19,000 research outputs found

    UV-enhanced sacrificial layer stabilised graphene oxide hollow fibre membranes for nanofiltration

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    Graphene oxide (GO) membranes have demonstrated great potential in gas separation and liquid filtration. For upscale applications, GO membranes in a hollow fibre geometry are of particular interest due to the high-efficiency and easy-assembly features at module level. However, GO membranes were found unstable in dry state on ceramic hollow fibre substrates, mainly due to the drying-related shrinkage, which has limited the applications and post-treatments of GO membranes. We demonstrate here that GO hollow fibre membranes can be stabilised by using a porous poly(methyl methacrylate) (PMMA) sacrificial layer, which creates a space between the hollow fibre substrate and the GO membrane thus allowing stress-free shrinkage. Defect-free GO hollow fibre membrane was successfully determined and the membrane was stable in a long term (1200 hours) gas-tight stability test. Post-treatment of the GO membranes with UV light was also successfully accomplished in air, which induced the creation of controlled microstructural defects in the membrane and increased the roughness factor of the membrane surface. The permeability of the UV-treated GO membranes was greatly enhanced from 0.07 to 2.8 L m(−2) h(−1) bar(−1) for water, and 0.14 to 7.5 L m(−2) h(−1) bar(−1) for acetone, with an unchanged low molecular weight cut off (~250 Da)

    An asymptotic approximation scheme for the concave cost bin packing problem

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    Department of Logistics2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

    Scheduling with processing set restrictions : a survey

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    2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

    The Leverage Externalities of Credit Default Swaps

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    Interaction of O vacancies and domain structures in single crystal BaTi O3: Two-dimensional ferroelectric model

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    Two-dimensional simulations on the interactions of oxygen vacancies and different domain structures in barium titanate single crystal were carried out using the phase field method. The evolution of the spontaneous polarizations and oxygen vacancies was coupled through Maxwell's equation. The results showed that two barriers near the electrodes existed in both the 90°and 180°domain structures. It has also been observed that while an intrinsic electrostatic potential drop across the 90°domain wall created the electric fields which drove the electrons and oxygen vacancies aggregate on the different sides of the domain wall, the 180°domain wall had insignificant interaction with the potential, and no electron or vacancy accumulation in 180°domain structure was observed. Polarization charge density is believed to be the origin of this difference. © 2008 The American Physical Society.published_or_final_versio

    A Gaussian Bayesian model to identify spatio-temporal causalities for air pollution based on urban big data

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    Identifying the causalities for air pollutants and answering questions, such as, where do Beijing's air pollutants come from, are crucial to inform government decision-making. In this paper, we identify the spatio-temporal (ST) causalities among air pollutants at different locations by mining the urban big data. This is challenging for two reasons: 1) since air pollutants can be generated locally or dispersed from the neighborhood, we need to discover the causes in the ST space from many candidate locations with time efficiency; 2) the cause-and-effect relations between air pollutants are further affected by confounding variables like meteorology. To tackle these problems, we propose a coupled Gaussian Bayesian model with two components: 1) a Gaussian Bayesian Network (GBN) to represent the cause-and-effect relations among air pollutants, with an entropy-based algorithm to efficiently locate the causes in the ST space; 2) a coupled model that combines cause-and-effect relations with meteorology to better learn the parameters while eliminating the impact of confounding. The proposed model is verified using air quality and meteorological data from 52 cities over the period Jun 1st 2013 to May 1st 2015. Results show superiority of our model beyond baseline causality learning methods, in both time efficiency and prediction accuracy. © 2016 IEEE.postprintLink_to_subscribed_fulltex

    Real-time counting of single electron tunneling through a T-shaped double quantum dot system

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    Real-time detection of single electron tunneling through a T-shaped double quantum dot is simulated, based on a Monte Carlo scheme. The double dot is embedded in a dissipative environment and the presence of electrons on the double dot is detected with a nearby quantum point contact. We demonstrate directly the bunching behavior in electron transport, which leads eventually to a super-Poissonian noise. Particularly, in the context of full counting statistics, we investigate the essential difference between the dephasing mechanisms induced by the quantum point contact detection and the coupling to the external phonon bath. A number of intriguing noise features associated with various transport mechanisms are revealed.Comment: 8 pages, 5 figure
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