Sathyabama University

About: Sathyabama University is a education organization based out in Chennai, Tamil Nadu, India. It is known for research contribution in the topics: Wireless sensor network & Diesel fuel. The organization has 5993 authors who have published 5948 publications receiving 47033 citations.

Zeolite encapsulated Ni(II) and Cu(II) complexes with tetradentate N2O2 Schiff base ligand: catalytic activity towards oxidation of benzhydrol and degradation of rhodamine-B

Abstract: Nickel(II) and copper(II) complexes of the Schiff base ligand O,O′-trimethyl bis (salicylidene isonicotinylhydrazone) (H2L) were synthesized and characterized. The encapsulation of these complexes in the cavities of the zeolite was achieved by a fixed ligand method (FLM). The free complexes (FC) and the retention of the zeolite encapsulated metal complexes [ZEMC; i.e., Ni(II)L–Y, Cu(II)L–Y] were investigated by several spectroscopic, thermal analysis, sorption and microscopic techniques [i.e., FTIR, NMR, ESI-mass, conductivity, DRS/UV-Vis, EPR, XPS, AAS, TGA, XRD, nitrogen isotherm, magnetic and (SEM/TEM)EDX]. This study reveals the formation and stability of the metal complexes in the cavities of the zeolite. The catalytic activities of free complexes and encapsulated complexes were studied in the liquid phase oxidation of benzhydrol/H2O2 and the photodegradation of rhodamine-B (RhB) under UV/visible (H2O2) irradiation. The catalytic activities of benzhydrol (BH) oxidation and RhB degradation were higher with free complexes and encapsulated complexes, respectively. In most cases, the copper(II) [Cu(II)L·2ClO4, Cu(II)L–Y] complexes showed better activity than the nickel(II) complexes [Ni(II)L·2ClO4, Ni(II)L–Y] in both BH and RhB degradation reactions. The enhancement of Cu(II)L–Y activity was mainly due to the metal present in the cavities and on the surface. Hence, in the case of FC, rate of the reaction (% of conversion) for the copper(II) complexes is more than that for nickel(II) in BH oxidation, but, in the case of ZEMC, the photocatalytic activity and rate of reaction (% of conversion) were more for Cu(II)L–Y than Ni(II)L–Y. These results show that both the oxidation reactions follow pseudo first order kinetics. The catalytic activities of the recovered and purified ZEMC were compared with the fresh catalyst.

Identification of Plant Disease using Image Processing Technique

Abstract: Agriculture has become far more than simply a method to feed ever growing populations. It’s important wherever in additional than seventieth population of an Asian country is depends on agriculture. Which means it feeds nice range of individuals. The foremost necessary consider less amount crop of quality because of disease. Detecting disease may be a key to stop agricultural losses. The aim of this project is to develop a software system answer that Mechanically find and classify disease. The step like loading an image, pre-Processing, Segmentation, extraction and classification are involves illness detection. The leaves pictures are used for detecting the plant diseases. Therefore use of image process technique to find and classify diseases in agricultural applications is useful.

SURFACE ROUGHNESS PARAMETERS OPTIMIZATION IN MACHINING A356/SiC/20p METAL MATRIX COMPOSITES BY PCD TOOL USING RESPONSE SURFACE METHODOLOGY AND DESIRABILITY FUNCTION

Abstract: The paper presents the experimental investigation on machining of fabricated silicon carbide particle reinforced aluminium metal matrix (A356/SiC/20p) composites by poly crystalline diamond (PCD) inserts. Experiments were conducted on lathe at various cutting conditions. The parameters considered for the experiments were cutting speed, feed and depth of cut. The response considered for the analysis was surface roughness. An empirical model has been developed for predicting the surface roughness in machining of A356/SiC/20p composites. Response surface regression and analysis of variance (ANOVA) are used in order to study the effects of machining parameters. Optimum machining condition for minimizing the surface roughness is determined using desirability function approach. The influences of different parameters in machining Al/SiC particulate composite have been analyzed in detail.