Please cite this article as: T.A. Khan, M. Nazir, I. Ali, A. Kumar, Removal of Chromium(VI) from aqueous solution using guar gum-nano zinc oxide biocomposite adsorbent, Arabian Journal of Chemistry (2013), doi: http:// dx. AbstractGuar gum-nano zinc oxide (GG/nZnO) biocomposite was used as adsorbent for enhanced removal of Cr(VI) from aqueous solution. The maximum adsorption was achieved at 50 min contact time, 25 mg/L Cr(VI) conc., 1.0 g/L adsorbent dose and 7.0 pH. Langmuir, Freundlich, Dubinin-Kaganer-Radushkevich and Temkin isotherm models were used to interpret the experimental data. The data obeyed both Langmuir and Freundlich models (R 2 =0.99) indicating multilayer adsorption of Cr(VI) onto the heterogeneous surface. The linear plots of Temkin isotherm showed adsorbent-adsorbate interactions. Moreover, the energy obtained from DKR isotherm (1.58-2.24 KJ/mol) indicated physical adsorption of the metal ions on the adsorbent surface, which implies more feasibility of the regeneration of the adsorbent. GG/nZnO biocomposite adsorbent showed improved adsorption capacity for Cr(VI) (q m = 55.56 mg/g) as compared to other adsorbents reported in the literature. Adsorption process followed pseudo-second order kinetics; controlled by both liquid-film and intra-particle diffusion mechanisms. Thermodynamic parameters (ΔG o , ΔH o and ΔS o ) reflected the feasibility, spontaneity and exothermic nature of adsorption. The results suggested that GG/nZnO biocomposite is economical, eco-friendly and capable to remove Cr(VI) from natural water resources.

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The recent advancements in technology in the wireless technology has led to rise of wearable antennas made of different fabrics. It is an unconventional antenna, meant to be a part of clothing and body. The radiating element is made of copper or any other conductor while the substrate used for wearable antenna application are textile or cloth based material. This literature review tends to reveal the various considerations for designing of wearable antenna from different textile materials and illustrates the effect of wearable antenna on human body and vice versa. These antennas have wide range of applications in the area of tracking, navigation, telemedicine, public safety and defence.

Abstract-Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose another algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

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