Molecular dynamic simulation of carbon dioxide, methane, and nitrogen adsorption on Faujasite zeolite

Investigation of solvent extraction of acetic acid and acetone from water in the presence of SiO2 nanoparticles using molecular dynamics simulation

In this study, molecular dynamics simulation was used to predict the molecular diffusion coefficient of acetic acid and acetone in water, toluene, and benzene. The results showed that COMPASS was the best force field to optimize the atoms and structure of molecules, and the results were compared with experimental equations. The Arrhenius behavior of the molecular diffusion coefficient was investigated at three temperatures. The extraction of acetic acid and acetone from water was investigated using two solvents, toluene, and benzene, with and without SiO2 nanoparticles. The relative concentration change diagram was drawn for three cases without and with SiO2 nanoparticles. To quantitatively examine the results, extraction efficiency, selectivity, and distribution coefficient were calculated. The extraction efficiency of acetone from water by benzene in the absence of silica nanoparticles was 65.748 %, this value in the presence of SiO2 nanoparticles with a concentration of 0.2231 wt% was 72.45 % due to the Brownian motion of the nanoparticles, which increased the mass transfer and as a result, the extraction efficiency. With the further increase of nanoparticles up to 1.7573 wt%, the extraction efficiency decreased to 61.276 %, which can be attributed to the accumulation of silica nanoparticles and the decrease in the free movement of nanoparticles.

Loading Self-Assembly Siliceous Zeolites for Affordable Next-Generation Wearable Artificial Kidney Technology

The global demand for dialysis among patients with end-stage kidney disease has surpassed the capacity of public healthcare, a trend that has intensified. While wearable artificial kidney (WAK) technology is seen as a crucial solution to address this demand, there is an urgent need for both efficient and renewable toxin-adsorbent materials to overcome the long-standing technological challenges in terms of cost, device size, and sustainability. In this study, we employed screening experiments for adsorbent materials, multimodal characterization, and Monte Carlo adsorption simulations to identify a synthetic self-assembly silicalite-1 zeolite that exhibits highly ordered crystal arrays along the [010] face (b-axis) direction, demonstrating exceptional adsorption capabilities for small molecular toxins such as creatinine and urea associated with uremia. Moreover, this metal-free, cost-effective, easily synthesized, and highly efficient toxin adsorbent could be regenerated through calcination without compromising the performance. The simulated toxin adsorption experiments and comprehensive biocompatibility verification position it as an auxiliary adsorbent to reduce dialysate dosages in WAK devices as well as a potential adsorbent for small-molecule toxins in dialysis. This work is poised to propel the development of next-generation WAK devices by providing siliceous adsorbent solutions for small-molecule toxins.

Molecular simulation of liquid-liquid extraction of acetic acid and acetone from water in the presence of nanoparticles based on prediction of solubility parameters

In this work, molecular dynamics simulation (MD) was used for studying the liquid-liquid extraction of acetic acid and acetone from water in the presence of nanoparticles. In the next step, the solubility parameter of acetic acid and acetone were predicted at 1 atm and different temperatures along with the solubility parameter of solvents and water at 25 °C and 1 atm. Three pure systems and three systems with different concentration of nanoparticles were investigated to show the effect of cell size or number of molecules on the solubility parameter. With the addition of SiO2 nanoparticles to the solvents, at low concentrations of nanoparticles (0.01-0.1 vol%), the solubility parameter is increased due to the Brownian motion. With the further increase concentration of the nanoparticles, the solubility parameter decreases due to the accumulation of nanoparticles. The difference between the solubility parameter of benzene and acetone was 0.414 (J/cm3)0.5 and 3.13 (J/cm3)0.5, with and without the presence of SiO2 nanoparticles, respectively. Finally, toluene was found to be the best solvent for acetone and acetic acid at silica nanoparticles concentration of 0.062 vol%.

Adsorption Modeling Based on Classical Density Functional Theory and PC-SAFT: Temperature Extrapolation and Fluid Transfer

Adsorption is at the heart of many processes from gas separation to cooling. The design of adsorption-based processes requires equilibrium adsorption properties. However, data for adsorption equilibria are limited, and therefore, a model is desirable that uses as little data as possible for its parametrization, while allowing for data interpolation or even extrapolation. This work presents a physics-based model for adsorption isotherms and other equilibrium adsorption properties. The model is based on one-dimensional classical density functional theory (1D-DFT) and the perturbed-chain statistical associating fluid theory (PC-SAFT). The physical processes inside the pores are considered in a thermodynamically consistent approach that is computationally efficient. Once parametrized with a single isotherm, the model is able to extrapolate to other temperatures and outperforms the extrapolation capabilities of state-of-the-art models, such as the empirical isotherm models from Langmuir or Toth. Furthermore, standard combining rules can be used to transfer parameters adjusted to an adsorbent/fluid pair to other fluids. These features are demonstrated for the adsorption of N2, CH4, and CO2 in metal-organic frameworks. Thereby, the presented model can calculate temperature-dependent isotherms for various fluids by using data limited to a single isotherm as input.

Effect of Moisture on Methane Adsorption Characteristics of Long-Flame Coal

Long-flame coal is a bituminous coal with the lowest metamorphic degree, accounting for 16.1% of China's coal reserves. With increases in mining depths and intensities, mine gas disasters related to the mining of long-flame coal are becoming increasingly serious. Therefore, the exploration of the effect of moisture on the adsorption of methane in coal can provide support for popularizing the application of hydraulic measures in long-flame coal mining areas. In this paper, a molecular structure model of long-flame coal was established by molecular dynamics and the Monte Carlo method. The adsorption characteristics of methane in long-flame coal structures under different pressures were simulated, and the effects of different amounts of water on the methane adsorption and adsorption heat were explored. The results show that, under the same adsorption equilibrium pressure, the methane adsorption rate decreases with increasing water content, and with increasing adsorption equilibrium pressure, the adsorption capacity of methane increases gradually; this increasing trend is in agreement with the Langmuir equation. The water adsorption of coal is greater than the methane adsorption of coal. With the increase in the number of water molecules, when coal-based molecules adsorb methane and then adsorb water molecules, the adsorption heat of methane is reduced, and the desorption of methane molecules is promoted.