Understanding the mass transfer behaviors in hollow fiber membrane module of artificial liver is important for improving toxin removal efficiency. A three-dimensional numerical model was established to study the mass transfer of small molecule bilirubin and macromolecule bovine serum albumin (BSA) in the hollow fiber membrane module. Effects of tube-side flow rate, shell-side flow rate, and hollow fiber length on the mass transfer of bilirubin and BSA were discussed. The simulation results showed that the clearance of bilirubin was significantly affected by both convective and diffusive solute transport, while the clearance of macromolecule BSA was dominated by convective solute transport. The clearance rates of bilirubin and BSA increasd with the increase of tube-side flow rate and hollow fiber length. With the increase of shell-side flow rate, the clearance rate of bilirubin first rose rapidly, then slowly rose to an asymptotic value, while the clearance rate of BSA gradually decreased. The results can provide help for designing structures of hollow fiber membrane module and operation parameters of clinical treatment.
了解人工肝中空纤维膜组件传质行为对其高效解毒具有重要指导意义。建立了中空纤维膜组件内流动传质的三维数值模拟模型，研究了小分子胆红素与大分子牛血清白蛋白（BSA）在组件内的传质行为，讨论了管程流量、壳程流量、中空纤维管长度对胆红素与BSA传质的影响。研究结果表明小分子胆红素的传质方式是对流传质和扩散传质二者兼具，而大分子BSA的传质方式以对流传质为主；胆红素和BSA的清除速率随着管程流量增大而提升，也随着中空纤维管长度增加而提升；随着壳程流量增大，胆红素的清除速率先快速提升再缓慢上升达到渐近值，而BSA的清除速率随壳程流量增大而逐渐减小。研究成果可以为人工肝中空纤维膜组件的结构优化设计和临床操作参数提供依据。.

The study examined mass transfer coefficients in a structured CO2 absorption column using machine learning (ML) and response surface methodology (RSM). Three correlations for the fractional effective area (af), gas phase mass transfer coefficient (kG), and liquid phase mass transfer coefficient (kL) were derived with coefficient of determination (R2) values of 0.9717, 0.9907 and 0.9323, respectively. To develop these correlations, four characteristics of structured packings, including packing surface area (ap), packing corrugation angle (θ), packing channel base (B), and packing crimp height (h), were used. ML used five models, represented as random forest (RF), radial basis function neural network (RBF), multilayer perceptron (MLP), XGB Regressor, and Extra Trees Regressor (ETR), with the best models being radial basis function neural network (RBF) for af (R2 = 0.9813, MSE = 0.00088), RBF for kG (R2 = 0.9933, MSE = 0.00056), and multilayer perceptron (MLP) for kL (R2 = 0.9871, MSE = 0.00089). The channel base had the most impact on af and kL, while crimp height affected kG the most. Although the RSM method produced adequate equations for each output variable with good predictability, the ML method provides superior modeling capabilities.

In this work, we explore a simplified model based on both analytical and computational methods for the study of film-boiling droplet motion on microscale ratchets. We consider a specific ratchet design with the length periods and depth of ratchets much smaller than the size of the droplet. We conclude based on our modeling that for the ratchet configuration considered in this paper, the conduction within the vapor film is the dominant means of heat transfer in comparison with convection and radiation. Furthermore, we demonstrate a more manageable two-dimensional model in which analytical approaches coupled with computational approaches yield reasonably accurate results in comparison to the actual experiments.

In this paper, we investigate the electro-osmotic flow (EOF) and mass transfer of a Newtonian fluid propelled by a pressure gradient and alternating current (AC) electric field in a parallel microchannel with sinusoidal roughness and modulated charged surfaces. The two-wall roughness is described by in-phase or out-of-phase sine functions with a small amplitude δ. By employing the method of perturbation expansion, the semi-analytical solutions of the Poisson-Boltzmann (P-B) equation based on the Debye-Hückel approximation and the modified Navier-Stokes (N-S) equation are obtained. The numerical solution of the concentration equation is obtained by the finite difference method. The effects of sinusoidal roughness, modulated charged surface, and the AC electric field on the potential field, velocity field, and concentration field are discussed. Under the influence of the modulated charged surface and sinusoidal roughness, vortices are generated. The velocity oscillates due to the effect of the AC electric field. The results indicate that solute diffusion becomes enhanced when the oscillation Reynolds number is below a specific critical value, and it slows down when the oscillation Reynolds number exceeds this critical value.

