Removal of hexavalent chromium anions via polymer enhanced ultrafiltration using a fully ionized polyelectrolyte

A fully ionized polyelectrolyte was synthesized for Cr(VI) removal from aqueous solutions by continuous polymer enhanced ultrafiltration (PEUF). Effect of operating parameters such as pH, loading, polymer, and competing ion concentrations were examined. Highest Cr(VI) retention was obtained at a loading of 0.01 at pH 4. Increasing both polymer and chromate concentrations at a fixed loading of 0.01 decreased the retention which demonstrated the effect of crowding. In the presence of competing anions such as chloride and sulfate, Cr(VI) retention decreased for all of the pH values studied. Even at high competing anion concentrations, significant retentions of Cr (VI) were obtained.     

Biohydrometallurgy of secondary metal resources: a potential alternative approach for metal recovery

Research on biohydrometallurgy of secondary metal resources is primarily focused on the leaching of valuable metals. For secondary metal resources biological processing can be an economically more effective and environmentally friendlier alternative to traditional hydrometallurgical and pyrometallurgical processes. Therefore, biohydrometallurgy is a rapidly evolving biotechnology that has already provided revolutionary solutions to old problems associated with recovery of metals by conventional pyrometallurgy and chemical metallurgy. This review evaluates various processes of recovery of metals from waste materials and commercial applications are discussed. Case studies and future technology directions are reviewed. © 2013 Society of Chemical Industry     

Reactive red 120 and NI(II) derived poly(2‐hydroxyethyl methacrylate) nanoparticles for urease adsorption

Non‐porous poly(2‐hydroxyethyl methacrylate) [p(HEMA)] nanoparticles were prepared by surfactant free emulsion polymerization. The p(HEMA) nanoparticles was about 200 nm diameter, spherical form, and non‐porous. Reactive Red 120 (RR 120) was covalently attached to the p(HEMA) nanoparticles and Ni(II) ions were incorporated to attach dye molecules. Urease was immobilized onto RR120‐Ni(II) attached p(HEMA) nanoparticles via adsorption. The maximum urease adsorption capacity of RR120‐Ni(II) attached p(HEMA) nanoparticles was 480.01 mg g^?1 nanoparticles at pH 7.0 in phosphate buffer. It was observed that urease could be repeatedly adsorbed and desorbed without significant loss in adsorption amount. K_m values were 21.50 and 34.06 mM for the free and adsorbed enzyme. The V_max values were 4 U for the free enzyme and 3.3 U for the adsorbed enzyme. The optimum pH was 25 mM pH 7 phosphate buffer for free and adsorbed enzyme. The optimum temperature was determined at 35°C and 55°C for the free and adsorbed enzyme, respectively. These findings show considerable promise for this material as an adsorption matrix in biotechnological applications. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39757.     

Solving path problems on the GPU

We consider the computation of shortest paths on Graphic Processing Units (GPUs). The blocked recursive elimination strategy we use is applicable to a class of algorithms (such as all-pairs shortest-paths, transitive closure, and LU decomposition without pivoting) having similar data access patterns. Using the all-pairs shortest-paths problem as an example, we uncover potential gains over this class of algorithms. The impressive computational power and memory bandwidth of the GPU make it an attractive platform to run such computationally intensive algorithms. Although improvements over CPU implementations have previously been achieved for those algorithms in terms of raw speed, the utilization of the underlying computational resources was quite low. We implemented a recursively partitioned all-pairs shortest-paths algorithm that harnesses the power of GPUs better than existing implementations. The alternate schedule of path computations allowed us to cast almost all operations into matrix–matrix multiplications on a semiring. Since matrix–matrix multiplication is highly optimized and has a high ratio of computation to communication, our implementation does not suffer from the premature saturation of bandwidth resources as iterative algorithms do. By increasing temporal locality, our implementation runs more than two orders of magnitude faster on an NVIDIA 8800 GPU than on an Opteron. Our work provides evidence that programmers should rethink algorithms instead of directly porting them to GPU.     

Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The antecedent and conclusion parameters of neuro-fuzzy are determined by these algorithms. The data of a 250 W photovoltaic (PV) is used in the applications. For effective MPPT, different neuro-fuzzy structures, different membership functions and different control parameter values are evaluated in detail. Related training algorithms are compared in terms of solution quality and convergence speed. The strengths and weaknesses of these algorithms are revealed. It is seen that the type and number of membership function, colony size, number of generations affect the solution quality and convergence speed of the training algorithms. As a result, it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.     

Cut-on interference filter for the 8–11.7 μm region

The design and manufacture of a cut-on optical filter for the 8–11.7 μm region, fully blocked to uv, is described. The filter is composed of PbTe/ZnS symmetrical stacks deposited on two sides of a germanium substrate. Binder layers of Y₂O₃ between the multilayers and the substrate markedly improved the coating's environmental durability. A total of 30 layers was deposited and the average transmittance was 95% in the desired region.