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     

Nonnegative ill-conditioned linear systems and GMRES method

In this paper we consider solving ill-conditioned linear systems under nonnegativity constraints with noisy right hand sides. The classical approaches to solve such systems are constrained least square (quadratic programming) and barrier methods. First we present these classical methods. Then a modified version of the GMRES method (NGMRES) is presented. Since we assume that the coefficient matrices are ill-conditioned, then the Tikhonov regularization of the problem is considered. Our computational experiments show that the NGMRES provides us high quality solutions much faster than the other two approaches.     

Convex optimization approach to a single quadratically constrained quadratic minimization problem

In this paper, first we show that for rank deficient matrices, the optimal solution of a single equality constrained quadratic minimization problem can be found by relaxing the equality constraint to the inequality one, which makes the problem a convex problem. Then we show that for full rank matrices, an optimal solution can be obtained using semidefinite optimization framework.     

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.     

Robust least squares solution of linear inequalities

Least squares solution of linear inequalities appears in many disciplines such as linear separability problems and inconsistency correction. In this paper we consider this problem with uncertainty in its data. Then we prove that its robust counterpart is equivalent to a second order conic linear optimization problem, which can be efficiently solved using interior point methods.     

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.

     

Comparative of the removal of Pb2+, Cd2+ and Ni2+ by nano crystallite hydroxyapatite from aqueous solutions: Adsorption isotherm study

Release of heavy metal onto the water and soil as a result of agricultural and industrial activities may pose a serious threat to the environment. In this study, the adsorption behavior of nano hydroxyapatite with respect to Pb²⁺, Cd²⁺ and Ni²⁺ has been studied in order to consider its application to purity metal finishing wastewater. The batch method has been employed, using metal concentrations in solution ranging from 100 to 400 mg/L. The uptake capacity and distribution coefficients (K_d) were determined for the adsorption system as a function of sorbate concentration. The Langmuir, Freundlich, and Dubinin–Kaganer–Radushkevich (DKR) isotherms applied for sorption studies showed that the amount of metal sorbed on nano hydroxyapatite. It was found that the adsorption phenomena depend on charge density and hydrated ion diameter. According to the equilibrium studies, the selectivity sequence can be given as Pb²⁺ > Cd²⁺ > Ni²⁺. These results show that nano hydroxyapatite holds great potential to remove cationic heavy metal species from industrial wastewater.