Residual stresses and birefringence in injection molding of amorphous polymers: Simulation and comparison with experiment

A physical modeling and a two‐dimensional numerical simulation of the injection‐molding of a disk cavity by using a hybrid finite element method (FEM) and finite difference method (FDM) are presented. Three stages of the injection‐molding cycle––filling, packing, and cooling––are included. The total residual stresses are taken to be a sum of the flow stresses calculated using a compressible nonlinear viscoelastic constitutive equation and the thermal stresses calculated using a linear viscoelastic constitutive equation. The total residual birefringence is taken to be the sum of the flow birefringence related to the flow stresses through the stress–optical rule, and the thermal birefringence related to the thermal stresses through the photoviscoelastic constitutive equation. The Tait equation is used to describe the P‐V‐T relationship. The simulation shows that without packing the birefringence in the surface layer of moldings, with its maximum near the surface, is caused by the frozen‐in flow birefringence (flow stresses) and in the core region by the frozen‐in thermal birefringence (thermal stresses). With packing, a second birefringence maximum appears between the center and the position of the first maximum due to flow in the packing stage. The predicted birefringence profiles and extinction angle profiles are found to be in fair agreement with corresponding measurements in literature for disk moldings. © 2005 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 622–639, 2006     

Measurement of lipid flux to advance translational research: evolution of classic methods to the future of precision health

Over the past 70 years, the study of lipid metabolism has led to important discoveries in identifying the underlying mechanisms of chronic diseases. Advances in the use of stable isotopes and mass spectrometry in humans have expanded our knowledge of target molecules that contribute to pathologies and lipid metabolic pathways. These advances have been leveraged within two research paths, leading to the ability (1) to quantitate lipid flux to understand the fundamentals of human physiology and pathology and (2) to perform untargeted analyses of human blood and tissues derived from a single timepoint to identify lipidomic patterns that predict disease. This review describes the physiological and analytical parameters that influence these measurements and how these issues will propel the coming together of the two fields of metabolic tracing and lipidomics. The potential of data science to advance these fields is also discussed. Future developments are needed to increase the precision of lipid measurements in human samples, leading to discoveries in how individuals vary in their production, storage, and use of lipids. New techniques are critical to support clinical strategies to prevent disease and to identify mechanisms by which treatments confer health benefits with the overall goal of reducing the burden of human disease.Subject terms: Metabolomics, Translational research, Machine learning     

Metabolites from the Actinobacterium Saccharomonospora piscinae Isolated from a Fishpond Sediment

Chemistry of Natural Compounds -     

Particle interaction and coercivity for acicular particles

The influence of the packing factor on coercivity for an assembly of particles is calculated. A rigorously theoretical explanation for the origin of empirical constants in the phenomenologically linear expression is given. The nonlinear coercivity dependence for a small packing factor is attributed to the nonuniform distribution of particles and the surface effects.     

A new 3,4-dihydronaphthalen-1(2H)-one from the leaves of Cinnamomum philippinense

Investigation of the leaves extract of Cinnamomum philippinense (Merr.) Chang (Lauraceae) led to the isolation of one novel compound, cinnamophilin D. Its structure was determined through in-depth spectroscopic and mass-spectrometric analyses.     

Modulation of electric field on persistent current of carbon nanotubes

We use tight-binding model including curvature effects to study the effect of transverse electric field on the persistent currents of armchair and zigzag carbon nanotubes (ACNTs and ZCNTs) threaded by longitudinal magnetic field. With increasing field strength, ZCNTs could undergo zero-gap transitions, whereas metallic ACNTs are not affected. The current amplitude, without electric field, in a (m,m$m,m$) ACNT is inversely proportional to m²$m^2$. However, for a (m,0$m,0$) ZCNT, it is determined by the modulus of m with respect to three. Electric field could enhance the current amplitude of an ACNT, but could not change its magnetism. As for a ZCNT, both electric-field-distorted electronic states and zero-gap transitions determine a change in magnetism that is pronouncedly related with nanotube's geometry.     

Metal azelate coordination polymers containing a kinked dipyridyl tether: CdSO4 topology and “ligand vacancy” primitive cubic three-dimensional networks

Hydrothermal self-assembly has generated three coordination polymers incorporating the kinked hydrogen-bonding capable tethering ligand 4,4′-dipyridylamine (dpa) and the long flexible aliphatic dicarboxylate azelate dianion (⁻O₂C(CH₂)₇CO₂⁻, aze), [M(aze)(dpa)(H₂O)]_n (M = Co, 1; M = Ni, 2) and {[Cd(aze)(dpa)] · 2H₂O}_n (3). Complexes 1 and 2 possess crystallographically disordered azelate ligands, forming related three-dimensional (3-D) 4-connected “ligand vacancy” primitive cubic coordination polymer networks via the random intersection of two different types of [M(aze)(dpa)]_n idealized two-dimensional (2-D) layers. Compound 3 manifests a 3-D 6⁵8 CdSO₄ topology coordination polymer network, formed from orthogonal sets of parallel [Cd(aze)]_n double chains linked through dpa ligands. Luminescent properties for 3 and thermal properties are also discussed.     

Closed-form valuations of basket options using a multivariate normal inverse Gaussian model

This paper uses a multivariate normal inverse Gaussian model to develop closed-form pricing formulas for both geometric and arithmetic basket options. For geometric basket options, an exact analytical solution is possible; for arithmetic basket options, the formula is an approximation. The model is based on a jump-driven financial process, which is known empirically to be more realistic than a geometric Brownian motion. By comparing our results to Monte Carlo experiments, we confirm the internal consistency of our formulas. The “Greeks” can be derived from the closed-form formulas in a straightforward manner.