Visualization of Multiphase Reactive Flow and Mass Transfer in Functionalized Microfluidic Porous Media.

Multiphase reactive flow in porous media is an important research topic in many natural and industrial processes. In the present work, photolithography is adopted to fabricate multicomponent mineral porous media in a microchannel, microfluidics experiments are conducted to capture the multiphase reactive flow, methyl violet 2B is employed to visualize the real-time concentration field of the acid solution and a sophisticated image processing method is developed to obtain the quantitative results of the distribution of different phases. With the advanced methods, experiments are conducted with different acid concentration and inlet velocity in different porous structures with different phenomena captured. Under a low acid concentration, the reaction will be single phase. In the gaseous cases with higher acid concentration, preferential flow paths with faster flow and reaction are formed by the multiphase hydrodynamic instabilities. In the experiments with different inlet velocities, it is observed that a higher inlet velocity will lead to a faster reaction but less gas bubbles generated. In contrast, more gas bubbles would be generated and block the flow and reaction under a lower inlet velocity. Finally, in heterogeneous structures, fractures or cavities would significantly redirect the flow and promote the formation of preferential flow path nearby.

Diffusion Behavior of VOC Molecules in Polyvinyl Chloride Investigated by Molecular Dynamics Simulation.

Due to the threats posed by many volatile organic compounds (VOCs) to human health in indoor spaces via air, the mass transfer characteristics of VOCs are of critical importance to the study of their mechanism and control. As a significant part of the mass transfer process, diffusion widely exists in emissions from floors (e.g., PVC floors) and in sorption in porous materials. Molecular simulation studies by can provide unparalleled insights into the molecular mechanisms of VOCs. We construct the detailed atomistic structures of PVC blend membranes to investigate the diffusion behavior of VOC molecules (n-hexane) in PVC by molecular dynamics (MD). The variation in the diffusion coefficient of n-hexane in PVC with respect to temperature is in line with Arrhenius' law. The effect of temperature on the diffusion mechanism was investigated from the perspectives of free volume, cavity distribution and polymer chain mobility. It was found that the relationships between the diffusion coefficients of n-hexane in the polymer and the inverse fractional free volume are exponential and agree well with the free volume theory. Hopefully, this study will offer quantitative insights into the mass transport phenomena of VOCs within polymeric materials.

Porous Flow Field for Next-Generation Proton Exchange Membrane Fuel Cells: Materials, Characterization, Design, and Challenges.

Porous flow fields distribute fuel and oxygen for the electrochemical reactions of proton exchange membrane (PEM) fuel cells through their pore network instead of conventional flow channels. This type of flow fields has showed great promises in enhancing reactant supply, heat removal, and electrical conduction, reducing the concentration performance loss and improving operational stability for fuel cells. This review presents the research and development progress of porous flow fields with insights for next-generation PEM fuel cells of high power density (e.g., ∼9.0 kW L-1). Materials, fabrication methods, fundamentals, and fuel cell performance associated with porous flow fields are discussed in depth. Major challenges are described and explained, along with several future directions, including separated gas/liquid flow configurations, integrated porous structure, full morphology modeling, data-driven methods, and artificial intelligence-assisted design/optimization.

Projection Diagram for Determining Polarization Curves under Variation of Activation Criterion Using Similarity Theory.

