Enhanced antibacterial properties and suppressed biofilm growth on multi-walled carbon nanotube (MWCNT) blended polyethersulfone (PES) membranes

This study investigates the biofilm formation resistance of the multi-walled carbon nanotube (MWCNT) blended polyethersulfone (PES) membranes. The antimicrobial properties and biofilm formation resistance of these composite membranes were explored using Escherichia coli (E. coli) and Pseudomonas aeruginosa (P. aeruginosa) as model organisms. The results show that the dispersion of the MWCNTs in the membrane structure matters in determining the biofilm formation resistance of the composite membranes. Here, no colonies were observed on the composite membranes with 0.5 wt % of MWCNT content (C/P-0.5%) when the E. coli cells were deposited onto the membrane surface. Furthermore, when the membranes were incubated in P. aeruginosa suspensions, the C/P-0.5% membrane showed almost 87 % less biofilm formation at 24 h, with the biofilm formation resistance increasing to 92 % at 4 d, compared to the neat PES membrane. Finally, there was no MWCNT release during the water filtration of the composite membranes

Co-occurrence matrix analysis-based semi-supervised training for object detection

One of the most important factors in training object recognition networks using convolutional neural networks (CNNs) is the provision of annotated data accompanying human judgment. Particularly, in object detection or semantic segmentation, the annotation process requires considerable human effort. In this paper, we propose a semi-supervised learning (SSL)-based training methodology for object detection, which makes use of automatic labeling of un-annotated data by applying a network previously trained from an annotated dataset. Because an inferred label by the trained network is dependent on the learned parameters, it is often meaningless for re-training the network. To transfer a valuable inferred label to the unlabeled data, we propose a re-alignment method based on co-occurrence matrix analysis that takes into account one-hot-vector encoding of the estimated label and the correlation between the objects in the image. We used an MS-COCO detection dataset to verify the performance of the proposed SSL method and deformable neural networks (D-ConvNets) as an object detector for basic training. The performance of the existing state-of-the-art detectors (DConvNets, YOLO v2, and single shot multi-box detector (SSD)) can be improved by the proposed SSL method without using the additional model parameter or modifying the network architecture.Comment: Submitted to International Conference on Image Processing (ICIP) 201

Coupled Processes of Fluid Flow, Solute Transport, and Geochemical Reactions in Reactive Barriers

A complex pattern of coupling between fluid flow and mass transport develops when heterogeneous reactions occur. For instance, dissolution and precipitation reactions can change a porous medium's physical properties, such as pore geometry and thus permeability. These changes influence fluid flow, which in turn impacts the composition of dissolved constituents and the solid phases, and the rate and direction of advective transport. Two-dimensional modeling studies using TOUGHREACT were conducted to investigate the coupling between flow and transport developed as a consequence of differences in density, dissolution precipitation, and medium heterogeneity. The model includes equilibrium reactions for aqueous species, kinetic reactions between the solid phases and aqueous constituents, and full coupling of porosity and permeability changes resulting from precipitation and dissolution reactions in porous media. In addition, a new permeability relationship is implemented in TOUGHREACT to examine the effects of geochemical reactions and density difference on plume migration in porous media. Generally, the evolutions in the concentrations of the aqueous phase are intimately related to the reaction-front dynamics. Plugging of the medium contributed to significant transients in patterns of flow and mass transport

Kinetic decomposition of ozone and para-chlorobenzoic acid (pCBA) during catalytic ozonation

The decomposition of ozone and para-chlorobezoic acid (pCBA) using ozone and ozone/goethite were investigated under various conditions to define the characteristics of ozonation and catalytic ozonation. A continuous analysis of the kinetics of the reaction between ozone and pCBA was established, and the decay rate of ozone and pCBA with/without goethite was determined. The decay rate of ozone in the presence of goethite was much higher than in the absence of goethite and was strongly pH dependent due to the reactivities of ozone with the three surface species ( drop FeOH2+, drop Fe0H, drop FeO-) of goethite. The removal pattern of ionized pCBA at different pHs agreed well with the instantaneous ozone demand. The removal rate of pCBA and instantaneous ozone demand with/without t-butanol at different pHs were compared to elucidate the reaction mechanisms associated with the three reaction sites: (i) on the surface of the catalyst, (ii) at the catalyst-solution interface, and (iii) in the bulk solution. (C) 2004 Elsevier Ltd. All rights reservedclose594

