A comparative study on aniline alkylation activity using methanol and dimethyl carbonate as the alkylating agents over Zn–Co–Fe ternary spinel systems

The catalyst compositions of the Zn1−xCOxFe2O4 (x= 0, 0.2, 0.5, 0.8 and 1.0) spiel series possessing ‘x’ values, x less than or equal to 0.5, are unique for selective N-monomethylation of aniline using methanol as the alkylating agent. Since dimethyl carbonate (DMC) is another potential non-toxic alkylating agent, alkylation of aniline was investigated over various Zn–Co ferrites using DMC as the alkylating agent. The merits and demerits of the two alkylating agents are compared. Catalytic activity followed a similar trend with respect to the composition of the ferrospinel systems. DMC is active at comparatively low temperature, where methanol shows only mild activity. However, on the selectivity basis, DMC as an alkylating agent could not compete with methanol, since the former gave appreciable amounts of N,N-dimethylaniline (NNDMA) even at low temperature where methanol gave nearly 99% N-methylaniline (NMA) selectivity. As in the case of methanol, DMC also did not give any C-alkylated products.

Present status of coral erosion in Lakshadweep with special reference to Minicoy

Coral Reefs are marine, biogenic, wave resistant carbonate structures, formed of the skeletal remains of hermatypic, or reef building organisms. The main reef builders are calcifying Rhodophytes, molluscs, sponges, polychaetes and Cnidarians. Among them, scleractinian corals and hydrocorallians are by far the most important contributors to the formation of reefs. Coral reefs cover approximately 600 thousand square kilometers of the earth's surface (Crossland fl a_1., 1991) which is about 2x106 square kilometres of tropical oceans.

A Multi-Objective Antenna Placement Genetic Algorithm for Matched Array Synthesis on Complex Platforms

A Multi-Objective Antenna Placement Genetic Algorithm (MO-APGA) has been proposed for the synthesis of matched antenna arrays on complex platforms. The total number of antennas required, their position on the platform, location of loads, loading circuit parameters, decoupling and matching network topology, matching network parameters and feed network parameters are optimized simultaneously. The optimization goal was to provide a given minimum gain, specific gain discrimination between the main and back lobes and broadband performance. This algorithm is developed based on the non-dominated sorting genetic algorithm (NSGA-II) and Minimum Spanning Tree (MST) technique for producing diverse solutions when the number of objectives is increased beyond two. The proposed method is validated through the design of a wideband airborne SAR