhibits excellent shape memory characteristics and distinctive transition temperatures. The utilization of advanced manufacturing methods such as additive manufacturing, three‐dimensional printing, and the emerging four‐dimensional printing technologies assisted by machine learning are detailed in producing and predicting SMEs. Finally, the current trends in the use of SMEs are summarized in areas of industrial and space engineering and biomedical applications.
Molecular dynamic (MD) simulation techniques are increasingly being adopted as efficient computational tools to design novel and exotic classes of materials for which traditional methods of synthesis and prototyping are either too costly, unsafe, and time-consuming in laboratory settings. Of such class of materials are liquid crystalline elastomers (LCEs) with favorable shape memory characteristics. These materials exhibit some distinct properties, including stimuli responsiveness to heat or UV and appropriate molecular structure for shape memory behaviors. In this work, the MD simulations were employed to compare and assess the leading force fields currently available for modeling the behavior of a typical LCE system. Three force fields, including Dreiding, PCFF, and SciPCFF, were separately assigned to model the LCE system, and their suitability was validated through experimental results. Among these selected force fields, the SciPCFF produced the best agreement with the experimentally measured thermal and viscoelastic properties compared to those of the simulated steady-state density, transition temperature, and viscoelastic characteristics. Next, shape fixity (R f ) and shape recovery (R r ) of LCEs were estimated using this force field. A fourstep simulated shape memory procedure proceeded under a tensile mode. The changes in molecular conformations were calculated for R f and R r after the unloading step and reheating step. The results revealed that the model LCE system exhibit characteristic behaviors of Rf and Rr over the thermomechanical shape memory process, confirming the suitability of selected force field for use in the design and prediction of properties of typical LCE class of polymers. I. INTRODUCTIONShape memory elastomers (SMEs) are a significant member of intelligent polymers which can be deformed to another temporary shape and subsequently recovered to their permanent shape again. 1,2 This process is typically achieved through an applied load and forms of trigger by an external stimulus. 3 Currently, a variety of external stimuli are utilized to activate shape memory effects, including heat 4 , pH 5 , water 6 , UV light 7 , or electric and magnetic fields 8,9 . Among these, heat is the most commonly used stimulus. Furthermore, molecular architecture of these materials, containing net-points (hard phase) and switch units (soft phase), is the crucial determining factor which promotes the shape memory behavior. 10 The net-points responsible for maintaining the permanent shape are generated by covalent
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