RESUMO
The use of co-metabolic substrates is effective for polycyclic aromatic hydrocarbons (PAHs) removal, but the potential of the high phenol concentrations in coal chemical wastewater (CCW) as a co-metabolic substrate in microbial electrolysis cell (MEC) has been neglected. In this study, the efficacy of varying phenol concentrations in comparison to simple substrates for degrading naphthalene in MEC under comparable COD has been explored. Results showed that phenol as a co-metabolic substrate outperformed sodium acetate and glucose in facilitating naphthalene degradation efficiency at 50 mg-COD/L. The naphthalene removal efficiency from RP, RA, and RG was found to be 84.11 ± 0.44 %, 73.80 ± 0.27 % and 72.43 ± 0.34 %, respectively. Similarly, phenol not only enhanced microbial biomass more effectively, but also exhibited optimal COD metabolism capacity. The addition of phenol resulted in a stepwise reduction in the molecular weight of naphthalene, whereas sodium acetate and glucose led to more diverse degradation pathways. Some bacteria with the potential ability to degrade PAHs were detected in phenol-added MEC, including Alicycliphilus, Azospira, Stenotrophomonas, Pseudomonas, and Sedimentibacter. Besides, phenol enhanced the expression of ncrA and nmsA genes, leading to more efficient degradation of naphthalene, with ncrA responsible for mediating the reduction of the benzene ring in naphthalene and nmsA closely associated with the decarboxylation of naphthalene. This study provides guidance for the effective co-degradation of PAHs in CCW with MEC, demonstrating the effectiveness of using phenol as a co-substrate relative to simple substrates in the removal of naphthalene.
RESUMO
We propose a physical information neural network with learning rate decay strategy (LrD-PINN) to predict the dynamics of symmetric, asymmetric, and antisymmetric solitons of the self-defocusing saturable nonlinear Schrödinger equation with the PT-symmetric potential and boost the predicted evolutionary distance by an order of magnitude. Taking symmetric solitons as an example, we explore the advantages of the learning rate decay strategy, analyze the anti-interference performance of the model, and optimize the network structure. In addition, the coefficients of the saturable nonlinearity strength and the modulation strength in the PT-symmetric potential are reconstructed from the dataset of symmetric soliton solutions. The application of more advanced machine learning techniques in the field of nonlinear optics can provide more powerful tools and richer ideas for the study of optical soliton dynamics.
RESUMO
A novel biochar involving pyrolysis of dewatered algal waste combined with KOH and residual FeCl3 co-activation was synthesized as an efficient sorbent specifically for Hg0 removal from coal-fired flue gas. It was found that the SBET of biochar co-activated by KOH and FeCl3 (BCFK) was 195.82 m2 g-1, much higher than that of single FeCl3 activated biochar (BCF) of 133.38 m2 g-1 and un-activated biochar (UBC) of 20.36 m2 g-1. Furthermore, BCFK exhibited higher magnetization characteristics as well as elemental Fe and Cl contents of 2.71% and 10.33%, respectively, based on the combined characterization of XPS and VSM, etc., which is a jump of about 10-fold compared to BCF. This allows BCFK to show the best Hg0 removal capability of 689.66 µg g-1 under the inlet Hg0 concentration of 100 µg m-3 and 150 °C, according to pseudo-second-order kinetic model. Further analysis by XPS and Hg-TPD (Temperature Programmed Desorption) revealed that oxidation by Cl∗ radicals and C-Cl as well as weak chemisorption contributed to the removal of Hg0. Eventually, this efficient, simply prepared, low-cost and easily separable biochar distinguished itself in comparison to other materials. This will undoubtedly promote the valorization of algae and provide a reliable alternative material for the treatment of coal-fired flue gas.
