Ultrathin polyamide nanofiltration membrane prepared by triazine-based porous organic polymer as interlayer for dye removal

Separation membrane with high flux is generally encouraged in industrial application,because of the tremendous needs for decreasing membrane areas,usage costs and space requirements.The most effective and direct method for obtaining the high flux is to decrease membrane thickness.Polyamide(PA)nanofiltration membrane is conventionally prepared by the direct interfacial polymerization(IP)on substrate surface,and results in a thick PA layer.In this work,we proposed a strategy that constructing triazine-based porous organic polymer(TRZ-POP)as the interlayer to prepare the ultrathin PA nanofiltration membranes.TRZ-POP is firstly deposited on the polyethersulfone substrate,and then the formed TRZ-POP provides more adhesion sites towards PA based on its high specific surface areas.The chemical bonding between terminal amine group of TRZ-POP and the amide group of PA further improves the binding force,and strengthens the stability of PA layer.More importantly,the high porosity of TRZPOP layer causes the higher polymerization of initial PA owning to the stored sufficient amino monomer;and H-bonding interaction between amine groups of TRZ-POP and piperazine(PIP)can astrict the release of PIP.Thus,IP process is controlled,and the thinnest thickness of prepared PA layer is only<15 nm.As expected,PA/TRZ-POP membrane shows a more excellent water flux of 1414 L·m^(-2)·h^(-1)·MPa^(-1)than that of the state-of-the-art nanofiltration membranes,and without sacrificing dye rejection.The build of TRZPOP interlayer develops a new method for obtaining a high-flux nanofiltration membrane.

Dynamics and intermittent stochastic stabilization of a rumor spreading model with guidance mechanism in heterogeneous network

We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-prevailingequilibrium under R_(0)<1 and R_(0)>1 is carried out by Lyapunov method and LaSalle's invariant principle.Next,we design an aperiodically intermittent stochastic stabilization method to suppress the rumor propagation.By using the Ito formula and exponential martingale inequality,the expression of the minimum control intensity is calculated.This method can effectively stabilize the rumor propagation by choosing a suitable perturb intensity and a perturb time ratio,while minimizing the control cost.Finally,numerical examples are given to illustrate the analysis and method of the paper.

Segmentation of Hyper-Acute Ischemic Infarcts from Diffusion Weighted Imaging Based on Support Vector Machine

Accurate and automatic segmentation of hyper-acute ischemic infarct from magnetic resonance imaging is of great importance in clinical trials. Manual delineation is labor intensive, exhibits great variability due to unclear infarct boundaries, and most importantly, is not practical due to urgent time requirement for prompt therapy. In this paper, segmentation of hyper-acute ischemic infarcts from diffusion weighted imaging based on Support Vector Machine (SVM) is explored. Experiments showed that SVM could provide good agreement with manual delineations by experienced experts to achieve an average Dice coefficient of 0.7630.121. The proposed method could achieve significantly higher segmentation accuracy and could be a potential tool to assist clinicians for quantifying hyper-acute infarction and decision making especially for thrombolytic therapy.