Poly(butylene succinate-co-ε-caprolactone) Copolyesters: Enzymatic Synthesis in Bulk and Thermal Properties

This work explores for the first time the enzymatic synthesis of poly(butylene-co-ε-caprolactone) (PBSCL) copolyesters in bulk using commercially available monomers (dimethyl succinate (DMS), 1,4-butanediol (BD), and ε-caprolactone (CL)). A preliminary kinetic study was carried out which demonstrated the higher reactivity of DMS over CL in the condensation/ring opening polymerization reaction, catalyzed by Candida antarctica lipase B. PBSCL copolyesters were obtained with high molecular weights and a random microstructure, as determined by 13C NMR. They were thermally stable up to 300 °C, with thermal stability increasing with the content of CL in the copolyester. All of them were semicrystalline, with melting temperatures and enthalpies decreasing up to the eutectic point observed at intermediate compositions, and glass transition temperatures decreasing with the content of CL in the copolyester. The use of CALB provided copolyesters free from toxic metallic catalyst, which is very useful if the polymer is intended to be used for biomedical applications.

Introduction to the New Copolymer of Chloroprene and Acrylonitrile with Differentiated Properties

The random copolymer of chloroprene and acrylonitrile is a newly developed rubber whose features and value propositions are not scientifically explored yet. This article focuses on the basic characterizations and properties of acrylonitrile-chloroprene rubber. Qualitative analyses through infrared (FTIR) and nuclear magnetic resonance (1H-NMR) spectra confirm the presence of both the -Cl and -CN groups in the new rubber. As evidenced through differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA), the single glass transition temperature of acrylonitrile-chloroprene rubber reflects its monophasic random microstructure. While compared against commercial grades of chloroprene rubber (CR) and nitrile rubber (NBR), the new rubber provides a distinctive combination of properties that are not available with either of the elastomer alone. Acrylonitrile-chloroprene rubber demonstrates slightly lower specific gravity, an improved low-temperature compression set, higher flex-fatigue resistance, and lower volume swelling in IRM 903 and Fuel C to chloroprene rubber. As compared to nitrile rubber, the new copolymer shows appreciably better heat aging and ozone resistance. Good abrasion resistance, low heat buildup, and remarkably high flex-fatigue resistance indicate excellent durability of the acrylonitrile-chloroprene rubber under dynamic loading. Based on the preliminary results, it is apparent that the new copolymer can be a candidate elastomer for various industrial applications which demand good fluid resistance, high heat and low-temperature tolerances, good weatherability, and durability under static and dynamic conditions.

Synthesis and characterization of poly(butylene terephthalate) copolyesters derived from threitol

The synthesis, characterization, and thermal properties of partially renewable poly(butylene terephthalate) copolyesters containing alditol units are described. These copolyesters were obtained by polycondensation in solution from mixtures of 1,4-butanediol and 2,3-di- O-benzyl-L-threitol with terephthaloyl chloride. Copolyesters with weight-average molecular weights oscillating between 4 000 and 12 000 g·mol−1 and dispersities around 1.5 were obtained. All them had a random microstructure and were thermally stable well above 300°C. Copolyesters containing up to 30% of dibenzyl threitol units were found to be crystalline and to adopt the same crystal structure as the parent homopolyester poly(butylene terephthalate). The melting temperature and crystallinity were observed to decrease, and the glass transition temperature to increase, with increasing amounts of alditol units incorporated in the copolyester. Furthermore, the crystallizability was depressed by copolymerization.

End-to-end nanophotonic inverse design for imaging and polarimetry

By codesigning a metaoptical front end in conjunction with an image-processing back end, we demonstrate noise sensitivity and compactness substantially superior to either an optics-only or a computation-only approach, illustrated by two examples: subwavelength imaging and reconstruction of the full polarization coherence matrices of multiple light sources. Our end-to-end inverse designs couple the solution of the full Maxwell equations—exploiting all aspects of wave physics arising in subwavelength scatterers—with inverse-scattering algorithms in a single large-scale optimization involving ≳ 10 4 $\gtrsim {10}^{4}$ degrees of freedom. The resulting structures scatter light in a way that is radically different from either a conventional lens or a random microstructure, and suppress the noise sensitivity of the inverse-scattering computation by several orders of magnitude. Incorporating the full wave physics is especially crucial for detecting spectral and polarization information that is discarded by geometric optics and scalar diffraction theory.

Simulations of Non-Gaussian Property Fields Based on the Apparent Properties of Statistical Volume Elements

The properties of composite materials with random microstructures are often defined by homogenizing the properties of a representative volume element (RVE). This results in the effective properties of an equivalent homogeneous material. This approach is useful for predicting a global response but smooths the underlying variability of the composite's properties resulting from the random microstructure. Statistical volume elements (SVEs) are partitions of an RVE. Homogenization of individual SVEs produces a population of apparent properties. While not as rigorously defined as RVEs, SVEs can still provide a repeatable framework to characterize mesoscale variability in composite properties. In particular, their statistical properties can be used as the basis for simulation studies. For this work, Voronoi tessellation was used to partition RVEs into SVEs and apparent properties developed for each SVE. The resulting field of properties is characterized with respect to its spatial autocorrelation and distribution. These autocorrelation and distribution functions (PDFs) are then used as target fields to simulate additional property fields, with the same probabilistic characteristics. Simulations based on SVEs may provide a method of further exploring the uncertainty within the underlying approximations or of highlighting effects that might be experimentally measurable or used to validate the use of an SVE mesoscale analysis in a specific predictive model. This work presents an update to an existing simulation technique developed by Joshi (1975, “A Class of Stochastic Models for Porous Media,” Ph.D. thesis, University of Kansas, Lawrence, KS) and initially extended by Adler et al. (1990, “Flow in Simulated Porous Media,” Int. J. Multiphase Flow, 16(4), pp. 691–712). The simulation methodology is illustrated for three random microstructures and two SVE partitioning sizes.

On Continuum Based Multiscale Modelling of Engineered Soft Tissue Constructs

Engineered tissue constructs are assembled through combining scaffolds, cells and biologically active molecules for restoring, maintaining, or improving damaged tissues or whole organs. Cells in engineered tissue constructs often experience mechanical forces during the fabrication process, maturation process, and under in vivo conditions. These mechanical forces/stimuli induce cellular responses and affect cell viability, proliferation, and differentiation. While it is critical to understand the mechanical milieu of cells in tissue constructs, it is also extremely challenging due to the time and length scale span. Multiscale modeling approaches have been emerged to provide linkage among different length scale. One of the approaches is continuum based multiscale modeling to link organ, tissue and cellular levels. A representative volume element (RVE) with periodic or random microstructure serves as a vehicle to connect different length scales. This study focuses on effects of RVE selection, microstructure, and boundary conditions on the mechanical environment at cellular level. In particular, cell embedded alginate tissue constructs were studied. Hyperelastic models were used for modeling alginate and cells. Multi-cellular FE models were generated. The results of the average properties and the stress/strain experienced by cells were compared under different conditions.