Surface structural and solar absorptance features of nitrate-based copper-cobalt oxides composite coatings: Experimental studies and molecular dynamic simulation

The copper and cobalt oxides composites coatings on aluminum substrates have been successfully synthesized via sol-gel method using nitrate-based sol precursors. The composites were characterized by X-ray Diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM), Atomic Force Microscopy (AFM), and UV–Vis–NIR spectrophotometry. The sol-gel reactions were discussed and Molecular Dynamics (MD) simulation was integrated into the study to predict molecules assembly properties. The XRD analyses revealed that the CuO and the Co₃O₄ composites were formed after the annealing process with the average difference of the calculated lattice parameters compared to ICDDs was 1.17%. The surface electronic structure was mainly consisted of tetrahedral Cu(I), octahedral Cu(II), tetrahedral Co(II), octahedral Co(III) as well as surface, sub-surface and lattice oxygen O^?. The XRD, XPS and MD simulation results showed that there was minimal (or possibly non-existing) indication of copper-cobalt mixed phase oxides formations. FESEM and AFM surveys revealed that the coating had a porous surface composed of interlinked nanoparticles in the range of ~?10 to ~?40?nm. UV–Vis–NIR reflectance spectra showed that the sol precursors concentration and the dip-drying cycle significantly influenced the absorptance value with optimum absorptance (α) of 88.7% exhibited by coating synthesized using sol concentration of 0.1?M and 10 dip-drying cycles. High absorptance value and simplicity in the synthesis process render the coatings to be very promising candidates for solar selective absorber (SSA) applications.     

Adaptive neural network output feedback control of incommensurate fractional-order PMSMs with input saturation via command filtering and state observer

Neural Computing and Applications - In this paper, an adaptive neural network (NN) output feedback control is investigated for incommensurate fractional-order permanent magnet synchronous motors...     

Computational Fluid Dynamics Study on a Top-Blown Smelting Process with Lance Failure in an Isa Furnace

JOM - The Isa/Ausmelt smelting technology with a top submerged lance (TSL) has been extensively used in copper smelting processes. However, the TSL is extremely vulnerable to damage and failure...     

Identification of vivianite,an unusual blue pigment,in a sixteenth century painting and its implications

Vivianite, a blue pigment employed in the past practically only in Northern and Central Europe, but with very limited use, was identified in an early sixteenth century painting, stylistically with Flemish features, from a church in Portugal. The identification of this iron phosphate mineral was made by SEM‐EDS based on the atomic ratio between phosphorus and iron in layers of blue paint (area analysis) and in particles of these same layers (spot analysis). This painting, about which there is no document to prove its authorship, becomes the first case, known in detail, of a sixteenth century painting containing vivianite. Moreover, this find and the presence of a chalk ground, also identified, strongly support the hypothesis of being a Flemish painting.     

Preparation and polymerization of isopimaric acid derivatives

Isopimaric acid is a typical rosin compound and can account for 30% of the total mass of slash pine rosin. The molecular structure of isopimaric acid derivatives features an unsaturated double bond at the C13 position, opening up the possibility of their industrial polymerization. In this study, isopimaric acid (95.4%), methyl isopimarate (99.5%), and allyl isopimarate (95.1%) were prepared as highly pure monomers. New experimental results are presented and mechanisms based on the investigation of free-radical polymerization under UV irradiation are proposed. New rosin monomers for potential value-added utilization of woody biomass are also identified. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47817.     

Structural,magnetic and magnetostrictive properties of Co1-xLixFe2O4 synthesized by cathode materials of spent Li-ion batteries

In this study, we investigated the effects of substituting Li⁺ for Co²⁺ at the B sites of the spinel lattice on the structural, magnetic and magnetostrictive properties of cobalt ferrites. The Li⁺ substituted cobalt ferrites, Co_1-xLi_xFe₂O₄, with x varying from 0 to 0.7 in 0.1 increments, were synthesized with a sol-gel auto-combustion method using the cathode materials of spent Li-ion batteries. X-ray diffraction analysis revealed that all the Co_1-xLi_xFe₂O₄ nanopowders had a single-phase spinel structure and the lattice parameters decreased with increasing Li⁺ content, which can be proved by slight shifts towards higher diffraction angle values of the (311) peak. Field emission scanning electron microscopy was used to observe the fractured inner surface of the sintered cylindrical rods and the increased porosity resulted in a decreased magnetostriction. The oxidation states of Co and Fe in the cobalt ferrite samples were examined by X-ray photoelectron spectroscopy. High resolution transmission electron microscopy micrographs showed that most particles were roughly spherical and with sizes of 25–35?nm. Li⁺ substitution had a strong effect on the saturation magnetization and coercivity, which were characterized with a vibrating sample magnetometer. The Curie temperature was reduced due to the decrease in magnetic cations and the weakening of the exchange interactions. The magnetostrictive properties were influenced by the incorporation of Li⁺ at the B sites of the spinel structure and correlated with the changes in porosity, magnetocrystalline anisotropy and the cation distribution.     

Tensor Q-rank: new data dependent definition of tensor rank

Machine Learning - Recently, the $${ Tensor}~{ Nuclear}~{ Norm}~{ (TNN)}$$ regularization based on t-SVD has been widely used in various low tubal-rank tensor recovery tasks. However, these models...     

Multi-objective layout optimization for an orbital propellant depot

Structural and Multidisciplinary Optimization - The overall layout optimization design of an orbital propellant depot involves the optimization of shape, size, and positions of propellant tanks in...     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.