A generalized equation for the prediction of melting temperatures of homopolymers and copolymers

A generalized equation was derived to calculate the melting temperatures of homopolymers and copolymers. The Gibbs‐Thomson equation for homopolymers and a modified application to copolymers were derived using the proposed equation. The melting temperature T_m⁰ in the Flory equation corresponds to the melting temperature T_m^C,∞ of copolymer crystals with stems of infinite length. Also, T_m^C,n*, the melting temperature for copolymer crystals with stems containing the maximum possible number of structural units, n*, should be used instead of T_m⁰ as the basis of supercooling in crystallization. The proposed equation shows good agreement with experimental data for α‐alkene‐ethylene homogeneous copolymers.     

On the kinetics of the autoxidation of fats: influence of pro‐oxidants,antioxidants and synergists

The influence of minor amounts of pro‐ and anti‐oxidants on the kinetics of the autoxidation of fat has been evaluated. The reaction rates of oxygen with the substrates were found to follow the same basic equation, hitherto established for pure substrates. There is evidence that the surface of the reaction vessel also acts as a reaction catalyst and its effect is proportional to the area of glass in contact with lipids. Oxidation is enhanced by trace metal ions as well as by surface‐active compounds (e.g. hydroperoxides and sterols). Antioxidants such as α‐tocopherol and butylated hydroxyanisole inhibit the oxidation by delaying the start of oxygen consumption (the induction period) while retarders like amino acids only decrease the rate of oxidation. Thus pro‐ and anti‐ oxidants affect either the start or the rate of oxygen consumption. The empirical formula dx/dt = k [O₂] (1‐x/n) f′(t) was found applicable to the different stages of oxidation.     

Cholescintigraphy in the diagnosis of Rotor syndrome

A 2-year-old boy with Rotor syndrome was studied with Tc-99m N-(di-isopropylphenyl carbamoylmethyl) iminodiacetic acid (DIPA). In this patient, the liver was not visualized, and there was persistent visualization of the cardiac blood pool and along with prominent kidney excretion. It is concluded that Tc-99m DIPA cholescintigraphy may be helpful in the diagnosis of Rotor syndrome.     

Evaluation of fine needle capillary sampling in superficial and deep-seated lesions. An analysis of 670 cases

The gene rafY from the plasmid pRSD2, which enables Escherichia coli to grow on raffinose, was transferred into expression plasmid pUSL77. The protein was expressed in the porin-deficient Escherichia coli strain KS26 and was isolated and purified to homogeneity. The pure protein was reconstituted into lipid bilayer membranes. It formed an ion-permeable channel with a single-channel conductance of 2.9 nS of the open state in 1 M KCl, which is approximately twice of that of the general diffusion pores OmpF and OmpC of E. coli outer membrane. At lower pH the channel exhibited rapid flickering between three substates of the open channel. The RafY channel appears to be wide and water filled and has a small selectivity for cations over anions. Although RafY is part of an uptake and fermentation system for raffinose it does not contain a binding site for carbohydrates. Our results suggest that RafY is a general diffusion pore with a diameter, larger than that of the general diffusion porins OmpF and OmpC, that allows the diffusion of high-molecular-mass carbohydrates through the outer membrane.     

Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization

Neural Computing and Applications - Cryptography often involves substituting (and converting) the secret information into dummy data so that it could reach the desired destination without leakage....     

A systematic review on emperor penguin optimizer

Neural Computing and Applications - Emperor Penguin Optimizer (EPO) is a recently developed metaheuristic algorithm to solve general optimization problems. The main strength of EPO is twofold....     

First-principles investigation of F-functionalized ZGNR/AGNR for nanoscale interconnect applications

Journal of Computational Electronics - Zigzag and armchair graphene nanoribbons (ZGNR and AGNR) have been investigated using the density functional theory (DFT) and nonequilibrium Green’s...     

Effect of the dispersed phase fraction on particle size in blends with high viscosity ratio

It has been reported that for polymer blends with high viscosity ratio (>1), the size of the dispersed particles decreases with increasing volume fraction of the dispersed phase. In order to explain this effect, an equation was derived for the affine deformation of an imaginary plane of the dispersed phase in stratified two‐phase steady, simple, shear flow. The model predicts that for viscosity ratio >1, the deformation rate increases with volume fraction of the dispersed phase, and the shear stress also increases, leading to an increase of the breakup time. Therefore, the total deformation of the dispersed phase, before breakup, increases with increase of volume fraction, resulting in a decrease of the size of the dispersed phase particles. Accordingly, one can expect that in industrial mixers, the particle size of the blends should decrease as the volume fraction increases, if coalescence is suppressed. Experiments were carried out in a Haake batch mixer, using polyethylene/polyamide‐6 blends compatibilized by adding maleic anhydride grafted polyethylene. Particle size decreased up to 20 wt% polyamide‐6, at 100, 150, and 200 RPM, and increased between 20 and 30 wt%. The decrease of the particle size is mainly due to increased deformation of the dispersed phase. The increase of the particle size above 20 wt% is due to coalescence at high fractions.     

A structure-oriented computer simulation of the injection molding of viscoelastic crystalline polymers part II: Model predictions and experimental results

A theoretical model proposed for simulation of the injection molding of partially crystalline thermoplastics can predict fill time, velocity, temperature and pressure distributions, the distribution of shear and normal stresses, crystallinity, amorphous birefringence, and tensile moduli. In this paper, experimental data will be compared to the predictions of the model.