This study presents a novel model to predict gas-water two-phase transport behaviors in shale microfractures by incorporating a mobile water film with varying thickness according to the extended Derjaguin-Landau-Verwey-Overbeek (DLVO) theory as well as multiple fluid transport mechanisms (i.e., real gas transport controlled by the Knudsen number and water slippage). This model is implemented in real shale microfractures via digital-core imaging. A gas-water displacement process is modelled by the invasion percolation theory, while a local multiphase distribution is determined by combining disjoining pressure with capillary force. Key findings reveal that gas relative permeability (RP) decreases by 17% and water RP enhances by 33.5%, when the mean aperture decreases from 1.67 to 0.0418μm. Neglecting water film brings a decrease in water RP and an overestimation of gas transport ability. Moreover, two critical microfracture apertures are determined, which enhances an understanding of the water film impact on gas-water transport properties in application.

Community detection decomposes large-scale, complex networks ‘optimally’ into sets of smaller sub-networks. It finds sub-networks that have the least inter-connections and the most intra-connections. This article presents an efficient community detection algorithm that detects community structures in a weighted network by solving a multi-objective optimization problem. The whale optimization algorithm is extended to enabe it to handle multi-objective optimization problems with discrete variables and to solve the problems on parallel processors. To this end, the population’s positions are discretized using a transfer function that maps real variables to discrete variables, the initialization steps for the algorithm are modified to prevent generating unrealistic connections between variables, and the updating step of the algorithm is redefined to produce integer numbers. To identify the community configurations that are Pareto optimal, the non-dominated sorting concept is adopted. The proposed algorithm is tested on the Tennessee Eastman process to show its application and performance.

A spatially resolved 1-D pressure filtration model was developed for a slurry of edible fat crystals. The model focuses on the expression step in which a cake is compressed to force the liquid through a filter cloth. The model describes the local oil flow in the shrinking cake modeled as a porous nonlinear elastic medium existing of two phases, viz. porous aggregates and inter-aggregate liquid. Conservation equations lead to a set of two differential equations (vs time and vs a material coordinate ) for two void ratios, which are solved numerically by exploiting a finite-difference scheme. A simulation with this model results in a spatially resolved cake composition and in the outflow velocity, both as a function of time, as well as the final solid fat contents of the cake. Simulation results for various filtration conditions are compared with experimental data collected in a pilot-plant scale filter press.

The present study depicts the hydrodynamics along with the mixing characteristics inside a millichannel-based serpentine fixed-bed device to attain the particular demands of the fabrication of the miniature adsorption devices. Residence Time Distribution (RTD) analyses were accomplished to analyze the velocity distribution inside the packed bed geometry. The operating variables effect the hydrodynamics, mixing, and the lead adsorption characteristics, which were pronounced clearly in the present context. Depending on the results obtained in the experiment, the new correlations were proposed. The parametric effects on the lead ions adsorption were studied in the same millichannel geometry packed with the graphene oxide (GO) coated glass beads. Thomas model was utilized to investigate the kinetics of the adsorptive removal process. The regeneration study of the said millichannel-based fixed-bed device was also executed.

For the ionic liquid (IL)-solute systems of broad interest, a deep neural network based recommender system (RS) for predicting the infinite dilution activity coefficient (γ∞) is proposed and applied for a large extension of the UNIFAC model. In the RS, neural network entity embeddings are employed for mapping each IL and solute and neural collaborative filtering is utilized to handle the nonlinearities of IL-solute interactions. A comprehensive experimental γ∞ database covering 215 ILs and 112 solutes (totally 41,553 data points) is established for training the RS, where the cross-validation and test are performed based on a rigorous dataset split by IL-solute combinations. The obtained RS shows superior performance than the state-of-the-art γ∞ models and is thus taken to complete the solute-in-IL γ∞ matrix. Based on the completed γ∞ database, a large extension of the UNIFAC-IL model is finally presented, filling all the parameters between involved groups.

Both fast and turbulent fluidized beds exhibit entrainment, but the differences in the flow phenomena are not well understood. This study targeted a comparative analysis of the cluster (or streamer), mass flux, and segregation datasets from these two fluidization regimes. The particle systems were narrow particle size distributions (PSDs), binary mixtures, or broad PSDs of Geldart Group B particles. Relative to the fast fluidized bed, the turbulent bed exhibited (i) higher cluster probability and frequency, but lower cluster duration; (ii) lower local mass flux; and (iii) similar segregation extents. Regarding clusters, the relative dominance of the variables on probability was similar for both regimes, but there was a difference for probability and frequency. For overall mass flux, particle-related properties were more dominant with the turbulent bed. As for segregation, the radial position was the most influential in the fast fluidized bed, but the least in the turbulent one.

