Dielectric relaxation around the nematic-isotropic transition of liquid crystalline polymers

This study is concerned with a series of acrylate based side-chain liquid crystalline (LC) polymers. Previous studies have shown that these LC polymers have a preference for parallel or perpendicular alignment with respect to the polymer chain which depends on the length of the coupling chain joining the mesogenic unit to the polymer backbone. On the other hand, the dielectric relaxation of these side-chain LC polymers shows a strong relaxation associated to the mesogenic unit dynamics. For samples with parallel alignment, it was found that the dielectric relaxation of the nematic is weaker and broader than the relaxation of the isotropic. By contrast, for samples with perpendicular alignment, the isotropic to nematic transition reduces the broadening the relaxation and increases the relaxation strength. These two features are more evident for samples with short coupling units for which the dielectric relaxation observed appears to be strongly coupled with the backbone dynamics.

A detailed single chain model for molten poly(tetrafluoroethylene) from a novel structure refinement technique on neutron scattering data

We present a new methodology that couples neutron diffraction experiments over a wide Q range with single chain modelling in order to explore, in a quantitative manner, the intrachain organization of non-crystalline polymers. The technique is based on the assignment of parameters describing the chemical, geometric and conformational characteristics of the polymeric chain, and on the variation of these parameters to minimize the difference between the predicted and experimental diffraction patterns. The method is successfully applied to the study of molten poly(tetrafluoroethylene) at two different temperatures, and provides unambiguous information on the configuration of the chain and its degree of flexibility. From analysis of the experimental data a model is derived with CC and CF bond lengths of 1.58 and 1.36 Å, respectively, a backbone valence angle of 110° and a torsional angle distribution which is characterized by four isometric states, namely a split trans state at ± 18°, giving rise to a helical chain conformation, and two gauche states at ± 112°. The probability of trans conformers is 0.86 at T = 350°C, which decreases slightly to 0.84 at T = 400°C. Correspondingly, the chain segments are characterized by long all-trans sequences with random changes in sign, rather anisotropic in nature, which give rise to a rather stiff chain. We compare the results of this quantitative analysis of the experimental scattering data with the theoretical predictions of both force fields and molecular orbital conformation energy calculations.

Extracting quantitative structural parameters for disordered polymers from neutron scattering data

The organization of non-crystalline polymeric materials at a local level, namely on a spatial scale between a few and 100 a, is still unclear in many respects. The determination of the local structure in terms of the configuration and conformation of the polymer chain and of the packing characteristics of the chain in the bulk material represents a challenging problem. Data from wide-angle diffraction experiments are very difficult to interpret due to the very large amount of information that they carry, that is the large number of correlations present in the diffraction patterns.We describe new approaches that permit a detailed analysis of the complex neutron diffraction patterns characterizing polymer melts and glasses. The coupling of different computer modelling strategies with neutron scattering data over a wide Q range allows the extraction of detailed quantitative information on the structural arrangements of the materials of interest. Proceeding from modelling routes as diverse as force field calculations, single-chain modelling and reverse Monte Carlo, we show the successes and pitfalls of each approach in describing model systems, which illustrate the need to attack the data analysis problem simultaneously from several fronts.

Expression of epitope-tagged LMW glutenin subunits in the starchy endosperm of transgenic wheat and their incorporation into glutenin polymers

The low-molecular-weight (LMW) glutenin subunits are components of the highly cross-linked glutenin polymers that confer viscoelastic properties to gluten and dough. They have both quantitative and qualitative effects on dough quality that may relate to differences in their ability to form the inter-chain disulphide bonds that stabilise the polymers. In order to determine the relationship between dough quality and the amounts and properties of the LMW subunits, we have transformed the pasta wheat cultivars Svevo and Ofanto with three genes encoding proteins, which differ in their numbers or positions of cysteine residues. The transgenes were delivered under control of the high-molecular-weight (HMW) subunit 1Dx5 gene promoter and terminator regions, and the encoded proteins were C-terminally tagged by the introduction of the c-myc epitope. Stable transformants were obtained with both cultivars, and the use of a specific antibody to the c-myc epitope tag allowed the transgene products to be readily detected in the complex mixture of LMW subunits. A range of transgene expression levels was observed. The addition of the epitope tag did not compromise the correct folding of the trangenic subunits and their incorporation into the glutenin polymers. Our results demonstrate that the ability to specifically epitope-tag LMW glutenin transgenes can greatly assist in the elucidation of their individual contributions to the functionality of the complex gluten system.

Multivalency in healable supramolecular polymers: the effect of supramolecular cross-link density on the mechanical properties and healing of noncovalent polymer networks

Polymers with the ability to heal themselves could provide access to materials with extended lifetimes in a wide range of applications such as surface coatings, automotive components and aerospace composites. Here we describe the synthesis and characterisation of two novel, stimuli-responsive, supramolecular polymer blends based on π-electron-rich pyrenyl residues and π-electron-deficient, chain-folding aromatic diimides that interact through complementary π–π stacking interactions. Different degrees of supramolecular “cross-linking” were achieved by use of divalent or trivalent poly(ethylene glycol)-based polymers featuring pyrenyl end-groups, blended with a known diimide–ether copolymer. The mechanical properties of the resulting polymer blends revealed that higher degrees of supramolecular “cross-link density” yield materials with enhanced mechanical properties, such as increased tensile modulus, modulus of toughness, elasticity and yield point. After a number of break/heal cycles, these materials were found to retain the characteristics of the pristine polymer blend, and this new approach thus offers a simple route to mechanically robust yet healable materials.

Developing green supply chain management taxonomy-based decision support system

The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.