N-Doped hierarchical porous carbons with enhanced microporosity were prepared byin situintroduction of active site K+into MOF precursors.

A UiO-66-coated mesh membrane with micro- and nanostructures was designed and successfully fabricated on steel mesh through a simple solution immersion process, exhibiting hydrophilic and underwater superoleophobic properties. It displays an outstanding oil-water separation efficiency over 99.99% with a high water permeation flux of 12.7 × 10 L m h, so high purity water (with the residual oil content less than 4 ppm) can be readily obtained from such a simple mesh membrane from various oil-water mixtures. Its large-scale membrane production will facilitate its practical usage for the industrial and environmental water purification.

Plasmonic nanomaterials, along with their assemblies, provide numerous applications due to their profound optical properties. In this work, we report the self-assembly of Au@Ag core-shell nanocuboids (NCs) into staircase superstructures in both vertical and horizontal orientations through two-stage droplet evaporation. Each stair is composed of a uniform well-aligned monolayer of NCs. The gap distance between NCs can be greatly shrunk to boost the corresponding surface-enhanced Raman scattering (SERS) performance using an ethanol wash method. The SERS performance of the assembled NCs is calculated by finite-difference time-domain (FDTD) simulation, and studied against the step number using 4-mercaptobenzoic acid as a Raman reporter molecule. The increasing EF with the increase of layer number proves that the plasmon mode propagates well in our uniformly aligned assemblies.

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Hazard and operability analysis (HAZOP) is widely applied in petroleum industry as a scientific and effective safety analysis method, but it is traditionally qualitative in essence and hereby has such shortages as vague conclusions, susceptible to human factor, lack of comprehensive consideration, and so on. This paper proposed a dynamic simulation‐based quantitative HAZOP method that utilizes dynamic simulation to reason deviations to reduce uncertainty in manual analysis. It transforms deviations into quantitative dynamic tasks and uses these tasks to activate dynamic simulation for quantitative deviation reasoning work. The possible consequence and propagation time caused by deviation is probed by analyzing simulation results. In this process, some deviations that appeared seldom or did not at all before can also be simulated and analyzed with the aid of dynamic mechanism model. Case studies in extractive distillation and ammonia synthesis loop showed that this method can present propagation effect of key process parameters on safety state and is useful for iterative and automatic assessment work. It is also found that detailed operation and device data are necessary for initial complex process modeling. In addition, we should improve simulation platform to meet practical requirements when applying this method. © 2015 Curtin University of Technology and John Wiley & Sons, Ltd.