Functionalization of gold nanorod (GNR) with dimercaptosuccinic acid is reported as a way to develop a sensor, GNR-PEG-DMSA that can rapidly detect very low concentrations of arsenic contamination in water and using the paper strip. The sensor is developed by stepwise chemical conjugations of gold nanorods (GNR) with poly­(ethylene glycol) methyl ether thiol (mPEG-SH) followed by meso-2,3-dimercaptosuccinic acid (DMSA). GNR-PEG-DMSA shows a visible color change in the presence of both inorganic forms of arsenic: AsIII (arsenite) and AsV (arsenate) ions in solution and on a paper substrate, because of the ion-induced aggregation of nanorods through an arsenic complex formation strategy, which is relative to the arsenic concentrations. Colorimetric and spectroscopic analyses are very much selective for both AsIII and AsV ions with a detection limit of ∼1.0 ppb. In addition, the GNR-PEG-DMSA exhibits excellent potential for quantitative estimation of total arsenic in groundwater samples. The paper-based sensing method demonstrates the usefulness in arsenic level screening under field-test mode.

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In the present work, tungsten carbide (WC) particulate of average size 10 mm were electrocodeposited in the nickel metal matrix, to form metal matrix composite (MMC) coating over the EN8 steel substrate. The electrodeposition of Ni-WC particulate composite coating was carried out using the Watt's bath under the influence of varying current density and duty cycle. It was found that current density of 0.02 A/ cm 2 was sufficient to start the codeposition kinetics. But, good quality of electrodeposition was obtained at a current density of 0.04 A/cm 2 . The WC particulate entrapment and distribution of WC particles in Ni matrix according the variation in experimental parameters has been reported. The dense and compact microstructure was obtained at a current density of 0.04 A/cm 2 and duty cycle of 30%. Microhardness and corrosion resistance properties of composite coating were also evaluated and reported. INTRODUCTIONSurface modification, with the formation=deposition of overlaying layer of metal matrix composite (MMC), provides enhanced mechanical, tribological, and corrosion resistance properties. During the last few decades, researchers have attempted to improve those properties through electrocodeposition of hard particles such as Al 2 O 3 [1-4], TiO 2 [5, 6], SiC [7-9], ZrO 2 [10, 11], WS 2 [12], and Si 3 N 4 [13,14] in different metal matrixes (Ni, Cr, Co, etc.). Nickel is a most suitable metal, among all metal matrixes due to its good chemical compatibility with the other metal and alloys [18]. Moreover, it imparts very good corrosion resistance property to the coated surface. Tungsten carbide is a hard ceramic having high thermal stability and good dispersion properties which lead to high wear and thermal resistance properties of the coating. Deposition of electrically nonconductive tungsten carbide particles alone is very difficult, as it produces obstruction to obtain dense interface of metal-carbide during the electrodeposition process, but it can be easily codeposited with a transition group of elements. Although there are a number of surface coating techniques available, but the electrodeposition process has drawn significant attention because it is a nonthermal process, technologically feasible, easily controllable, economically superior technique to produce a MMC. It is based on the uniform entrapment of second-phase hard particles within the metal matrix.Although many research papers have been reported in the area of WC composite coating through direct current

Tooling is an essential element of near net shape manufacturing processes such as injection molding and die casting, where it may account for over 25% of the total product cost and development time, especially when order quantity is small. Development of rapid and low cost tooling, combined with a scientific approach to mold cost estimation and control, has therefore become essential. This paper presents an integrated methodology for die and mold cost estimation, based on the concept of cost drivers and cost modifiers. Cost drivers include the geometric features of cavity and core, handled by analytical cost estimation approach to estimate the basic mold cost. Cost modifiers include tooling parameters such as parting line, presence of side core(s), surface texture, ejector mechanism and die material, contributing to the total mold cost. The methodology has been implemented and tested using 13 industrial examples. The average deviation was 0.40%. The model is flexible and can be easily implemented for estimating the cost of a variety of molds and dies by customizing the cost modifiers using quality function deployment approach, which is also described in this paper.