A coupling framework for modeling the non-constant-velocity approach of two fluid particles and the curved film drainage was developed, and an improved model was presented to predict the variable-velocity approach. Using this framework, the effect of the constant-velocity and variable-velocity approach on liquid film drainage was investigated. Two film drainage models based on immobile interface and fully mobile interface were adopted. The simulation results showed that the film thinning rate of the former is much less than that of the latter. In the case of constant-velocity approach, the immobile interface model showed a relatively flat curved film, while in the case of variable-velocity approach, three types of film, wimple, pimple and dimple, can be found. The different combinations of the drainage models and the approach velocity boundary conditions were compared with the experiments. The fully mobile interface model with variable-velocity approach can reasonably predict the coalescence and rebound of bubbles.

Carbon quantum dots (C-QDs) show great potential to replace traditional semiconductive quantum dots as the next generation of fluorescent probes. We demonstrate here a new C-QD production process using lignin, a high-volume but low market-value industrial waste and/or environmental hazards, as the starting carbon source. By adding a small amount of inorganic acid, the rich phenolic components in lignin were successfully converted to C-QDs through a coking formation mechanism similar to what happens on solid acid catalysts in traditional fossil fuel cracking process. The aqueous solution presence of the received lignin C-QDs is beneficial for brain cell imaging applications, attributing to their fast internalization, low toxicity, tunable photoluminescence by appropriate acidity and reaction temperature during hydrothermal synthesis. This method not only provides a low-cost C-QDs production route, but also helps gain extra profit and/or improve environment for many small agricultural business and paper and pulp industry located in rural area.

Holistic catalytic reactors with fractal structure have attracted growing attention in heterogeneous reactions because of its advantages of improved mass transfer and easy separation. Herein, a simple and cost-efficient design strategy that combined 3D printing and electroless deposition was presented to construct dynamic, holistic stirred reactors with the fractal structure. The conversion factor α of fractal impeller is 65.01 mmol m-2 h-1 with a large volume of reactant (80 mL), which is 1.7 times that of the normal impeller with the same Ag catalysts. Experimental results and simulation analysis demonstrate that the fractal impeller significantly improves the catalytic performance by enhancing mass transfer and spatial dispersion in the reaction. Moreover, the holistic impeller could be reused for ten times without obvious loss of catalytic performance, and easily separated from the reaction system. The structural design of fractal reactors will open the way for a new efficient dynamic heterogeneous catalytic reactor.

Zwitterionic materials have attracted increasing attentions in the underwater super-oleophobic applications for its strong hydration via electrostatic interactions. Herein, molecular dynamics simulations were used to investigate the hydration and underwater oleophobicity of sulfobetaine-terminated self-assembled monolayers (SB-SAMs) with different carbon spacer lengths (CSL) between oppositely charged groups of SB molecules. Simulation results show that the hydration of SB-SAMs is positively dependent on CSL; the underwater oleophobicity is strengthened and then weakened with the increase of CSL, reaching optimal performance when CSL = 3; Adhesion force of oil droplet on SB-SAMs is inversely correlated with their contact angles, reaching the minimum value when CSL = 3. Moreover, the addition of NaCl can weaken the self-association of SB molecules resulted from interactions between cationic and anionic groups, which promotes hydration and enhances underwater oleophobicity of SB-SAMs. These results will benefit for the design of novel zwitterion-based materials for anti-fouling and oil-water separation applications.

Acetylene, an important petrochemical feedstock, is the starting chemical to produce many polymer products. Separating C2H2 from its by-product mixtures is still an energy-consuming process and remains challenging. Here, we present a metal-organic framework[Zn2(bpy)(btec)], with a desirable pore geometry and highly stable framework, which demonstrated a high separation performance of C2H2 from simulated mixtures. With the desirable pore dimension and hydrogen bonding sites, Zn2(bpy)(btec) shows by far the both highest C2H2/CO2 and C2H2/CO2 uptake ratios, very high adsorption selectivities and moderately C2H2 uptake of 93.5 cm3•cm−3 under 298 K and 1 atm. Not only straightforwardly produced high purity of C2H4, but also recovered high purity of C2H2 (>98%) in the regeneration process (>92% recovery). More notably, Zn2(bpy)(btec) can be straightforwardly synthesized at a large scale under environmentally friendly conditions, and its good water/chemical stability, thermostability, and cyclic stability highlight the promise of this molecular sieving material for industrial C2H2 separation.

The cell free system has been paid more attention due to its potential of facilitating more efficient catalysis of multistep reactions. In this study, an efficient enzymatic cascade of GSH production was developed through the evolution of bifunctional glutathione synthetase (GshF), coupled with polyphosphate kinase (PPK). First, the stability and activity of GshF were enhanced by loop interchange and site-directed mutagenesis. As a result, the GshF half-value period increased 163.3-fold, and its activity raised 18 %. PPK from Jhaorihella thermophile (PPKJT) was characterized and used to regenerate ATP in the GSH synthesis, with hexametaphosphate (PolyP(6)) as the phosphate donor. After the process optimization, 99.9 mM GSH and 7.6 mM oxidized glutathione (GSSG) were produced within 2 h. The molar yield was 95.9 mol/mol based on the amino acid added, while the productivities of GSH achieved 49.95 mM/h, which was the highest yield and productivity ever reported about GSH synthesis.

