Effects of channel size, wall wettability, and electric field strength on ion removal from water in nanochannels

Molecular dynamics simulations are employed to estimate the effect of nanopore size, wall wettability, and the external field strength on successful ion removal from water solutions. It is demonstrated that the presence of ions, along with the additive effect of an external electric field, constitute a multivariate environment that affect fluidic interactions and facilitate, or block, ion drift to the walls. The potential energy is calculated across every channel case investigated, indicating possible ion localization, while electric field lines are presented, to reveal ion routing throughout the channel. The electric field strength is the dominant ion separation factor, while wall wettability strength, which characterizes if the walls are hydrophobic or hydrophilic has not been found to affect ion movement significantly at the scale studied here. Moreover, the diffusion coefficient values along the three dimensions are reported. Diffusion coefficients have shown a decreasing tendency as the external electric field increases, and do not seem to be affected by the degree of wall wettability at the scale investigated here.

Phosphorylated cellulose paper as highly efficient adsorbent for cadmium heavy metal ion removal in aqueous solutions

In search for more effective and eco-friendly adsorbent materials, this study comprehensively investigated Cd2+ adsorption onto phosphorylated cellulose paper (PCP).

Novel Thermosensitive-co-Zwitterionic Sulfobetaine Gels for Metal Ion Removal: Synthesis and Characterization

Zwitterionic betaine polymers are promising adsorbents for the removal of heavy metal ions from industrial effluents. Although the presence of both negative and positively charged groups imparts them the ability to simultaneously remove cations and anions, intra- and/or inter-chain interactions can significantly reduce their adsorption efficiencies. Therefore, in this study, novel gels based on crosslinked co-polymers of thermosensitive N-isopropylacrylamide (NIPAAM) and zwitterionic sulfobetaine N,N-dimethylacrylamido propyl ammonium propane sulfonate (DMAAPS) were synthesized, characterized, and evaluated for ion removal. Fourier-transform infrared (FTIR) and proton nuclear magnetic resonance (1H NMR) analyses confirmed the success of the co-polymerization of NIPAAM and DMAAPS to form poly(NIPAAM-co-DMAAPS). The phase transition temperature of the co-polymer increased with increasing DMAAPS content in the co-polymer, indicating temperature-dependent amphiphilic behavior, as evidenced by contact angle measurements. The ion adsorption analyses of the poly(NIPAAM-co-DMAAPS) gels indicated that co-polymerization increased the molecular distance and weakened the interaction between the DMAAPS-charged groups (SO3− and N+), thereby increasing the ion adsorption. The results confirmed that, with a low concentration of DMAAPS in the co-polymer gels (~10%), the maximum amount of Cr3+ ions adsorbed onto the gel was ~58.49% of the sulfonate content in the gel.

The Application of Principal Component Analysis (PCA) for the Optimization of the Conditions of Fabrication of Electrospun Nanofibrous Membrane for Desalination and Ion Removal

Nowadays, acquiring a water supply for urban and industrial uses is one of the greatest challenges facing humanity for ensuring sustainability. Membrane technology has been considered cost-effective, encompasses lower energy requirements, and at the same time, offers acceptable performance. Electrospun nanofibrous membranes (ENMs) are considered a novel and promising strategy for the production of membranes that could be applied in several treatment processes, especially desalination and ion removal. In this study, we apply an unsupervised machine-learning strategy, the so-called principal component analysis (PCA), for the purpose of seeking discrepancies and similarities between different ENMs. The main purpose was to investigate the influence of membrane fabrication conditions, characteristics, and process conditions in order to seek the relevance of the application of different electrospun nanofibrous membranes (ENMs). Membranes were majorly classified into single polymers/layers, from one side, and dual multiple layer ENMs, from another side. For both classes, variables related to membrane fabrication conditions were not separated from membrane characterization variables. This reveals that membranes’ characteristics not only depend on the chemical composition, but also on the fabrication conditions. On the other hand, the process conditions of ENM fabrication showed an extensive effect on membranes’ performance.

Optimization of Chitosan Surface Response Methodology (Natural and Commercial) Used for Chromium Ion Removal from Wastewater across Different Parameters

Chromium is one of the most significant metals used in the industry. There are many techniques for treating different types of industrial waste water that include chromium ion. In this study, the authors successfully adsorbed the chromium ion from alkaline aqueous solutions using different prepared types of chitosan as adsorbent materials. For the simultaneous sorption behaviour, the adsorption potential of the produced adsorbent was investigated for Cr+6 in a batch system. Natural chitosan was extracted from shrimp shell as it contains about 8–10% chitin which is used in the production of chitosan. The removal percentage of Cr+6 reached 99% after grafting natural and commercial chitosan at specific conditions. Several isotherm models have been used for mechanistic studies. The results indicated that the adsorption data for commercial chitosan is well-fitted by the Freundlich isotherm, Langmuir for commercial grafted, natural and natural grafted chitosan. Kinetic and equilibrium studies showed that the experimental data of Cr+6 were better described by the pseudo-first-order model for commercial chitosan and fitted the pseudo-second-order model for different types of chitosan used. Significantly, in order to scale this effective strategy on an industrial scale, response surface methodology (RSM) was used as a modelling tool to optimise process parameters such as ion concentrations, utilising Statistica Software.