Tender coconut water has been very popular as a natural beverage rich in various electrolytes, amino acids, and vitamins, and hence a large amount of tender coconut kernel is left without efficient utilization. To explore the possibility of making infused tender coconut kernel, we investigated the effects of two osmosis methods, including solid-state osmotic dehydration and liquid-state osmotic dehydration, as well as two osmosis agents such as sorbitol and sucrose, on the mass transfer of coconut kernel under solid-state osmotic dehydration conditions. The results showed that under the conditions of solid-state osmosis using sucrose and liquid-state osmosis using sucrose solution, the water diffusion coefficients were 9.0396 h-1/2 and 2.9940 h-1/2, respectively, with corresponding water mass transfer coefficients of 0.3373 and 0.2452, and the equilibrium water loss rates of 49.04% and 17.31%, respectively, indicating that the mass transfer efficiency of solid-state osmotic dehydration of tender coconut kernel was significantly higher than that of liquid-state osmotic dehydration. Under solid osmosis conditions, the water loss rates using sucrose and sorbitol were 38.64% and 41.95%, respectively, with dry basis yield increments of 61.38% and 71.09%, respectively, demonstrating superior dehydration efficiency of sorbitol over sucrose under solid-state osmosis. This study can provide a reference for the theoretical study of the mass transfer of tender coconut kernel through osmotic dehydration, and also provide technical support for the development and utilization of tender coconut kernel.

Flue gas emissions are the waste gases produced during the combustion of fuel in industrial processes, which are released into the atmosphere. These identical processes also produce a significant amount of wastewater that is released into the environment. The current investigation aims to assess the viability of simultaneously mitigating flue gas emissions and remediating wastewater in a bubble column bioreactor utilizing bacterial consortia. A comparative study was done on different growth media prepared using wastewater. The highest biomass yield of 3.66 g L-1 was achieved with the highest removal efficiencies of 89.80, 77.30, and 80.77% for CO2, SO2, and NO, respectively. The study investigated pH, salinity, dissolved oxygen, and biochemical and chemical oxygen demand to assess their influence on the process. The nutrient balance validated the ability of bacteria to utilize compounds in flue gas and wastewater for biomass production. The Fourier Transform-Infrared Spectrometry (FT-IR) and Gas Chromatography-Mass Spectrometry (GC-MS) analyses detected commercial-use long-chain hydrocarbons, fatty alcohols, carboxylic acids, and esters in the biomass samples. The nuclear magnetic resonance (NMR) metabolomics detected the potential mechanism pathways followed by the bacteria for mitigation. The techno-economic assessment determined a feasible total capital investment of 245.74$ to operate the reactor for 288 h. The bioreactor\'s practicability was determined by mass transfer and thermodynamics assessment. Therefore, this study introduces a novel approach that utilizes bacteria and a bioreactor to mitigate flue gas and remediate wastewater.