Since chromatographic separation is a dynamic process, with the interactions between the drug and the chiral stationary phase mediated by the solvent, no single interacting structure, such as could be found by minimizing the energy, could possibly describe and account for the ratio of residence times in the chromatographic column for the enantiomeric pair. We describe the use of explicit-solvent fully atomistic molecular dynamics simulations, permitting all the interactions between the atoms constituting the chiral stationary phase, solvent molecules and the drug molecule. This allows us to better understand the molecular dynamic chiral recognition that provides the discrimination which results in the separation of enantiomers by high performance liquid chromatography. It also provides a means of predicting, for a given set of conditions, which enantiomer elutes first and an estimate of the expected separation factor. In this review we consider the use of molecular dynamics towards this understanding and prediction.

Vapor recompressed batch distillation (VRBD) is an energy-integrated configuration which works on the principle of a heat pump. Operation of such a column is challenging due to unsteady, nonlinear dynamics and strong interplay between separation and energy efficiency. In this paper, a two-step approach is proposed for optimal operation and control of such a column. Initially, an openloop optimal operation policy is generated for maximization of an overall performance index using offline optimization. To this end, three performance indices are proposed to capture interplay between separation and energy efficiency. Subsequently, a model-based output feedback controller is designed to track this optimal performance trajectory. The effectiveness of the proposed approach is demonstrated using a benzene-toluene separation case study wherein it is shown that the proposed approach helps to achieve optimal operation in the presence of operational disturbances.

The growth of silica nanoparticles by agglomeration and viscous flow sintering is studied from free molecular to transition regime at high temperatures by discrete element method simulations. The effect of temperature on the aggregate mobility and gyration radii, particle morphology and collision frequency function is elucidated as function of the number of primary particles. The ratio between the characteristic sintering time and characteristic collision time controls the particle size and structure, quantified by the mass fractal dimension. The effect of this ratio of characteristic times on aggregate morphology is illustrated at various temperatures. Finally, when sintering is negligible, the overall collision frequency is 90% larger than that predicted by the classic Fuchs collision kernel for monodisperse agglomerates in the near free molecular and transition regime. For comparable coagulation and sintering rates, where aggregates with sinter bonds are formed, the overall collision frequency increases an enhancement of <90% is observed.

Massive amounts of gas hydrates occur naturally in the pores of sediments or fractures in permafrost regions and beneath the oceans. For hydrate formation in confinement, the equilibrium condition can shift to harsher conditions, lowering the water activity, and subsequently depressing the hydrate freezing temperature at a given pressure. Conversely, the nucleation and rate of hydrate formation, as well as hydrate conversion can be increased in confinement. Therefore, reliable assessment of the hydrate distribution in nature requires accurate thermodynamic and kinetic models of hydrate formation; however, these models tend to be based upon the properties of bulk hydrates. Hydrate formation and growth promotion in confinement are potentially interesting for hydrate technological applications, such as gas separation, energy storage, and flow assurance. This paper reviews the thermodynamic and kinetic properties and their interrelations of gas hydrates in confined spaces.

The low concentration methyl iodides (CH3I) adsorption process on reduced silver-functionalized silica aerogel (Ag0-Aerogel) was studied. The kinetic data were acquired using a continuous flow adsorption system. Because the corresponding physical process was observed, the shrinking core model (SCM) was modified and applied. An average CH3I pore diffusivity was calculated, the CH3I-Ag0-Aerogel reaction was identified as a 1.37 order reaction instead of first order reaction, and the nth order reaction rate constant was determined. This modified SCM significantly increases the accuracy of adsorption behavior prediction at low adsorbate concentration. Modeling results indicate that the overall adsorption process is controlled by the pore diffusion. However, at low adsorbate concentration (<100 ppbv), the CH3I adsorption is limited to the surface reaction due to the low uptake rate in a predictable time period.

A group of drugs used in Intra-Arterial Chemotherapy (IAC) have intrinsic ionic properties, which can be used for filtering excessive drugs from blood in order to reduce systemic toxicity. The ion-exchange mechanism is utilized in an endovascular Chemofilter device which can be deployed during the IAC for capturing ionic drugs after they have had their effect on the tumor. In this study, the concentrated solution theory is used to account for the effect of electrochemical forces on the drug transport and adsorption by introducing an effective diffusion coefficient in the advection-diffusion-reaction equation. Consequently, a multi-physics model coupling hemodynamic and electrochemical forces is developed and applied to simulations of the transport and binding of Doxorubicin in the Chemofilter device. A comparison of drug adsorption predicted by the computations to that measured in animal studies demonstrated the benefits of using concentrated solution theory over the Nernst-Plank relations for modeling drug binding.