No abstract

This review focuses on a somewhat unexplored strand of regenerative medicine, that is in situ tissue engineering. In this approach manufactured scaffolds are implanted in the injured region for regeneration within the patient. The scaffold is designed to attract cells to the required volume of regeneration to subsequently proliferate, differentiate, and as a consequence develop tissue within the scaffold which in time will degrade leaving just the regenerated tissue. This review highlights the wealth of information available from studies of ex-situ tissue engineering about the selection of materials for scaffolds. It is clear that there are great opportunities for the use of additive manufacturing to prepare complex personalized scaffolds and we speculate that by building on this knowledge and technology, the development of in situ tissue engineering could rapidly increase. Ex-situ tissue engineering is handicapped by the need to develop the tissue in a bioreactor where the conditions, however optimized, may not be optimum for accelerated growth and maintenance of the cell function. We identify that in both methodologies the prospect of tissue regeneration has created much promise but delivered little outside the scope of laboratory-based experiments. We propose that the design of the scaffolds and the materials selected remain at the heart of developments in this field and there is a clear need for predictive modelling which can be used in the design and optimization of materials and scaffolds.

Memory effects on polypropylene systems with differents amounts of a nucleating agent (Dybenzylidene Sorbitol DBS) have been studied by Wide Angle X ray scattering methods. It has been observed that deformation applied in polypropylene melts, where even small amounts of DBS are included, is templated into the crystalline state. After crystallising a sheared polypropylene/DBS melt, an anysotropic texture is observed by X ray scattering, whereas the crystals produced from sheared pure PP melts are randomly distributed. This fact is directly addressed how the DBS is spread into the polypropylene melts. Different concentration and deformation conditions are explored allowing to conclude that, below a certain temperature, the DBS self-organize into a three dimensional network producing the gelation of the PP melt. When the deformation is applied in this gel state, it is templated into the crystals, whereas when it is applied at temperatures above this self organisation, there is not memory of the deformation process when the sample crystallise.

The enhancement of dielectric constant in a polymer while maintaining low loss through composite methods has been challenging. In this paper, we report that through designing multi-layered structures with carbon nanofiber (CNF)/poly(vinylidene fluoride) (PVDF) composites intercalated by a pure PVDF layer, enhanced dielectric constant and low loss were achieved. The dielectric loss was similar to that of pure PVDF at high frequencies and even lower than pure PVDF at low frequencies. The results were achieved by designing special multi-layered structures including CNF/PVDF composite layers. The multi-layered sandwich-like or laminate structure composites with transversely heterogeneous CNF distributions were prepared using a simple two-step processing including solution casting and compression molding methods. The dielectric constant obtained from the sandwich structure containing 5, 7 and 15 wt% CNF/PVDF composite layers is even more independent of the frequency in a wide range from 10(2) to 10(6) Hz. Furthermore, the effects of the heterogeneous CNF distribution on the dielectric properties were studied by designing different multi-layered composite structures with varying architecture while maintaining the same CNF concentration level. It is shown that varying this stack-up architecture of different CNF distributions plays an important role in the enhancement level of the dielectric constant while having negligible effect on the dielectric loss of the nanocomposite, which is determined mainly by the CNF loading content.

A straightforward method using Legendre series enables the orientation distribution in a specimen with uniaxial symmetry to be derived from the azimuthal profile of a single arbitrary reflection. Moreover, the moments of the distribution (P2,(cos,)) can be obtained directly from the azimuthal profile without needing to calculate the complete distribution.Pole figures derived from X-ray diffraction measurements are the standard method of quantifying orientation in crystalline materials. Similarly, the azimuthal profiles of the diffuse arcs found for liquid crystals (Leadbetter & Wrighton, 1979) and non-crystalline polymers (Wilchinsky, 1968) have been used to give a measure of orientation.In polymers and liquid crystals, it is usually the orientation distribution for the molecular axes which is required, but this is only obtained directly from a pole figure if there is a strong reflection from planes perpendicular to the molecular axes. However, Wilchinsky (1963) has shown that, provided the molecules are random about their axes, a single arbitrary reflection can give the value of (cos 2.), where, is the angle between the molecular axis and the specimen axis.In this communication we show that, for a specimen with uniaxial symmetry, the higher moments of the orientation distribution can also be obtained from the azimuthal profile of an arbitrary reflection. Hence the full orientation distribution can be calculated without recourse to solving integral equations or inverting matrices.The scattering from a distribution of independent molecules is given by a convolution of the orientation distribution of molecular axes with the scattering for a single molecule (Ruland & Tompa, 1968). If both the orientation distribution D(,) and the molecular scattering I'(-) have cylindrical symmetry, then the resultant scattering I(,) also has cylindrical symmetry (Deas, 1952) and all three functions can be expanded in series of even-order Legendre polynomials (P2,), e.g. Equatorial reflection (, 0 = zt/2):(-1)" 22"(n!) 2 (P2.)o --(P2.)r (2n)!