Session RR05: V: Semicrystalline, Block, and Star Polymers

The role of intermolecular interactions on the crystallization

Crystalline properties of polyesters have attracted great interest since they can be obtained from sustainable sources and are biodegradable. The study of crystalline properties is of great relevance since it affects the final performance of the material, including mechanical properties and barrier properties. Nevertheless, the effect of intermolecular interactions has not been studied systematically. In this work, a series of polyesters that contain additional ester and amide groups have been studied. In addition to the presence of functional groups, the effect of the number of methylene groups and the position of the functional group in the repeating unit of the polymer in the crystalline properties is studied. We demonstrate how the presence of additional ester and amide groups widens the melt memory effect and hinders the crystallization process leading to higher undercoolings due to intermolecular interactions. The incorporation of additional ester groups, however, does not significantly modify the melting and crystallization temperature. Therefore, this work can shed light on understanding how the intermolecular interactions can modify the thermal properties. This would allow to tune melt memory, crystallization kinetic or thermal parameters (T_m or T_c) independently.

    

Spherulites, Cylindirtes and Other Morphologies of Semicrystalline Polymers Revealed in 3D by Optical Tomography

Morphology of semicrystalline polymers on the super-µm scale, spherulites, shish-kebabs, and cylindrites, strongly affects the mechanical and other material properties. Current imaging techniques give only a 2D picture of these objects, whose features in the 3rd dimension have been assumed rather than observed. Here we show how they can be visualized in 3D using two-photon confocal laser-scanning microscopy on suitably labelled polymers such as i-polypropylene or poly(lactic acid). As a result, we see spherulites and shear-induced cylindrites in 3D. The images also reveal unsuspected morphologies such as "vases" and "goblets", nonspherical "spherulites" and, unexpectedly, "shish-kebabs" grown from static melt. For shear-induced cylindrites, 3D images show that their circular cross-section is deformed into elliptical extended toward film-substrate interface. Unexpectedly, in the case of fiber pull induced cylindrites, a row of spherulites is nucleated at polymer-substrate interface, aligned along the fiber axis. All these intriguing morphologies are attributed to negative pressure buildup peaking at the growth front and at the nearby polymer surface caused by crystallization-induced volume contraction. This interpretation is supported by finite element simulation. These results reveal unfamiliar modes of self-assembly in familiar plastics and open new perspectives on polymer microstructure.   

How entanglements determine the morphology of semicrystalline polymers

Crystallization of polymers from entangled melts generally leads to the formation of semicrystalline materials with a nanoscopic lamellar morphology. Controlling this structure is key to the rational design, application and possible re-use of thermoplastic materials, but there is no consensus yet on the factors that control the thickness of the amorphous layers. We elucidate the effect of entanglements on the morphology in a series of model blends of high-molecular-weight polymers with unentangled oligomers leading to a reduced entanglement density as characterized by rheological measurements in the melt. Small-angle X-ray scattering experiments after isothermal crystallization reveal a reduced thickness of the amorphous layers, while the crystal thickness remains largely unaffected. A simple yet quantitative model without adjustable parameter is suggested, according to which the measured thickness of the amorphous layers adjusts itself in such a way that the entanglement concentration reaches a specific maximum value.   

Correlating near infrared data for improved polyolefin recycling

Polyolefins, the most ubiquitous polymers, continue to be difficult to sort. While the state-of-the-art technique for sorting polymers on an industrial scale, near infrared (NIR) spectroscopy, is fast, it is challenging to differentiate polyolefins by type (e.g., polypropylene, high density polyethylene, low density polyethylene, linear low density polyethylene). Since polyolefins are chemically similar but have diverse topologies leading to properties such as semi-crystallinity that can vary dramatically, the properties post recycling can be significantly degraded if polyolefins are not sorted. Here, we use slow, but precise measurement techniques to build a dataset of polyolefins and their corresponding properties. Using machine learning on the NIR data, we first demonstrate that we can identify the different types of polyolefins. We then show that the machine learned latent space of the NIR measurements can be correlated with physical quantities such as density, crucially connecting the fast, industrial measurement to the underlying physics. This connection can ultimately lead to enhanced sorting and thus improved recycling of polyolefins.   

Molecular simulations of strain-induced crystallization in multiblock copolymers

Semicrystalline thermoplastic elastomers such as polyurethanes, polyether-b-polyamide (or -polyester) and olefin block copolymers could be regarded as multiblock copolymers holding alternatingly crystallizable and noncrystallizable blocks. They are commonly processed by a basically strain-induced crystallization process in such as plastic molding, film stretching, fiber spinning and substrate casting. We studied three physical effects of the noncrystallizable components, i.e. dilution, microphase separation and contrast block rigidity, on the size diversity of crystalline microdomains yielded in strain-induced crystallization. The size diversity is considered as a vital factor in the high toughness of the materials, while the crystalline microdomains play the role of physical crosslinks in the high elasticity of the materials. Understanding these effects will facilitate our better understanding of chemical compositions and processing parameters of semicrystalline thermoplastic elastomers.   

Fluctuation and Correlation Effects on the Tiling Patterns Formed by ABC Stars of Symmetric Interactions

Based on the same model system used in the dissipative particle dynamics (DPD) simulations of ABC miktoarm star triblock terpolymers (referred to as "stars") of symmetric interactions (where the interaction parameters among the three components are equal), we perform both the self-consistent field (SCF) calculations and DPD simulations. This allows direct comparisons between them, without any parameter fitting, to unambiguously quantify the effects of fluctuations and correlations neglected by the former. In particular, we find the bulk periodicity of various lamellae and tiling patterns in our DPD simulations according to the recently proposed method. Comparisons of the SCF results for the above DPD model and those for the "standard" model further reveal the effects of model differences on the self-assembled structures of ABC stars.   

Mixing and Demixing Arising from Compression of Two Flexible and Semi-Flexible Polymer Chains in Nanochannels

We use molecular dynamics (MD) simulation to probe the non-equilibrium physics of two nanochannel-confined polymers in a homogeneous flow field. We find that the internal organization of the two chains takes the form of interwoven folds and circular coils for semi-flexible chains. This organization can lead to mixing or demixing depending on chain stiffness and flow speed. For sufficiently stiff chains, at low and intermediate flow, the two chains adopt a folded configuration that favors mixing. At high flow, the two chains adopt a predominantly coiled configuration that favors demixing, but only when the two chains are initialized in a demixed state. For decreasing stiffness, the chains start to aggregate locally instead of mixing smoothly. In the flexible chain limit, the two chains adopt a locally demixed configuration consisting of large aggregates that undergo complex stochastic dynamics, diffusing, disintegrating and reforming. In this low stiffness/flexible regime, new aggregates nucleate only when the two chains diffuse into a particular configuration that allows the chain closest to the barrier to penetrate through the second chain. Behavior resembling the low stiffness regime simulation results have been observed in nanofluidic experiments where two differentially labelled DNA chains inside nanochannels are compressed by buffer flow against a slit barrier that blocks the DNA while permitting buffer to escape.