Haocui Zhang

Bio: Haocui Zhang is an academic researcher from Dalian Institute of Chemical Physics. The author has contributed to research in topics: Volumetric flow rate & Carbon fibers. The author has an hindex of 2, co-authored 2 publications receiving 82 citations. Previous affiliations of Haocui Zhang include Chinese Academy of Sciences.

Hydrodynamics and mass transfer of gas–liquid flow in a falling film microreactor

Abstract: In this article, flow pattern of liquid film and flooding phenomena of a falling film microreactor (FFMR) were investigated using high-speed CCD camera. Three flow regimes were identified as ‘‘corner rivulet flow,’’ ‘‘falling film flow with dry patches,’’ and ‘‘complete falling film flow’’ when liquid flow rate increased gradually. Besides liquid film flow in microchannels, a flooding presented as the flow of liquid along the side wall of gas chamber in FFMR was found at high liquid flow rate. Moreover, the flooding could be initiated at lower flow rate with the reduction of the depth of the gas chamber. CO2 absorption was then investigated under the complete falling flow regime in FFMR, where the effects of liquid viscosity and surface tension on mass transfer were demonstrated. The experimental results indicate that kL is in the range of 5.83 to 13.4 � 10 � 5 ms � 1 and an empirical correlation was proposed to predict kL in FFMR.

Highly dispersible cerium-oxide modified Ni/SBA-15 for steam reforming of bio-mass based JP10

Abstract: Ni/SBA-15 modified by highly dispersed cerium-oxide was prepared with the aid of sucrose for steam reforming of JP10 (C10H16). Their characterization showed that addition of appropriate amount ceria led to the formation of highly dispersed CeO2 and Ni, and the CeO2 covered smaller nickel particles like strawberry seeds to form much more interface between them. Their catalytic activity exhibited higher stability over time on stream of 6.5 h with conversion higher than 95% and higher carbon resistance (mass loss less than 4.5% by TG), which may derive from good properties below: (1) much more interface enhanced cooperation effect and increased turnover frequency at the interface; (2) the stronger interaction between Ni and ceria to suppress sintering by formation of Ni-O-Ce solid solution; (3) the large amount of oxygen vacancies from the formation of Ni-O-Ce solid solution and highly dispersed CeO2 to facilitate the water–gas–shift reaction and carbon removal.

Hydrodynamics and Mass Transfer in Gas-Liquid Flows in Microreactors

Abstract: Over the last ten to fifteen years, microreaction echnology has become of increased interest to both academics and industrialists for intensification of multiphase processes. Amongst the vast application possibilities, fast, highly exothermic and/or mass transfer-limited gas-liquid reactions benefit from process miniaturization. Recent studies of hydrodynamics and mass transfer in gas-liquid microreactors with closed and open microchannels, e.g., falling-film microreactors, are reviewed and compared. Special attention is paid to Taylor or slug flow in closed channels, as this regime seems to be most adapted for practical engineering applications.

Gas–Liquid Reactions

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High-throughput microporous tube-in-tube microreactor as novel gas–liquid contactor: Mass transfer study

Abstract: High-throughput microporous tube-in-tube microchannel reactor (MTMCR) was first designed and developed as a novel gas–liquid contactor. Experimentally measured kLα in MTMCR is at least one or two orders of magnitude higher than those in the conventional gas–liquid contactors. A high throughput of 500 L/h for gas and 43.31 L/h for liquid is over 60 times higher than that of T-type microchannel. An increase of the gas or liquid flow rate, as well as a reduction of the micropore size and annular channel width of MTMCR, could greatly intensify the gas–liquid mass transfer. The interfacial area, α, in MTMCR was measured to be as high as 2.2 × 105 m2/m3, which is much higher than those of microchannels (3400–9000 m2/m3) and traditional contactors (50–2050 m2/m3). The artificial neural network model was proposed for predicting α, revealing only an average absolute relative error of <5%. © 2010 American Institute of Chemical Engineers AIChE J, 2011