A charged nanocomposite membrane via co-deposition of gallic acid and polyethyleneimine-silver for improving separation and antibacterial properties.

Pharmaceuticals have been continuously detected from surface water and groundwater. In order to improve the rejection performance of pharmaceuticals by a nanofiltration membrane (NF), a positively charged membrane was prepared by co-deposition of natural gallic acid and polyethyleneimine on the polyacrylonitrile hydrolysis membrane. Effects of gallic acid concentration, polyethylene imine concentration, reaction time, and the molecular weight of polyethylene imine were documented. The physical and chemical properties of the membrane were also investigated by surface morphology, hydrophilicity, surface charge, and molecular weight cut-off. The optimized membrane had a molecular weight cut-off of about 958 Da and possessed a pure water permeability of 74.21 L·m-2·h-1·MPa-1. The results exhibited salt rejection in the following order: MgCl2 > CaCl2 > MgSO4 > Na2CO3 > NaCl > Na2SO4, while the rejection ability of pharmaceuticals is as follows: amlodipine > atenolol > carbamazepine > ibuprofen, suggesting that the positively charged membrane has enhanced retention to both divalent cations and charged pharmaceuticals. In addition, the antibacterial membrane was obtained by loading silver nanoparticles onto the positively charged membrane, which greatly improved the antibacterial ability of the membrane.

A super-hydrophilic partially reduced graphene oxide membrane with improved stability and antibacterial properties.

In order to improve stability and antibacterial property, a novel super-hydrophilic partially reduced graphene oxide membrane was prepared by interfacial polymerization of piperazine and partially reduced graphene oxide as aqueous solution and trimesoyl chloride as organic solution. Fourier transform infrared spectroscopy, scanning electron microscope, and contact angle measurement were conducted to probe the morphology and properties of the membranes. The modified membrane possessed super-hydrophilicity, improved durability and swelling resistance. The optimized membrane had a molecular weight cut off of about 674 Da and possessed a pure water permeability of 49.86 L·m-2·h-1·MPa-1. The retention order of salts was Na2SO4 > MgSO4 > MgCl2 > Na2CO3 > CaCl2 > NaCl, while the rejection for four kinds of pharmaceuticals followed the order of ibuprofen (92%) > carbamazepine (87%) > amlodipine (80%) > atenolol (76%), indicating that the negatively charged membrane could improve the retention performance by the electrostatic repulsive effect. Moreover, the enhanced antibacterial performance of membrane attributed to the dual effects of the super-hydrophilicity and the tea polyphenols antibacterial material loading, which may alter the charge distribution on and within the membrane, leading to loss of cell viability.

Multiscale Temporal Self-Attention and Dynamical Graph Convolution Hybrid Network for EEG-Based Stereogram Recognition.

Stereopsis is the ability of human beings to get the 3D perception on real scenarios. The conventional stereopsis measurement is based on subjective judgment for stereograms, leading to be easily affected by personal consciousness. To alleviate the issue, in this paper, the EEG signals evoked by dynamic random dot stereograms (DRDS) are collected for stereogram recognition, which can help the ophthalmologists diagnose strabismus patients even without real-time communication. To classify the collected Electroencephalography (EEG) signals, a novel multi-scale temporal self-attention and dynamical graph convolution hybrid network (MTS-DGCHN) is proposed, including multi-scale temporal self-attention module, dynamical graph convolution module and classification module. Firstly, the multi-scale temporal self-attention module is employed to learn time continuity information, where the temporal self-attention block is designed to highlight the global importance of each time segments in one EEG trial, and the multi-scale convolution block is developed to further extract advanced temporal features in multiple receptive fields. Meanwhile, the dynamical graph convolution module is utilized to capture spatial functional relationships between different EEG electrodes, in which the adjacency matrix of each GCN layer is adaptively tuned to explore the optimal intrinsic relationship. Finally, the temporal and spatial features are fed into the classification module to obtain prediction results. Extensive experiments are conducted on collected datasets i.e., SRDA and SRDB, and the results demonstrate the proposed MTS-DGCHN achieves outstanding classification performance compared with the other methods. The datasets are available at https://github.com/YANGeeg/TJU-SRD-datasets and the code is at https://github.com/YANGeeg/MTS-DGCHN.

A high stability GO nanofiltration membrane preparation by co-deposition and crosslinking polydopamine for rejecting dyes.

In order to improve the stability of nanofiltration membrane in separation and purification, a novel polyelectrolyte multilayer nanofiltration membrane was facilely prepared by co-deposition of polydopamine (PDA) and polyethyleneimine (PEI) on the polyethersulfone (PES) ultrafiltration membrane substrate, followed by immersing graphene oxide (GO) solution, and crosslinking PDA. The modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM), water contact angle, their saline flux and ability to reject salt and dye were determined. The results also exhibited salt rejection ability as Na2SO4 > K2SO4 > MgSO4 > NaCl > KCl > MgCl2, suggesting the higher rejection of divalent anion. Also, the retention order of the dye by the GO modified membrane is DY86 > DB19 > AG27 > DY142 > DB56 > AR151 > VB5, indicating that the GO modified membrane has better rejection of negatively charged dyes as well as higher molecular weight dyes. Ethanol and hypochlorite resistance tests under different pH conditions showed the membranes coated GO enhanced stability in regard to salt rejection properties. Significantly, the anti-biological test confirmed the growth rate of microalgae on the GO introduced membrane was decreased greatly due to enhanced stability and lower roughness.