Revealing the correlation between polarization curve and input parameters is a highly concerned topic in proton exchange membrane fuel cell (PEMFC) research. Till now, three-dimensional (3D) numerical models have been the most comprehensive methods to predict the polarization curve under variational conditions. However, due to the diversity and complexity of the parameters involved, an immense numerical or experimental burden is required to obtain the above-referred correlation based on 3D numerical model. Application of the similarity theory is considered as a promising breakthrough in PEMFC research to obtain generalized and compact laws. Activation criterion, a relative magnitude of the effect of temperature on electrochemical reaction rate versus the effect of activation overpotential, is the most important criterion on the PEMFC performance. Revealing its impact on the dimensionless polarization curve in the aspects of slope, intercept, and curvature is one of the major challenges for further investigation. Herein, a projection diagram is proposed to determine polarization curves under variation of activation criterion using similarity theory based on a series of results with other criteria variation. As a validation of the concept, two scenarios are exhibited by numerical approach. Results suggest that the maximum relative deviation of polarization curves predicted by the projection diagram is 0.14%, which reaches a high accuracy. The projection diagram reveals the reason why the activation criterion has a comprehensive and complex impact on the dimensionless polarization curve.

Effects of Radiant Floor Heating Integrated with Natural Ventilation on Flow and Dispersion in a Newly Decorated Residence.

To date, few studies have been conducted on the characteristics of flow and dispersion caused by indoor radiant floor heating integrated with natural ventilation. In this study, we employed reduced-scale numerical models validated by wind-tunnel experiments to investigate the influence of radiant floor heating integrated with natural ventilation on airflow, heat transfer, and pollutant dispersion within an isolated building. The Richardson number (Ri) was specified to characterize the interaction between the inflow inertia force and the buoyancy force caused by radiant floor heating. Several Ri cases from 0 to 26.65, coupled with cross- or single-sided ventilation, were considered. Model validation showed that the numerical model coupled with the RNG k-ε model was able to better predict the indoor buoyant flow and pollutant dispersion. The results showed that the similarity criterion of Ri equality should be first satisfied in order to study indoor mixed convection using the reduced-scale model, followed by Re-independence. For cross-ventilation, when Ri < 5.31, the incoming flow inertia force mainly dominates the indoor flow structure so that the ACH, indoor temperature, and pollutant distributions remain almost constant. When Ri > 5.31, the thermal buoyancy force becomes increasingly important, causing significant changes in indoor flow structures. However, for single-sided ventilation, when Ri > 5.31 and continues to increase, the buoyancy force mainly dominates the indoor flow structure, causing a significant increase in ACH, thus reducing the indoor average temperature and pollutant accumulation.

Numerical studies on issues of Re-independence for indoor airflow and pollutant dispersion within an isolated building.

This study conducted the numerical models validated by wind-tunnel experiments to investigate the issues of Re-independence of indoor airflow and pollutant dispersion within an isolated building. The window Reynolds number (Re w ) was specified to characterize the indoor flow and dispersion. The indicators of RRC (ratio of relative change) or DR (K_DR) (difference ratio of dimensionless concentration) ≤ 5% were applied to quantitatively determine the critical Re w for indoor flow and turbulent diffusion. The results show that the critical Re (Re crit) value is position-dependent, and Re crit at the most unfavorable position should be suggested as the optimal value within the whole areas of interest. Thus Re H,crit = 27,000 is recommended for the outdoor flows; while Re w,crit = 15,000 is determined for the indoor flows due to the lower part below the window showing the most unfavorable. The suggested Re w,crit (=15,000) for indoor airflow and cross ventilation is independence of the window size. Moreover, taking K_DR ≤ 5% as the indicator, the suggested Re w,crit for ensuring indoor pollutant diffusion enter the Re-independence regime should also be 15,000, indicating that indoor passive diffusion is completely determined by the flow structures. The contours of dimensionless velocity (U/U 0) and concentration (K) against the increasing Re w further confirmed this critical value. This study further reveals the Re-independence issues for indoor flow and dispersion to ensure the reliability of the data obtained by reduced-scale numerical or wind-tunnel models.

Three-dimensional non-isothermal numerical model for predicting semi-volatile organic compound transport process in a room.