Fabrication and Investigation of Acid Functionalized CNT Blended Nanocomposite Hollow Fiber Membrane for High Filtration and Antifouling Performance in Ultrafiltration Process

In this study, we fabricated a nanocomposite polyethersulfone (PES) HF membrane by blending acid functionalized carbon nanotubes (FCNT) to address the issue of reduced membrane life, increased energy consumption, and operating costs due to low permeability and membrane fouling in the ultrafiltration process. Additionally, we investigated the effect of FCNT blending on the membrane in terms of the physicochemical properties of the membrane and the filtration and antifouling performance. The FCNT/PES nanocomposite HF membrane exhibited increased water permeance from 110.1 to 194.3 LMH/bar without sacrificing rejection performance and increased the flux recovery ratio from 89.0 to 95.4%, compared to a pristine PES HF membrane. This study successfully developed a high filtration and antifouling polymer-based HF membrane by blending FCNT. Furthermore, it was validated that blending FCNT into the membrane enhances the filtration and antifouling performance in the ultrafiltration process

Boron Nitride Nanotube (BNNT) Membranes for Energy and Environmental Applications

Owing to their extraordinary thermal, mechanical, optical, and electrical properties, boron nitride nanotubes (BNNTs) have been attracting considerable attention in various scientific fields, making it more promising as a nanomaterial compared to other nanotubes. Recent studies reported that BNNTs exhibit better properties than carbon nanotubes, which have been extensively investigated for most environment-energy applications. Irrespective of its chirality, BNNT is a constant wide-bandgap insulator, exhibiting thermal oxidation resistance, piezoelectric properties, high hydrogen adsorption, ultraviolet luminescence, cytocompatibility, and stability. These unique properties of BNNT render it an exceptional material for separation applications, e.g., membranes. Recent studies reported that water filtration, gas separation, sensing, and battery separator membranes can considerably benefit from these properties. That is, flux, rejection, anti-fouling, sensing, structural, thermal, electrical, and optical properties of membranes can be enhanced by the contribution of BNNTs. Thus far, a majority of studies have focused on molecular simulation. Hence, the requirement of an extensive review has emerged. In this perspective article, advanced properties of BNNTs are analyzed, followed by a discussion on the advantages of these properties for membrane science with an overview of the current literature. We hope to provide insights into BNNT materials and accelerate research for environment-energy applications

Efficacy of Electrically-Polarized 3D Printed Graphene-blended Spacers on the Flux Enhancement and Scaling Resistance of Water Filtration Membranes

In this research, an electrically polarized graphene-polylactic acid (E-GRP) spacer is introduced for the first time by a novel fabrication method, which consists of 3D printing followed by electrical polarization under a high voltage electric field (1.5 kV/cm). The fabricated E-GRP was tested in an osmotic-driven process (forward osmosis system) to evaluate its performance in terms of water flux, reverse solute flux, and ion attraction compared to a 3D printed nonpolarized graphene-polylactic acid (GRP) spacer and a polylactic acid (PLA) spacer. The use of the developed E-GRP as a draw spacer showed >50% water flux enhancement (32.4 +/- 2 Liter/m(2)/h (LMH)) compared to the system employing the GRP (20.5 +/- 2.3 LMH) or PLA (20.8 +/- 2.1 LMH) spacer. This increased water flux was attributed to the increased local osmotic pressure across the membrane surface due to the ions adsorbed by the polarized (E-GRP) spacer. As a feed spacer, the E-GRP also retarded the gypsum scaling on the membrane compared to the GRP spacer due to the dispersion effect of electrostatic forces between the gypsum aggregation and negatively charged surfaces. The electric polarization of the E-GRP spacer was shown to be maintained for >100 h by observing its salt adsorption properties (in a 3 M NaCl solution)