Using deep learning to learn physics of conduction heat transfer

Journal of Thermal Analysis and Calorimetry - In the present study, an advanced type of artificial intelligence, a deep neural network, is employed to learn the physic of conduction heat transfer...     

Direct breath figure formation on PMMA and superhydrophobic surface using in situ perfluoro-modified silica nanoparticles

Breath figure formation was carried out directly on the surface of poly(methylmethacrylate) using a mixture of a good solvent, tetrahydrofuran, and a nonsolvent, water. Direct breath figure formation was coined for this method and a mechanism was proposed to describe the figure formation by the method based on hypothesizes available for the normal breath figure formation. The proposed mechanism is such that the sonication effect, immersion time, and water content on characteristics of the obtained figures can be explained. The figured surface was then made superhydrophobic with a water contact angle of 175° using in situ growing of perfluoro modified silica nanoparticles inside the figure cell by one-pot method. The spherical modified silica nanoparticles were detected being trapped by figure features providing a mechanical entrapment of the low-surface energy nanoparticles. © 2013 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2013     

Doping effect of Ag nanoparticles on critical current of YBa2Cu3O7−δ bulk superconductor

The objective of this work is to investigate the effect of Ag nanoparticles on critical current of YBa₂Cu₃O_7?δ (YBCO) superconductor. Ag nanoparticles with different particle sizes from 30 to 1000 nm were prepared through the chemical reduction of AgNO₃ in an alcohol solution. Then, samples of YBCO superconductors were doped by 1 and 2 wt.% of Ag nanoparticles with different sizes. Samples were characterized with XRD, SEM and EDX measurements. Critical current measurements were performed using a standard four-probe technique at liquid nitrogen temperature. The results showed by increasing of Ag nanoparticles up to 700 nm the J_c increases, but decreases by further increase in Ag particles size. The critical current enhancement is attributed to the improved connectivity between the grain boundaries and better crystallization of the grains.     

The noble effect of aging on the thermal conductivity of modified CNTs-ethylene glycol nanofluids

In order to improve the heat transfer process by using nanofluids, different nanoparticles and base fluids have been studied. In this work, stability and effect of aging and temperature on the thermal conductivity of CNTs-ethylene glycol (EG) nanofluids were investigated. Chemical functionalisation was used to oxidise the surface of CNTs. The functionalised CNTs were used to prepare the nanofluids by a two-step method. The stability of nanofluids was measured by UV-vis spectroscopy and the results showed that the nanofluids had a good stability over several days. Immediately after nanofluid preparation not too much increase was observed for thermal conductivity but the nanofluid aging had a great influence on the improvement of the thermal conductivity, as after 65 days, about 50% increase was observed. The increase has been attributed to forming an ordered nanolayer of EG molecules around the CNTs. Also no significant temperature dependence of thermal conductivity was observed up to 50°C possibly due to the lack of temperature dependence of CNTs Brownian motions.     

Gelatin Nanoparticles with Enhanced Affinity for Calcium Phosphate

Gelatin nanoparticles can be tuned with respect to their drug loading efficiency, degradation rate, and release kinetics, which renders these drug carriers highly suitable for a wide variety of biomedical applications. The ease of functionalization has rendered gelatin an interesting candidate material to introduce specific motifs for selective targeting to specific organs, but gelatin nanoparticles have not yet been modified to increase their affinity to mineralized tissue. By means of conjugating bone‐targeting alendronate to biocompatible gelatin nanoparticles, a simple method is developed for the preparation of gelatin nanoparticles which exhibit strong affinity to mineralized surfaces. It has been shown that the degree of alendronate functionalization can be tuned by controlling the glutaraldehyde crosslinking density, the molar ratio between alendronate and glutaraldehyde, as well as the pH of the conjugation reaction. Moreover, it has been shown that the affinity of gelatin nanoparticles to calcium phosphate increases considerably upon functionalization with alendronate. In summary, gelatin nanoparticles have been developed, which exhibit great potential for use in bone‐specific drug delivery and regenerative medicine.

     

On the Parameters Estimators for a Discrete Analog of the Generalized Exponential Distribution

Nekoukhou et. al (Commun. Statist. Th. Meth., 2012) introduced a two-parameters discrete probability distribution so-called Discrete Analog of the Generalized Exponential Distribution (in short, DGED). We shall attempt to derive conditions under which a solution for the system of likelihood equations exists and coincides with the maximum likelihood (ML) estimators of the DGED. This kind of ML estimators are coincided with some moment estimators. An approximate computation based on Fisher’s accumulation method is presented in order for the ML estimations of the unknown parameters. Simulation study is also illustrated. Meanwhile, in the sequel two special cases of the DGED are considered. Some statistical properties for such special cases of the DGED are provided. We also propose a linear regression-type model for estimation of the parameter. Finally, we fit the DGED to a real data set and compare it with two other discrete distributions.