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A surface-active and "green" flooding agent, modified nanocellulose (NC), which is expected to be an alternative to the current flooding systems for enhancing oil recovery (EOR), was provided in this work. The physical properties of the NC samples including dispersity, rheology, phase behavior, emulsifiability, etc., as a function of mass fraction and charge density, were comprehensively studied to evaluate their EOR potential. The results indicate that this modified nanomaterial could be well dispersed in 1 wt % NaCl brine, forming a series of homogeneous nanofluids at the concentration above 0.4 wt %. Rheological analysis evidenced the viscoelastic properties and pronounced shear-thinning behavior of the nanofluids. Because of the presence of the active groups, the dynamic interfacial tension (Oil/Nanofluid) decreased to an order of 10 −1 mN/m, which accordingly promotes the microscopic recovery efficiency through an emulsification effect. It was also observed that the emulsifiability of the nanofluids was closely related to the charge density. Visual EOR experiments were conducted in a micromodel, from which two mechanisms, (1) sweep volume improvement and (2) emulsification and entrainment, were established for NC nanofluid flooding. As an eco-friendly material, this nanofluid is supposed to be a promising flooding agent in the near future.

Atomically dispersed gold supported on nanoscale ZnZrOx composite oxides was prepared and investigated in this work as a catalyst for the low-temperature ethanol dehydrogenation reactions. The composite ZnZrOx support disperses gold atomically and stabilizes it against growth much better than either of the neat oxides. Sequential ethanol conversion reactions to acetaldehyde and acetone take place on the Au/ZnZrOx catalysts within well-separated temperature windows over the range of tested temperatures (30-400 °C). ZnO modulates the acidity of the ZrO2 surface, and the extent of this was followed by isopropanol temperature-programmed desorption with online mass spectrometry (IPA-TPD/MS; and by diffuse reflectance UV-Vis-IR). Catalyst activity and selectivity were tested by temperature-programmed surface reaction (TPSR) and under steady-state reaction conditions. The work has demonstrated that ZnZrOx with optimized ZnO distribution preserves the active Au-Ox surface species under reaction conditions and suppresses undesired dehydration reactions. Addition of gold on the bare zirconia support passivates the acid sites catalyzing ethanol dehydration and introduces desired dehydrogenation sites at low temperatures (200 °C)

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.