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Low transition temperature mixtures (LTTMs) are versatile alternatives to ILs. They share many properties with ILs, so they become a suitable choice for entrainers in extractive distillation processes. In this study, glycolic acid and choline chloride in a 3:1 molar ratio (GC3:1) were synthesized and explored as entrainers for separation of acetonitrile + water azeotropic mixtures. Isobaric vapor−liquid equilibrium data for the pseudobinary mixtures of ACN + GC3:1 and water + GC3:1 were measured at atmospheric pressure (101.32 kPa). For the pseudoternary system ACN + water + GC3:1, also VLE data were measured at different GC3:1 mole fractions of 0.05, 0.1, and 0.15. The thermodynamic modeling of these systems was performed using the nonrandom two-liquid (NRTL) model. Furthermore, a study was conducted for synthesized GC3:1 recoverability. A good agreement were found between experimental data and predicted values for these systems. Results showed that LTTM (GC3:1) eliminated the acetonitrile + water azeotrope by manipulating the relative volatility of the acetonitrile + water mixture. Therefore, LTTM (GC3:1) can be concluded as an efficient entrainer for the separation of an acetonitrile + water azeotropic mixture by extractive distillation.

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The present work describes the tunable emission in inorganic-organic hybrid NPs which can be useful for optoelectronic and biosensing applications. In this work, Mn-ZnS nanoparticles emitting various colors, including blue and orange, were synthesized by simple chemical precipitation method using chitosan as a capping agent. Earlier reports describe that emission color characteristics in nanoparticles are tuned by varying particle size and with doping concentration. Here in this article tunable emission has been achieved by varying excitation wavelength in a single sample. This tunable emission property with high emission intensity was further achieved by changing capping concentration keeping host Mn-ZnS concentration same. Tunable emission is explained by FRET mechanism. Commission Internationale de l'Eclairage (CIE) chromaticity coordinates shifts from (0.273, 0.20) and (0.344, 0.275) for same naocrystals by suitably tuning excitation energy from higher and lower ultra-violet (UV) range. Synthesized nanoparticles have been characterized by X-ray diffraction, SEM, HRTEM, UV-Visible absorption and PL spectroscopy for structural and optical studies. Using tunable emission property, these highly emissive nanoparticles functionalized with biocompatible polymer chitosan were further used for glucose sensing applications. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License.

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C loud providers such as Amazon, IBM, and Microsoft are leasing their computing resources to various businesses providing them an alternative to investing in expensive hardware. Although recent information systems research has examined pricing-related issues in cloud computing, several important questions still remain. For example, how should buyers decide on the capacity portfolio of private and public clouds? What is the impact of the buyer's demand uncertainty on the capacity portfolio decision? We address these questions in this study through a stylized model. Our analysis reveals that the investment in cloud infrastructure (private, public or hybrid) is based on the profile of the buyer's demand. When a buyer faces demand with low mean, she relies on public cloud solutions. If the demand has high mean, then the buyer firm hosts applications on a private cloud. Implementing a hybrid cloud is the optimal strategy when the mean demand is in mid-range. We find that high demand variability makes businesses to move toward public cloud solutions. We support these insights through examples from practice in the cloud computing industry.