To enable portable kidney dialysis for end-stage renal disease, the regeneration of the dialysate in a closed loop system is a critical technical barrier. Currently dialysis treatment uses ∼120 L of dialysate per 4 h session, to remove urea as well as other toxins from the blood, far exceeding usable weights for a portable system. We have developed an efficient photooxidation system based on hydrothermally grown TiO2 nanowires, UV LEDs, and catalytic gas diffusion barriers to decompose urea from the dialysate at rates sufficient to remove daily production of urea at 15 g/day. With 365 nm LED irradiation of 4 mW/cm2, dialysate simulant solutions of 10 mM urea/0.15 M NaCl photocurrent density of ∼1 mA/cm2 was achieved, corresponding to 40% quantum efficiency in urea decomposition per incident photon. From performance parameters, a feasible portable device with 0.23 m2 active area and a current draw of 11 A is able to decompose a daily 15 g urea production sufficient to regenerate dialysate.
Graphene oxide (GO) is a promising membrane system for chemical separation applications due to its 2-D nanofluidics properties and an ability to control interplanar spacing for selectivity. The permeance of water, methanol (MeOH) and isopropyl alcohol (IPA) through 5 µm thick membranes was found to be 0.38 ± 0.15, 0.33 ± 0.16 and 0.42 ± 0.31 LMH/bar (liter/m2·h·bar), respectively. Interestingly, the permeance of a water–alcohol mixture was found to be dramatically lower (~0.01 LMH/bar) than any of its components. Upon removing the solvent mixture, the transmembrane flux of the pure solvent was recovered to near the original permeance. The interlayer space of a dried GO membrane was found to be 8.52 Å, which increased to 12.19 Å. 13.26 Å and 16.20 Å upon addition of water, MeOH and IPA. A decrease in d-space, about 2 Å, was consistently observed when adding alcohol to water wetted GO membrane and an optical color change and reduction in permeance. A newly proposed mechanism of a partial reduction of GO through a catalytic reaction with the water–alcohol mixture is consistent with experimental observations.
In order to clarify the proton transport phenomena in Nafion/carbon nanotubes (CNTs) composite membranes, we focused on the interfacial transport between Nafion and graphene sheets (GSs). We investigated the water content dependence of proton transport and structural properties at the interface between Nafion and GSs using molecular dynamics simulations. The density distribution, water cluster analysis at the interface region, and the self-diffusion coefficient of protons at the interface region were obtained at different water contents. The self-diffusion coefficients of protons at the interface were larger than those of the Nafion bulk for all the water contents because of the formation of water layer near the interface. Our findings provide insight into the relationship between the proton transport and the interfacial structure at molecular level, which suggests a possible improvement on proton transport with addition of CNTs with high specific surface area.
In order to improve the power generation efficiency of polymer electrolyte fuel cells (PEFC), it is necessary to increase the flux of proton transport inside a proton exchange membrane (PEM) under high temperature and low humidity conditions. Nowadays, the Nafion membrane is used as a reference for all proton exchange membranes. This membrane developed by DuPont company demonstrates a high proton conductivity value, chemical stability and prolonged using in fuel cell conditions in comparison with other membranes. However proton transport properties are greatly reduced when the membranes are degraded. Researches have been actively conducted to solve the problem of proton transport reduction in PEM under high temperature and low humidity conditions by two approaches. One of the research focuses is to design alternative materials based on those engineering polymers, for example, polybenzimidazole, poly(ether sulfone), and poly(ether ketone). Another research focus is the introduction of additives. Among the many additives, carbon nanotubes (CNTs) which are next-generation materials with a high aspect ratio and excellent thermal durability and mechanical properties, have been attracting attention. Previous studies have reported that the PEEK (poly ether ether ketone ) / CNT composite membranes show higher durability than Nafion membranes. And the proton transport properties in Nafion / sulfonated CNT composite membranes are improved over the that of Nafion membranes. It is said that the proton transport property is improved by forming a proton path which is made by the influence of the structural characteristics of CNT. However, the proton transport mechanism at the interface between the carbon surface of CNT and the polymer has not been fully understood. The purpose of this study is to clarify the proton transport mechanism in the interface between the carbon surface region and the polymer region and to evaluate the effects of functional groups with carbon surface by using molecular dynamics (MD) simulations. The surface of a CNT was modeled with a graphene sheet (GS). The diameter of the CNTs used in the experiment is about 10-20 nm, which is beyond capability of our MD simulations, and thus the CNT surface was assumed to be a flat surface. The simulation system is shown in Fig. 1. GSs were placed at the top and bottom of the simulation box, and polymer, water molecules, and hydronium ions were placed between them. In order to evaluate the influence of distances between GSs on structural characteristics and transport property, we prepared calculation systems at the wall distances of 4, 6, 8 and 10 nm. We calculated the density distribution in the direction vertical to the GS and the self-diffusion coefficient of the protons at the GS surface region and the center region. Furthermore, a hydrophilic sulfonated GS was prepared by putting sulfo groups to the hydrophobic GS to investigate the effects of the hydrophilic and hydrophobic GS interface on proton transport. The results of the density distribution showed tha...
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