Advanced (bio)fouling resistant surface modification of PTFE hollow-fiber membranes for water treatment.

Membrane surface treatment to modify anti-(bio)fouling resistivity plays a key role in membrane technology. This paper reports on the successful use of air-stimulated surface polymerization of dopamine hydrochloride incorporated ZnO nanoparticles (ZnO NPs) for impeding the intrinsic hydrophobicity and low anti-(bio)fouling resistivity of polytetrafluoroethylene (PTFE) hollow-fiber membranes (HFMs). The study involved the use of pristine and polydopamine (Pdopa) coated PTFE HFMs, both with and without the presence of an air supply and added ZnO NPs. Zeta potential measurements were performed to evaluate the dispersion stability of ZnO NPs prior to immobilization, while morphological characterization and time-dependency of the Pdopa growth layer were illustrated through scanning electron microscopy. Pdopa surface polymerization and ZnO NPs immobilization were confirmed using FT-IR and EDX spectroscopy. Transformation of the PTFE HFM surface features to superhydrophilic was demonstrated through water contact angle analysis and the stability of immobilized ZnO NPs assessed by ICP analysis. Anti-fouling criteria and (bio)fouling resistivity performance of the surface-modified membranes were assessed through flux recovery determination of bovine serum albumin in dead-end filtration as well as dynamic-contact-condition microbial evaluation against Staphylococcus spp. and Escherichia coli, respectively. The filtration recovery ratio and antimicrobial results suggested promising surface modification impacts on the anti-fouling properties of PTFE HFM. As such, the method represents the first successful use of air-stimulated Pdopa coating incorporating ZnO NPs to induce superhydrophilic PTFE HFM surface modification. Such a method can be extended to the other membranes associated with water treatment processes.

A risk-based soft sensor for failure rate monitoring in water distribution network via adaptive neuro-fuzzy interference systems.

Water Distribution Networks (WDNs) are considered one of the most important water infrastructures, and their study is of great importance. In the meantime, it seems necessary to investigate the factors involved in the failure of the urban water distribution network to optimally manage water resources and the environment. This study investigated the impact of influential factors on the failure rate of the water distribution network in Birjand, Iran. The outcomes can be considered a case study, with the possibility of extending to any similar city worldwide. The soft sensor based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) was implemented to predict the failure rate based on effective features. Finally, the WDN was assessed using the Failure Modes and Effects Analysis (FMEA) technique. The results showed that pipe diameter, pipe material, and water pressure are the most influential factors. Besides, polyethylene pipes have failure rates four times higher than asbestos-cement pipes. Moreover, the failure rate is directly proportional to water pressure but inversely related to the pipe diameter. Finally, the FMEA analysis based on the knowledge management technique demonstrated that pressure management in WDNs is the main policy for risk reduction of leakage and failure.

Investigation of the effects of starch on the physical and biological properties of polyacrylamide (PAAm)/starch nanofibers.

Here, we report the development of a new polyacrylamide (PAAm)/starch nanofibers' blend system and highlight its potential as substrate for efficient enzyme immobilization. PAAm was synthesized and blended with starch. The final blend was then electrospun into nanofibers. The response surface methodology was used to analyze the parameters that control nanofiber's diameter. Electrospun mat was then modified either by cross-linking or phytase immobilization using silane coupling agent and glutaraldehyde chemistry. Physico-chemical properties of blends were investigated using spectroscopic and thermal studies. The evaluation of immobilized enzyme kinetics on both pure and the starch blended PAAm nanofibers was performed using Michaelis-Menten kinetic curves. Fourier transform infrared spectroscopy results along with differential scanning and X-ray diffraction confirmed that blending was successfully accomplished. TGA analysis also demonstrated that the presence of starch enhances the thermal degradability of PAAm nanofibers. Finally, it was shown that addition of starch to PAAm increases the efficacies of enzyme loading and, therefore, significantly enhances the activity as well as kinetics of the immobilized enzyme on electrospun blend mats.