In this paper, a three-dimensional non-isothermal computational model for predicting indoor SVOC distribution is proposed, considering the effects of turbulence diffusion and suspended particles. The realizable k-ε model is introduced for turbulent flow simulation in a room. The Euler-Euler method is adopted to deal with the gas-particle two-phase flow coupled problem. Inertia slip velocity and irreversible first-order absorption boundary are employed for more accurate prediction of particle motion. The simulated curve of outlet gas-phase di-2-ethylhexyl phthalate (DEHP) concentration with emission time is verified by available experimental data. The emission process of DEHP in a 15 m2 room in Beijing during 100 days with or without air cleaner is simulated by the developed model considering air leak through window and door gaps. It is found that if the air cleaner keeps on all the time during 100 days the gas-phase DEHP concentration in the room will tend to be uniform, while the emission process is far from equilibrium without an air cleaner even the emission lasts 100 days. Results also suggest that floor heating, decrease of particle concentration, weaken of heat transfer, enhancement of mass transfer, and air infiltration in window gap contribute to decrease DEHP concentration.

Advanced carbon sequestration by the hybrid system of photobioreactor and microbial fuel cell with novel photocatalytic porous framework.

A new hybrid system is proposed to capture CO2 as well as generate electricity with the low CO2 inlet condition of confined space. Within the system, a novel photocatalytic porous framework coated by g-C3N4/TiO2 is prepared to avoid the inhibition of microalgae growth caused by the direct addition of photocatalyst. Under 0.8% v/v CO2 inlet condition, chemical oxygen demand (COD) yields from the photocatalytic framework immersed in the phosphate buffer and the algae suspension are 1.63 mg L-1 h-1 and 1.90 mg L-1 h-1, respectively. CO2 sequestration rate of a 60L cylindrical photobioreactor increases from 12% to 22%. The combination modes between photobioreactor and photocatalytic framework can be selected flexibly depends on the demands of application. This hybrid system not only benefits to enhance the CO2 sequestration rate of photobioreactor but also has the potential to be served as the power source in a confined space.

How different freezing morphologies of impacting droplets form.

HYPOTHESIS: Freezing morphologies of impacting water droplets depend on the interaction between droplet spreading and solidification. The existing studies showed that the shape of frozen droplets mostly is of spherical cap with a singular tip, because of much shorter timescale of the droplet spreading than that of the solidification. Here, we create the experimental conditions of extended droplet spreading and greatly enhanced heat transfer for fast solidification, thereby allowing to study such droplet freezing process under the strong coupling of the droplet spreading and solidification. EXPERIMENTS: We design experiments that a room-temperature water droplet impacts on a subcooled superhydrophilic surface in an enclosure chamber filled with nitrogen gas. We thoroughly investigate the freezing processes of impacting droplets under the effects of impact velocity and substrate temperature. Both the droplet impact dynamics and solidification are studied with a high-speed camera. FINDINGS: We observed five different freezing morphologies which depend on the droplet impact velocity and substrate temperature. We found that the formation of diverse morphologies results from the competitive timescales related to droplet solidification and impact hydrodynamics. We also develop a phase diagram based on scaling analysis and show how freezing morphologies are controlled by droplet impact and freezing related timescales.

Molecular Dynamics Study of Bubble Nucleation on an Ideally Smooth Substrate.

Questions regarding bubble nucleation on an ideally smooth surface are seemingly endless, but it can not be adequately verified yet because of the scale limitation (microscopic scale). Hence, in this study, bubble nucleation on an ideally smooth substrate is explored using the molecular dynamics simulation method. An ideally smooth hydrophilic platinum substrate at 145 K is conducted to heat the simple L-J liquid argon. Results show that a visible bubble nucleus successfully forms on the ideally smooth substrate without any additional disturbance, which is common in boiling studies using the traditional numerical simulation methods. However, the nucleation position is unpredictable. At the atomic level, the thermal energy transfer from an ideally smooth substrate to liquid atoms is inhomogeneous due to atomic inhomogeneous distribution and irregular movement, which are the key influencing factors for achieving bubble nucleation. The inhomogeneity will be highlighted with the heating process. As a result, some local liquid atoms near the ideally smooth surface absorb more thermal energy to overcome their potential barrier at a specific moment, causing the emergence of a distinct nucleus there. Furthermore, nanostructure substrates are introduced to make a comparison with the smooth substrate in bubble nucleation. There is no significant difference in the inception temperature of nucleation between the ideally smooth and nanostructure substrates, but the latter has better performance in improving the bubble nucleation rate.

