查看更多>>摘要：A low-cost ceramic membrane was coated with cellulose acetate (CA) using different polymer concentrations and dipping durations. The porosity of the membrane decreased considerably (from 58.4 % to 12.1 %) with an increase in polymer concentration from 2.5 to 10 wt. %. The values of the porosity increased and layer thickness decreased slightly with a decrease in dipping time (from 60 s to 15 s). The membrane prepared using 5 wt. % CA in acetone and 45 s dipping duration (T-3) had a polymer separation layer of thickness 14.2 μm and was found to be optimal with 51.8 % porosity, 35 nm pore diameter and a liquid (water) permeability of 7.39 × 10~(10) m~3/m~2·S·Pa. This membrane was applied for micellar enhanced ultrafiltration of three heavy metal ions, namely, Cu(II), Cr(VI) and Ni (II). The prepared membrane (T-3) was highly effective in ultrafiltration applications as evidenced from complete rejection (≈ 100 %) of cetylpyridinium chloride (CPC) along with satisfactory removal (> 99.7 %) of metal ions.
Pravin Parasakthi AravindhanJung Min KimYi-Hung Lin
12页
查看更多>>摘要：CO2 reduction cells are innovative devices that reduce CO2 into valuable chemicals (i.e. methanol (MeOH) and acetate (OAc~-)) on the cathode. A major challenge with such devices is to develop ion exchange membranes that allow ion-selective transport (i.e., protons for cation exchange membranes, CEM) and suppress the crossover of CO2 reduction products. To design such membranes, it is important to understand multi-solute transport behavior of these solutes. Previously, our group reported acetate diffusivities in co-transport with MeOH increase in sulfonated CEMs, where we speculated charge screening of the electrostatic interactions by co-diffusing MeOH has an impact. Here, crosslinked membranes fabricated by photopolymerization of poly(ethylene glycol) diacrylate (PEGDA), 3-sulfo-propyl methacrylate potassium (SPMAK, SO3~--containing ionomer), and a phenyl-con-taining comonomer either phenoxyethyl acrylate (PEA) or poly(ethylene glycol) phenyl ether acrylate (PEGPEA)) are investigated. We observe OAc" diffusivities to both (1) PEGDA-SPMAK and (2) PEGDA-PEGPEA increase in co-diffusion with MeOH and those to (3) PEGDA-SPMAK/PEGPEA decrease. To rationalize this emergent co-transport behavior, we speculate (1) electrostatic interactions are interfered with by co-diffusing MeOH, (2) chain mobility (segmental dynamics) increases in the presence of MeOH and (3) for films with both hydrophobic (PEGPEA) and hydrophilic (SPMAK) comonomers chain mobility (segmental dynamics) decrease due to interactions between the comonomer sidechains depressing overall solute diffusivities. While further investigations are needed, this work contributes to improving our fundamental understanding of the relationships between polymer film chemistry, solute chemistry, and emergent cotransport behavior observed and described in this work (and others) towards enabling the design of improved membrane materials.
查看更多>>摘要：The breakup of liquid drops is an important phenomenology for many applications. We approach this problem with the objective of improving methods for modeling the impulse and impact dispersal of liquids in transportation accident scenarios. These scenarios can be distinguished from many other simpler problems due to the quantity of liquid and the complexity of the intermediate liquid morphology. These differences necessitate alternative (lower computational cost and lower fidelity) approaches to the problem compared to much of the historical modeling work. This work leverages a recently implemented model for inter-particle forces in a Lagrangian/Eulerian computational fluid dynamics (CFD) code. The inter-particle force model is inspired by molecular dynamics methods. It employs a Lennard-Jones (LJ) attractive force and a spring-based repulsive force that is governed by LJ parameters. The LJ parameters are related to the bulk fluid properties through a theoretical relationship to the surface tension. Methods are developed for modifying the single particle aerodynamic drag term, depending on the new notion of particle connectivity. These methods are evaluated for potential utilization in practical simulations. Breakup experiments for drops in flows from prior studies suggest a critical Weber number relating to the onset of breakup for a drop. These data are replicated with the proposed model and it is shown that the proposed method can reasonably reproduce aspects of breakup for a range of scales with only a single tuned parameter.
查看更多>>摘要：Global demand for clean fuels is growing due to pollution and global warming. Undoubtedly, hydrogen is one of the main options for producing clean energy, which has been receiving special attention for years and global demand for it is constantly increasing every year. The global hydrogen market is currently valued at billions of dollars a year. Hydrogen can be used for a wide range of applications such as chemicals, food, glass, metal, etc. But one of the challenges facing the development of hydrogen production industries is the production of hydrogen from economical and eco-friendly sources and technologies. This means being able to predict the amount of hydrogen production from technology before launching it, as well as optimizing existing technologies for further production. Machine learning is widely recognized as one of the most efficient and effective tools for predicting hydrogen production. At the same time, hydrogen production technologies present important challenges that can often be addressed only with innovative machine learning algorithms and methods.
查看更多>>摘要：Sulfamethoxazole is a sulphonamide bacteriostatic antibiotic having poor solubility, resulting in a high prescribed dose of 800 mg/day. Accordingly, these high doses relate to an increased risk of adverse effects. In this contribution, a novel cocrystal of sulfamethoxazole-succinimide was prepared by mechanochemical synthesis to modulate the physicochemical properties. X-ray diffraction, thermal, and spectroscopic analyses were used to characterize the cocrystal thoroughly. Also, to gain an insight into the optimized structural geometry, important functional frequencies, and electronic properties, the density functional theory was used. The contribution of auxiliary interactions and inter-molecular interactions have been investigated by Hirshfeld surface analysis. Solubility and powder dissolution studies were performed to investigate the changes in the physicochemical properties. The cocrystal demonstrated an improvement in the solubility profile in aqueous media and an enhanced dissolution rate in the recommended dissolution media. Furthermore, accelerated stability studies under stress conditions were performed, where the cocrystal showed no indication of dissociation. The study demonstrates the significance of mechanochemical cocrystallization to modulate the physico-chemical properties of an API, along with an insight into spectroscopic, electronic and chemical conformation.
V. Villazon-LeonA. Bonilla-PetricioletJ.C. Tapia-Picazo
23页
查看更多>>摘要：Ionic liquids are compounds with interesting physical and chemical properties that can be applied to a wide variety of processes. The knowledge of their thermodynamic properties is essential for the design of products and processes. These properties include heat capacity, density, viscosity, thermal conductivity, melting point, surface tension, electrical conductivity, refractive index, thermal decomposition temperature, normal boiling point, critical properties, freezing point, isobaric expansivity, isothermal compressibility and static dielectric constant. However, the experimental database available of such properties for ionic liquids is limited, thus affecting the process design and modeling. Different thermodynamic models have been developed to estimate these properties and, group contribution models offer several advantages for these applications. This review covers different group contribution models reported and applied to estimate the thermodynamic properties of ionic liquids. The application, performance, and accuracy of these models for predicting the ionic liquids properties were analyzed and discussed. Some approaches combining group contribution models with artificial neural networks to estimate the thermodynamic properties of ionic liquids have been also described and exemplified. This review offers a survey of a variety of group contribution approaches that can be used to predict several thermodynamic properties of ionic liquids for process systems engineering.
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