Ultrasonic spray pyrolysis synthesis of Ag/TiO2 nanocomposite photocatalysts for simultaneous H2 production and CO2 reduction

Simultaneous photocatalytic hydrogen production and CO₂ reduction (to form CO and CH₄) from water using methanol as a hole scavenger were investigated using silver-modified TiO₂ (Ag/TiO₂) nanocomposite catalysts. A simple ultrasonic spray pyrolysis (SP) method was used to prepare mesoporous Ag/TiO₂ composite particles using TiO₂ (P25) and AgNO₃ as the precursors. The material properties and photocatalytic activities were compared with those prepared by a conventional wet-impregnation (WI) method. It was found that the samples prepared by the SP method had a larger specific surface area and a better dispersion of Ag nanoparticles on TiO₂ than those prepared by the WI method, and as a result, the SP samples showed much higher photocatalytic activities toward H₂ production and CO₂ reduction. The optimal Ag concentration on TiO₂ was found to be 2 wt%. The H₂ production rate of the 2% Ag/TiO₂–SP sample exhibited a six-fold enhancement compared with the 2% Ag/TiO₂–WI sample and a sixty-fold enhancement compared with bare TiO₂. The molar ratio of H₂ and CO in the final products can be tuned in the range from 2 to 10 by varying the reaction gas composition, suggesting a viable way of producing syngas (a mixture of H₂ and CO) from CO₂ and water using the prepared Ag/TiO₂ catalysts with energy input from the sun.     

Measuring and comparing service quality metrics through social media analytics: a case study

This paper proposes a framework of using social media analytics to help study service quality. A case study was conducted to collect and analyze a data set which included nearly half million tweets related to two of the largest supermarkets in the United States: Walmart and Kmart. The results illustrate how businesses can leverage external open data to complement the traditional survey-based approaches in order to better understand and measure their service quality metrics by studying the online opinions of their customers.     

Nano and Microtechnologies for the Study of Magnetotactic Bacteria

Magnetotactic bacteria (MTB) naturally synthesize magnetic nanoparticles that are wrapped in lipid membranes. These membrane‐bound particles, which are known as magnetosomes, are characterized by their narrow size distribution, high colloidal stability, and homogenous magnetic properties. These characteristics of magnetosomes confer them with significant value as materials for biomedical and industrial applications. MTB are also a model system to study key biological questions relating to formation of bacterial organelles, metal homeostasis, biomineralization, and magnetoaerotaxis. The similar size scale of nano and microfluidic systems to MTB and ease of coupling to local magnetic fields make them especially useful to study and analyze MTB. In this Review, a summary of nano‐ and microtechnologies that are developed for purposes such as MTB sorting, genetic engineering, and motility assays is provided. The use of existing platforms that can be adapted for large‐scale MTB processing including microfluidic bioreactors is also described. As this is a relatively new field, future synergistic research directions coupling MTB, and nano‐ and microfluidics are also suggested. It is hoped that this Review could start to bridge scientific communities and jump‐start new ideas in MTB research that can be made possible with nano‐ and microfluidic technologies.     

Elimination of Perfluorinated Surfactants – Adsorbent Evaluation Applying Surface Tension Measurements

The adsorption of perfluorooctane sulfonate (PFOS) onto activated carbons, nonfunctionalized polymeric adsorbents, and anion exchange resins was evaluated in batch as well as column experiments. It was found that the total PFOS capacity, adsorption kinetics, breakthrough times, and minimum effluent concentrations were highly dependent on the material properties, such as the inner surface area, pore size, functionalization, and hydrophobic character of the material, and on process parameters like temperature and ionic strength of the solution. The experiments furthermore revealed that surface tension measurements are a suitable method for online determination of PFOS concentrations above a defined value.     

Spatial competition and flexible manufacturing with spatially discriminatory pricing

This paper develops a two-dimensional spatial framework, in which firms have the technique of flexible manufacturing and engage in spatially discriminatory pricing, in order to explore the firms’ optimal locations and optimal attributes of basic products under linear transportation costs. The paper shows that the two firms will agglomerate at the center of the location line and the optimal attributes of the two basic products will be located at the first and third quartiles of the attribute line, respectively, when the ratio of the marginal modification rate to the transport rate is high. It also shows that the two firms will locate separately on the location line and that the optimal attributes of the two basic products will remain at the first and third quartiles, when this ratio is moderate. Moreover, this paper proves that the two firms will locate at the first and third quartiles of the location line, respectively, and that the attributes of the basic products will agglomerate at the center of the attribute line, when this ratio is low.     

Hardware architecture of the Protein Processing Associative Memory and the effects of dimensionality and quantisation on performance

The Protein Processor Associative Memory (PPAM) is a novel hardware architecture for a distributed, decentralised, robust and scalable, bidirectional, hetero-associative memory, that can adapt online to changes in the training data. The PPAM uses the location of data in memory to identify relationships and is therefore fundamentally different from traditional processing methods that tend to use arithmetic operations to perform computation. This paper presents the hardware architecture and details a sample digital logic implementation with an analysis of the implications of using existing techniques for such hardware architectures. It also presents the results of implementing the PPAM for a robotic application that involves learning the forward and inverse kinematics. The results show that, contrary to most other techniques, the PPAM benefits from higher dimensionality of data, and that quantisation intervals are crucial to the performance of the PPAM.