Activated clay, montmorillonite, and activated carbon were used for the removal of two basic dyes, Basic Green 5 (BG5) and Basic Violet 10 (BV10). Both dynamic and equilibrium data were obtained by the batch technique. The dynamic data indicate that the activated carbon was suitable for BG5 but not for BV10 primarily due to the molecular structure, whereas the montmorillonite was not good for either basic dye due to its low surface area for adsorption. The adsorption process was analyzed in terms of two pseudosteady-state equations and the intraparticle diffusion model. The adsorption isotherms of Langmuir and Freundlich as well as Langmuir -Freundlich types were employed to examine the equilibrium adsorption data. Results show that all the adsorption systems could be ORDER REPRINTS adequately fitted by the Langmuir -Freundlich equation. Thermodynamic parameters were also obtained.
A short time reflow of 15s at 250°C, followed by a liquid nitrogen quench, of the Sn–3Ag–0.5Cu solder on a Cu substrate gave rise to a three-layer interfacial structure. In addition to the commonly known η-Cu6Sn5∕ε-Cu3Sn layers, an amorphous layer with a thickness of less than 50nm exists between the Cu substrate and the thin ε-Cu3Sn layer. Nanocrystalline ε-Cu3Sn cells, revealed by transmission electron microscopy (TEM), as fine as 10nm were detected within the amorphous region. The results of TEM analysis suggest that the nucleation of interfacial intermetallic compound ε-Cu3Sn occurs within the amorphous layer.
To illustrate the interfacial reaction mechanism, the Sn-Zn[Sn–8.5Zn–0.5Ag-0.01Al-0.1Ga (wt%)] solder was reflowed on Cu substrate at 250 °C for 15 s followed by immediate quench in liquid nitrogen. The frozen interfacial microstructure was investigated with high resolution transmission electron microscope. An amorphous double layer was formed at the interface which consists of a 5 nm pure Cu region and a Cu-Zn diffusion region. Nanocrystalline intermetallic compound (IMC) Cu5Zn8 were observed in the Cu-Zn diffusion region. These nanocrystalline IMCs are suggested to form via a homogeneous nucleation process.
In the network technology era, the collected data are growing more and more complex, and become larger than before. In this article, we focus on estimates of the linear regression parameters for symbolic interval data. We propose two approaches to estimate regression parameters for symbolic interval data under two different data models and compare our proposed approaches with the existing methods via simulations. Finally, we analyze two real datasets with the proposed methods for illustrations.
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