ABSTRACT
As a typical type of organic flocculant, chitosan is limited by its poor water solubility and narrow pH range application. Grafting modification can improve chitosan's solubility and availability through linking macromolecular chains with other types of water-soluble groups or functional side groups. In this study, dielectric barrier discharge (DBD) was used to active the surface of chitosan, then activated chitosan was polymerized with acrylamide to synthesize a chitosan-based flocculant, chitosan-acrylamide (CS-AM). During the synthesis of CS-AM, the optimal conditions were determined as follows: discharge time of 5 min, discharge power of 60 W, total monomer mass concentration of 80 g L-1, polymerization time of 3 h, polymerization temperature of 70 °C, and m(CS) : m(AM) ratio of 1 : 3. The structure and morphological characteristics of CS-AM were investigated and analyzed by Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), thermogravimetric (TG) analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD) and N2 physical adsorption, respectively. The removal efficiency of kaolin suspension and CNTs suspension can reach up to 95.9% and 90.2% after flocculation of CS-AM. Furthermore, the zeta potential of the supernatant from the CS-AM treated kaolin suspension at different pH values was examined, and the flocculation mechanism of CS-AM was analyzed. This study provides new ideas for the preparation and development of modified chitosan and broadens its application in water treatment.
ABSTRACT
The flocculation performance of chitosan can be enhanced by grafting modification to overcome its disadvantages of poor water solubility. In this study, chitosan was modified by dielectric barrier discharge plasma and polymerized with acrylamide and aluminum chloride to synthesize a new chitosan-based flocculant, namely, chitosan-acrylamide-aluminum chloride (CA-PAC). After optimizing the synthesis conditions of CA-PAC, the best conditions were as follows: discharge time of 3 min, discharge power of 50 W, polymerization temperature of 60 °C, polymerization time of 3 h, total monomer concentration of 100 g/L, and m(AlCl3):m(CA) ratio of 2:1. Characterization was performed through SEM, XPS, FTIR, XRD, TG and 1H NMR. Results showed that the preparation of CA-PAC was successful. The influences of flocculant dosage, pH, and stirring intensity on flocculation efficiency were investigated. The removal efficiency of turbidity was 94.1 %. The investigation of the flocculation mechanism revealed that CA-PAC mainly relied on charge neutralization or the synergic action of electric neutralization, bridging, and roll-sweep under acidic and neutral conditions, but it depended on the joint action of adsorption bridging and net sweeping under alkaline conditions. This study provides new ideas for the preparation and development of modified chitosan and broadens its application in water treatment.
ABSTRACT
A crucial point in neuroscience is how to correctly decode cognitive information from brain dynamics for motion control and neural rehabilitation. However, due to the instability and high dimensions of electroencephalogram (EEG) recordings, it is difficult to directly obtain information from original data. Thus, in this work, we design visual experiments and propose a novel decoding method based on the neural manifold of cortical activity to find critical visual information. First, we studied four major frequency bands divided from EEG and found that the responses of the EEG alpha band (8-15 Hz) in the frontal and occipital lobes to visual stimuli occupy a prominent place. Besides, the essential features of EEG data in the alpha band are further mined via two manifold learning methods. We connect temporally consecutive brain states in the t distribution random adjacency embedded (t-SNE) map on the trial-by-trial level and find the brain state dynamics to form a cyclic manifold, with the different tasks forming distinct loops. Meanwhile, it is proved that the latent factors of brain activities estimated by t-SNE can be used for more accurate decoding and the stable neural manifold is found. Taking the latent factors of the manifold as independent inputs, a fuzzy system-based Takagi-Sugeno-Kang model is established and further trained to identify visual EEG signals. The combination of t-SNE and fuzzy learning can highly improve the accuracy of visual cognitive decoding to 81.98%. Moreover, by optimizing the features, it is found that the combination of the frontal lobe, the parietal lobe, and the occipital lobe is the most effective factor for visual decoding with 83.05% accuracy. This work provides a potential tool for decoding visual EEG signals with the help of low-dimensional manifold dynamics, especially contributing to the brain-computer interface (BCI) control, brain function research, and neural rehabilitation.
ABSTRACT
Molybdenum disulfide (MoS2) was added to the system after being treated with high-voltage pulse discharge plasma to improve the degradation efficiency of pollutants and reduce energy consumption. The discharge plasma-treated solution contains hydrogen peroxide and metal iron ions, and MoS2 addition can cause co-catalytic Fenton reaction. The effects of discharge time, initial pH, phenol concentration, MoS2 dosage, discharge voltage, and gas type on phenol removal and aqueous H2O2 concentration were mainly investigated. Results showed that the addition of MoS2 after plasma treatment can reduce the plasma treatment time by 70% and maintain or even increase the degradation efficiency of phenol from 40% (after 20 min of discharge plasma) to 92% (after turning off the discharge and dosing with MoS2 for 30 min). Acidic conditions (pH = 3-4) and oxygen were beneficial to phenol removal. MoS2 addition greatly improved the catalytic oxidation of discharge plasma. This study provides a promising direction for water treatment based on plasma technology.