Magnetic Actuation of Surface Walkers: The Effects of Confinement and Inertia.

Driven by a magnetic field, the rotation of a particle near a wall can be rectified into a net translation. The particles thus actuated, or surface walkers, are a kind of active colloid that finds application in biology and microfluidics. Here, we investigate the motion of spherical surface walkers confined between two walls using simulations based on the immersed-boundary lattice Boltzmann method. The degree of confinement and the nature of the confining walls (slip vs no-slip) significantly affect a particle's translational speed and can even reverse its translational direction. When the rotational Reynolds number Reω is larger than 1, inertia effects reduce the critical frequency of the magnetic field, beyond which the sphere can no longer follow the external rotating field. The reduction of the critical frequency is especially pronounced when the sphere is confined near a no-slip wall. As Reω increases beyond 1, even when the sphere can still rotate in the synchronous regime, its translational Reynolds number ReT no longer increases linearly with Reω and even decreases when Reω exceeds ∼10.

Highly luminescent sensing for nitrofurans and tetracyclines in water based on zeolitic imidazolate framework-8 incorporated with dyes.

Antibiotics are one of the emerging contaminants in water, which have a great impact on ecosystems and human health. It has been challenging to simultaneously realize low-cost, rapid, highly sensitive and selective detection of antibiotics with conventional methods. Here, we report luminescent chemosensors for detecting antibiotics in water, based on metal-organic framework (MOF), i.e., zeolitic imidazolate framework-8 (ZIF-8), loaded with rhodamine B (RhB) and fluorescein disodium salt (FSS) dyes. Compared with ZIF-8, the fluorescence signals of RhB@ZIF-8 and FSS@ZIF-8 were significantly improved and presented ultrahigh sensitivity to nitrofurans (NFAs) and tetracyclines (TCs) with fluorescence quenching and fluorescence enhancement in water, respectively. The unique structures and properties of RhB@ZIF-8 and FSS@ZIF-8 lead to outstanding sensitivities in antibiotic detection. For instance, the RhB@ZIF-8 sensor shows the lower limit of detection (LOD) of 0.26 µM to nitrofurantoin (NFT), 0.47 µM to nitrofurazone (NFZ), 0.11 µM to tetracycline (TC), and 0.14 µM to oxytetracycline (OTC); while the FSS@ZIF-8 sensor shows the LOD of 0.31 µM to NFT, 0.35 µM to NFZ, 0.17 µM to TC, and 0.16 µM to OTC. In addition, NFT and TC were also successfully detected by FSS@ZIF-8 in water from real water environment. The results indicate that dye@MOF-based luminescent composites are favorable for antibiotic detection, presenting great potentials in water quality monitoring.

Predicting Effective Diffusivity of Porous Media from Images by Deep Learning.

We report the application of machine learning methods for predicting the effective diffusivity (De) of two-dimensional porous media from images of their structures. Pore structures are built using reconstruction methods and represented as images, and their effective diffusivity is computed by lattice Boltzmann (LBM) simulations. The datasets thus generated are used to train convolutional neural network (CNN) models and evaluate their performance. The trained model predicts the effective diffusivity of porous structures with computational cost orders of magnitude lower than LBM simulations. The optimized model performs well on porous media with realistic topology, large variation of porosity (0.28-0.98), and effective diffusivity spanning more than one order of magnitude (0.1 ≲ De < 1), e.g., >95% of predicted De have truncated relative error of <10% when the true De is larger than 0.2. The CNN model provides better prediction than the empirical Bruggeman equation, especially for porous structure with small diffusivity. The relative error of CNN predictions, however, is rather high for structures with De < 0.1. To address this issue, the porosity of porous structures is encoded directly into the neural network but the performance is enhanced marginally. Further improvement, i.e., 70% of the CNN predictions for structures with true De < 0.1 have relative error <30%, is achieved by removing trapped regions and dead-end pathways using a simple algorithm. These results suggest that deep learning augmented by field knowledge can be a powerful technique for predicting the transport properties of porous media. Directions for future research of machine learning in porous media are discussed based on detailed analysis of the performance of CNN models in the present work.