Chemical bioreactions play a significant role in many of the microfluidic devices, and their applications in biomedical science have seen substantial growth. Given that effective mixing is vital for initiating biochemical reactions in many applications, micromixers have become increasingly prevalent for high-throughput assays. In this research, a numerical study using the finite element method was conducted to examine the fluid flow and mass transfer characteristics in novel micromixers featuring an array of pillars. The study utilized two-dimensional geometries. The impact of pillar configuration on mixing performance was evaluated using concentration distribution and mixing index as key metrics. The study explores the effects of pillar array design on mixing performance and pressure drop, drawing from principles such as contraction-expansion and split-recombine. Two configurations of pillar arrays, slanted and arrowhead, are introduced, each undergoing investigation regarding parameters such as pillar diameter, gap size between pillar groups, distance between pillars, and vertical shift in pillar groups. Subsequently, optimal micromixers are identified, exhibiting mixing efficiency exceeding 99.7% at moderate Reynolds number (Re = 1), a level typically challenging for micromixers to attain high mixing efficiency. Notably, the pressure drop remains low at 1102 Pa. Furthermore, the variations in mixing index over time and across different positions along the channel are examined. Both configurations demonstrate short mixing lengths and times. At a distance of 4300 μm from the inlet, the slanted and arrowhead configurations yielded mixing indices of 97.2% and 98.9%, respectively. The micromixers could provide a mixing index of 99.5% at the channel\'s end within 8 s. Additionally, both configurations exceeded 90% mixing indices by the 3 s. The combination of rapid mixing, low pressure drop, and short mixing length positions the novel micromixers as highly promising for microfluidic applications.

BACKGROUND: The rapid growth and diversification of drug delivery systems have been significantly supported by advancements in micro- and nano-technologies, alongside the adoption of biodegradable polymeric materials like poly(lactic-co-glycolic acid) (PLGA) as microcarriers. These developments aim to reduce toxicity and enhance target specificity in drug delivery. The use of in silico methods, particularly molecular dynamics (MD) simulations, has emerged as a pivotal tool for predicting the dynamics of species within these systems. This approach aids in investigating drug delivery mechanisms, thereby reducing the costs associated with design and prototyping. In this study, we focus on elucidating the diffusion mechanisms in curcumin-loaded PLGA particles, which are critical for optimizing drug release and efficacy in therapeutic applications.
METHODS: We utilized MD to explore the diffusion behavior of curcumin in PLGA drug delivery systems. The simulations, executed with GROMACS, modeled curcumin molecules in a representative volume element of PLGA chains and water, referencing molecular structures from the Protein Data Bank and employing the CHARMM force field. We generated PLGA chains of varying lengths using the Polymer Modeler tool and arranged them in a bulk-like environment with Packmol. The simulation protocol included steps for energy minimization, T and p equilibration, and calculation of the isotropic diffusion coefficient from the mean square displacement. The Taguchi method was applied to assess the effects of hydration level, PLGA chain length, and density on diffusion.
RESULTS: Our results provide insight into the influence of PLGA chain length, hydration level, and polymer density on the diffusion coefficient of curcumin, offering a mechanistic understanding for the design of efficient drug delivery systems. The sensitivity analysis obtained through the Taguchi method identified hydration level and PLGA density as the most significant input parameters affecting curcumin diffusion, while the effect of PLGA chain length was negligible within the simulated range. We provided a regression equation capable to accurately fit MD results. The regression equation suggests that increases in hydration level and PLGA density result in a decrease in the diffusion coefficient.

暂无摘要。

Microbial electrosynthesis (MES) is a promising technology for CO2 fixation and electrical energy storage. Currently, the low current density of MES limits its practical application. The H2-mediated and non-biofilm-driven MES could work under higher current density, but it is difficult to achieve high coulombic efficiency (CE) due to low H2 solubility and poor mass transfer. Here, we proposed to enhance the hydrogen mass transfer by adding silica nanoparticles to the reactor. At pH 7, 35 ℃ and 39 A·m- 2 current density, with the addition of 0.3wt% silica nanoparticles, the volumetric mass transfer coefficient (kLa) of H2 in the reactor increased by 32.4% (from 0.37 h- 1 to 0.49 h- 1), thereby increasing the acetate production rate and CE of the reactor by 69.8% and 69.2%, respectively. The titer of acetate in the reactor with silica nanoparticles (18.5 g·L- 1) was 56.9% higher than that of the reactor without silica nanoparticles (11.8 g·L- 1). Moreover, the average acetate production rate of the reactor with silica nanoparticles was up to 2.14 g·L- 1·d- 1 in the stable increment phase, which was much higher than the other reported reactors. These results demonstrated that the addition of silica nanoparticles is an effective approach to enhancing the performance of H2-mediated MES reactors.