Gas-Liquid Flow and Interphase Mass Transfer in LL Microreactors

This work investigates the impact of fluid (CO2(g), water) flow rates, channel geometry, and the presence of a surfactant (ethanol) on the resulting gas–liquid flow regime (bubble, slug, annular), pressure drop, and interphase mass transfer coefficient (kla) in the FlowPlateTM LL (liquid-liquid) microreactor, which was originally designed for immiscible liquid systems. The flow regime map generated by the complex mixer geometry is compared to that obtained in straight channels of a similar characteristic length, while the pressure drop is fitted to the separated flows model of Lockhart–Martinelli, and the kla in the bubble flow regime is fitted to a power dissipation model based on isotropic turbulent bubble breakup. The LL-Rhombus configuration yielded higher kla values for an equivalent pressure drop when compared to the LL-Triangle geometry. The Lockhart–Martinelli model provided good pressure drop predictions for the entire range of experimental data (AARE < 8.1%), but the fitting parameters are dependent on the mixing unit geometry and fluid phase properties. The correlation of kla with the energy dissipation rate provided a good fit for the experimental data in the bubble flow regime (AARE < 13.9%). The presented experimental data and correlations further characterize LL microreactors, which are part of a toolbox for fine chemical synthesis involving immiscible fluids for applications involving reactive gas–liquid flows

Modelling and Design of a Novel Integrated Heat Exchange Reactor for Oxy-Fuel Combustion Flue Gas Deoxygenation

The concentration of residual O2 in oxy-fuel combustion flue gas needs to be reduced before CO2 transportation, utilization, or storage. An original application of the printed circuit heat exchanger (PCHE) for catalytic combustion with natural gas (catalytic deoxygenation) is described for reducing the residual O2 concentration. The PCHE design features multiple adiabatic packed beds with interstage cooling and fuel injection, allowing precise control over the reaction extent and temperature within each reaction stage through the manipulation of fuel and utility flow rates. This work describes the design of a PCHE for methane–oxygen catalytic combustion where the catalyst loading is minimized while reducing the O2 concentration from 3 vol% to 100 ppmv, considering a maximum adiabatic temperature rise of 50 °C per stage. Each PCHE design differs by the number of reaction stages and its individual bed lengths. As part of the design process, a one-dimensional transient reduced-order reactor model (1D ROM) was developed and compared to temperature and species concentration axial profiles from 3D CFD simulations. The final design consists of five reaction stages and four heat exchanger sections, providing a PCHE length of 1.09 m at a processing rate of 12.3 kg/s flue gas per m3 PCHE

Understanding membrane selectivity in pervaporation of water-rich water:ethanol mixtures

In pervaporation, membrane selectivity is defined as the ratio of the ratios of two components of a liquid:liquid mixture in the permeate and in the feed. In a thermodynamically-controlled system, this value will be the same as the difference between vapour and liquid composition in the absence of a membrane. We demonstrate this to be the case for water:ethanol pervaporation at high water:ethanol ratios both for an unmodified polydimethylsiloxane membrane and for a membrane modified by grafting a layer of hydrophilic polyacrylamide. We observe transient kinetic deviations toward greater selectivity on addition of salts which push the thermodynamic vapour pressure equilibrium towards ethanol, and to a more significant degree with grafting of polyacrylamide to the hydrophobic membrane, suggesting that these modifications retard the flow of water through the membrane. The physical plausibility of the chemical potential gradient used in interpretation of pervaporation data by the solutiondiffusion model is critiqued

A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM_2.5 in Halifax, Nova Scotia during the BORTAS-B experiment

This paper presents a quantitative comparison of the four most commonly used receptor models, namely absolute principal component scores (APCS), pragmatic mass closure (PMC), chemical mass balance (CMB) and positive matrix factorization (PMF). The models were used to predict the contributions of a wide variety of sources to PM2.5 mass in Halifax, Nova Scotia during the experiment to quantify the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS). However, particular emphasis was placed on the capacity of the models to predict the boreal wildfire smoke contributions during the BORTAS experiment. The performance of the four receptor models was assessed on their ability to predict the observed PM2.5 with an R2 close to 1, an intercept close to zero, a low bias and low RSME. Using PMF, a new woodsmoke enrichment factor of 52 was estimated for use in the PMC receptor model. The results indicate that the APCS and PMC receptor models were not able to accurately resolve total PM2.5 mass concentrations below 2 μg m−3. CMB was better able to resolve these low PM2.5 concentrations, but it could not be run on 9 of the 45 days of PM2.5 samples. PMF was found to be the most robust of the four models since it was able to resolve PM2.5 mass below 2 μg m−3, predict PM2.5 mass on all 45 days and utilise an unambiguous woodsmoke chemical tracer. The median woodsmoke relative contributions to PM2.5 estimated using PMC, APCS, CMB and PMF were found to be 0.08, 0.09, 3.59 and 0.14 μg m−3 respectively. The contribution predicted by the CMB model seemed to be clearly too high based on other observations. The use of levoglucosan as a tracer for woodsmoke was found to be vital for identifying this source