Influence of Environmental Factors on the Adsorption Capacity and Thermal Conductivity of Silica Nano-Porous Materials.

In this work, the influence of temperature and humidity environment on the water vapor adsorption capacity and effective thermal conductivity of silica nano-porous material is conducted within a relative humidity range from 15% to 90% at 25 °C, 40 °C and 55 °C, respectively. The experiment results show that both the temperature and relative humidity have significant influence on the adsorption capacity and effective thermal conductivity of silica nano-porous materials. The adsorption capacity and effective thermal conductivity increase with humidity because of the increases of water vapor concentration. The effective thermal conductivity increases linearly with adsorption saturation capacity at constant temperature. Because adsorption process is exothermic reaction, the increasing temperature is not conducive to the adsorption. But the effective thermal conductivity increases with the increment of temperature at the same water uptake because of the increment of water thermal conductivity with temperature Geometric models and unit cell structure are adopted to predict the effective thermal conductivity and comparisons with the experimental result are made, and for the case of moist silica nano-porous materials with high porosity no quantitative agreement is found. It is believed that the adsorbed water will fill in the nano-pores and gap and form lots of short cuts, leading to a significant reduction of the thermal resistance.

Experimental and Numerical Study on Thermal Conductivity of Proton Exchange Membrane.

In this paper, the thermal conductivity of dry Nafion 117 is measured by Hot Disk TPS2500 and a molecular dynamics calculation model for the proton exchange membrane is constructed by Materials Studio (MS) software platform to study its thermal conductivity. Cell structures of different water content of Nafion membrane at 300 K and 330 K are obtained, respectively. It is found that at the same temperature the predicted thermal conductivity of PEM increases with the water content, and at the same water content the predicted thermal conductivity decreases with the temperature. So both the water content and temperature are important factors affecting thermal conductivities of PEM.

Study on Unit Cell Models and the Effective Thermal Conductivities of Silica Aerogel.

In this paper, two modified unit cell models, truncated octahedron and cubic array of intersecting square rods with 45-degree rotation, are developed in consideration of the tortuous path of heat conduction in solid skeleton of silica aerogel. The heat conduction is analyzed for each model and the expressions of effective thermal conductivity of the modified unit cell models are derived. Considering the random microstructure of silica aerogel, the probability model is presented. We also discuss the effect of the thermal conductivity of aerogel backbone. The effective thermal conductivities calculated by the proposed probability model are in good agreement with available experimental data when the density of the aerogel is 110 kg/m3.

The Calculation of Thermal Conductivities by Three Dimensional Direct Simulation Monte Carlo Method.

Three dimensional direct simulation Monte Carlo (DSMC) method with the variable soft sphere (VSS) collision model is implemented to solve the Boltzmann equation and to acquire the heat flux between two parallel plates (Fourier Flow). The gaseous thermal conductivity of nitrogen is derived based on the Fourier's law under local equilibrium condition at temperature from 270 to 1800 K and pressure from 0.5 to 100,000 Pa and compared with the experimental data and Eucken relation from Chapman and Enskog (CE) theory. It is concluded that the present results are consistent with the experimental data but much higher than those by Eucken relation especially at high temperature. The contribution of internal energy of molecule to the gaseous thermal conductivity becomes significant as increasing the temperature.

Generalized lattice Boltzmann model for flow through tight porous media with Klinkenberg's effect.

Gas slippage occurs when the mean free path of the gas molecules is in the order of the characteristic pore size of a porous medium. This phenomenon leads to Klinkenberg's effect where the measured permeability of a gas (apparent permeability) is higher than that of the liquid (intrinsic permeability). A generalized lattice Boltzmann model is proposed for flow through porous media that includes Klinkenberg's effect, which is based on the model of Guo et al. [Phys. Rev. E 65, 046308 (2002)]. The second-order Beskok and Karniadakis-Civan's correlation [A. Beskok and G. Karniadakis, Microscale Thermophys. Eng. 3, 43 (1999) and F. Civan, Transp. Porous Med. 82, 375 (2010)] is adopted to calculate the apparent permeability based on intrinsic permeability and the Knudsen number. Fluid flow between two parallel plates filled with porous media is simulated to validate the model. Simulations performed in a heterogeneous porous medium with components of different porosity and permeability indicate that Klinkenberg's effect plays a significant role on fluid flow in low-permeability porous media, and it is more pronounced as the Knudsen number increases. Fluid flow in a shale matrix with and without fractures is also studied, and it is found that the fractures greatly enhance the fluid flow and Klinkenberg's effect leads to higher global permeability of the shale matrix.

Pore-scale modeling of multiphase reactive transport with phase transitions and dissolution-precipitation processes in closed systems.

A pore-scale model based on the lattice Boltzmann (LB) method is developed for multiphase reactive transport with phase transitions and dissolution-precipitation processes. The model combines the single-component multiphase Shan-Chen LB model [X. Shan and H. Chen, Phys. Rev. E 47, 1815 (1993)], the mass transport LB model [S. P. Sullivan et al., Chem. Eng. Sci. 60, 3405 (2005)], and the dissolution-precipitation model [Q. Kang et al., J. Geophys. Res. 111, B05203 (2006)]. Care is taken to handle information on computational nodes undergoing solid-liquid or liquid-vapor phase changes to guarantee mass and momentum conservation. A general LB concentration boundary condition is proposed that can handle various concentration boundaries including reactive and moving boundaries with complex geometries. The pore-scale model can capture coupled nonlinear multiple physicochemical processes including multiphase flow with phase separations, mass transport, chemical reactions, dissolution-precipitation processes, and dynamic evolution of the pore geometries. The model is validated using several multiphase flow and reactive transport problems and then used to study the thermal migration of a brine inclusion in a salt crystal. Multiphase reactive transport phenomena with phase transitions between liquid-vapor phases and dissolution-precipitation processes of the salt in the closed inclusion are simulated and the effects of the initial inclusion size and temperature gradient on the thermal migration are investigated.

Mesoscopic study of the effects of gel concentration and materials on the formation of precipitation patterns.

A mesoscopic model based on the lattice Boltzmann method (LBM) is proposed to simulate the formation of Liesegang precipitation patterns and investigate the effects of gel on the morphology of the precipitates. In this model, nucleation is introduced on the basis of Ostwald's supersaturation theory, and subsequent crystal growth on the precipitate surface is simulated using a crystal growth model by taking into account the heterogeneous reaction on the surface of the precipitate. This model can capture the porous structures of the precipitates and can take into account the effects of the gel concentration and material by adjusting the gel porosity and nucleation threshold. The density of the precipitate nodes in the model is limited. A wide range of precipitation patterns is predicted under different gel concentrations, including regular bands, treelike patterns, and for the first time with numerical models, transition patterns between regular bands and treelike patterns. Both the spacing law and the width law are carefully investigated with different gel concentrations and gel materials, and the obtained α in the width law (w(n) ≈ x(n)(α), where x(n) and w(n) are the position and the width of the nth band, respectively) is in the range of 0.58-0.67, sandwiched by previously predicted ranges.