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Effluents before disinfection from four wastewater reclamation plants were treated with chlorine (Cl 2 ), ozone (O 3 ), chlorine dioxide (ClO 2 ), medium-pressure ultraviolet (MPUV) and four different combinations of the above, to evaluate the effect of disinfection processes on the genotoxicity removal by the SOS/umu test. Results showed that the genotoxicity increased after MPUV irradiation (10–100 mJ/cm 2 ), but declined when adopting other disinfection processes. The effectiveness of genotoxicity reduction by five chemical disinfectants was identified as: O 3 > pre-ozonation with Cl 2 ≈ ClO 2 > combination of ClO 2 and Cl 2 > Cl 2 . The sequential combination of MPUV, Cl 2 and O 3 reduced the genotoxicity to a level similar to the source water. The influence of differential disinfection process varied on iodinated wastewater, which is closely related to the competitive reactions between disinfectants, iodine and dissolved organic matters. The removal of genotoxic pollutants and the formation of genotoxic disinfection by-products are the two major factors that lead to the change in genotoxicity during disinfection. [ABSTRACT FROM AUTHOR]

Anion exchange membranes (AEMs) with excellent antifouling property are essential for treating highly saline organic wastewater through electrodialysis (ED). In this study, we proposed a strategy of surface charge inversion to construct a blocked- nanolayer based on in-suit dopamine (DA) deposition followed by grafting negative-charged 2-acrylamide-2-methylpropanesulfonic acid (AMPS) for promoting the antifouling performance of AEM. It's indicated that the surface hydrophilicity and negative charge density was gradually enhanced with the increase of AMPS grafting density without sacrifices of ion exchange capability, swelling ratio and desalination performance. In the simulated fouling experiments, the optimal AEM-AMPS-105 membrane exhibited excellent antifouling property due to the improved surface hydrophilicity and high electrostatic repulsion against organic matter. It's highlighted that the transmembrane voltage of modified membrane after operating 200 min was reduced from 7.12 V to 4.85 V with a significant decrease of energy consumption by 55.1 % while maintaining a high current efficiency level of 85.5 %. Moreover, the modified membrane performed significantly enhanced salt/contaminant selectivity and high stability in dye wastewater treatment. We anticipated that the construction of charge-blocked nanolayer by surface charge inversion offered a practical method for improving the organic fouling-resistance of AEMs. [Display omitted] • An anion exchange membrane with a negative-charged blocking nanolayer was developed by surface charge inversion. • Surface hydrophilicity and negative charge density was gradually improved with the increase of AMPS grafting density. • The constructed AMPS nanolayer contributed to formationing the hydration layer and enhancing the electrostatic exclusion effect. • Modified AEM exhibited excellent antifouling ability and stability. [ABSTRACT FROM AUTHOR]

Developing polyamide (PA) reverse osmosis (RO) membrane with chlorine resistance is of great significance for simplifying pretreatment processes and saving operating costs. Herein, we constructed an active layer capable of highly chlorine stability and regenerative chlorine resistance by introducing p-amino diphenylamine (p-ADA) with redox activity via a facile secondary interfacial reaction (s-IR) on PA membrane surface. The calculation of resistance-in-series model indicated that the introduction of p-ADA facilitated the increase of NaCl transmembrane resistance without sacrificing membrane permeance. Chlorination experiments under acid conditions proved the protection effect of p-ADA grafted layer due to its oxidation resistance, avoiding the direct attack by free chlorine to amide bonds of polyamide membrane. By virtue of the convertible modality of the p-ADA molecule between the quinone and benzene structures during redox process, modified membranes presented the capability of regenerative chlorine resistance. After the "chlorination-reduction" cycle experiments, the normalized flux of modified membranes remained 0.522 while contrasted PA membranes showed a flux of 0.278; and the corresponding normalized NaCl rejection of modified membranes maintained at 0.998 significantly higher than that of PA membranes (0.963). This study presents a straightforward and efficient approach to enhance the chlorine resistance of PA RO membranes. [Display omitted] • p-ADA was adopted to modify the PA RO membrane by a secondary interfacial reaction. • The grafted p-ADA could cover and heal the defects of the PA membrane. • The modified membranes showed improved chlorine resistance with a higher salt rejection. • The redox feature of p-ADA molecules endowed the modified membranes with regenerative chlorine resistance. [ABSTRACT FROM AUTHOR]

Diversified ion-selective separation applications have dramatically incentivized the exploitation and performance modulation of highly ion-selective nanofiltration (NF) membranes. However, the ion selectivity of NF membranes is synergistically governed by multi-scale factors of membrane structural parameters and operational parameters, with the intrinsic ion-selective mechanism still ambiguous. Herein, we proposed an ensemble machine learning (ML) method to decouple key factors affecting the ionic selectivity of polyamide NF membranes. Membrane structural parameters and operational parameters were typically extracted as input variables and linked to mono−/divalent ion selectivity by model training based on Random Forest and XGBoost algorithms. The feature importance assessment indicated the critical role of membrane structure parameters on ion selectivity, wherein pore radius dominated the mono−/divalent anionic selectivity while zeta potential for mono−/divalent cationic selectivity. Partial dependence analyses further depicted intensive insights regarding the influence of membrane structural parameters on ion selectivity. Moreover, stochastic dataset splitting measurements demonstrated the accurate predictive capability of the model simultaneously possessing excellent stability and reliability. We anticipated that the implementation of ensemble ML in explicating the intricate ion-selective mechanism created platforms for understanding the structure-membrane performance correlation and orientally manufacturing highly ion-selective NF membranes. [Display omitted] • Ensemble machine learning was implemented to decouple the key features affecting ion selectivities of polyamide membranes. • RF and XGBoost algorithms were adopted to learn from relevant variables and evaluate permutation features importance. • Mono-/divalent anionic selectivity was dominated by pore size while zeta potential for mono-/divalent cationic selectivity. [ABSTRACT FROM AUTHOR]

Noise and reverberation can severely degrade speech quality and intelligibility, so many deep neural network-based noisy-reverberant speech enhancement methods have been proposed, among which classic methods include spectral masking and spectral mapping. Spectrum masking and spectrum mapping have their advantages and disadvantages in different noise environments, and they are complementary. This paper proposes a dual branch deep interactive UNet (DBDIUNet) for monaural speech enhancement to combine the advantages of spectral mapping and spectral masking. The DBDIUNet uses a classical encoder-decoder architecture, including a shared encoder and two decoders. One decoder outputs the complex ideal ratio mask (cIRM), and the other outputs the enhanced complex spectrum. The two signals are coupled by coherent averaging to get the enhanced speech signal. A novel deep interaction structure is proposed for the interaction of information between the two decoders, which achieves a very significant performance improvement at the minimal cost of computational consumption and hyperparameters. Compared with the noisy speech on the Interspeech 2020 deep noise suppression challenge blind test set, DBDIUNet improves the WB-PESQ, NB-PESQ, STOI, SI-SDR indicators by 1.575, 0.955, 7.9%, 8.67 respectively. In the noisy-reverberant speech enhancement test, DBDIUNet improves the WB-PESQ, STOI, SI-SDR, DNSMOS, and SRMR by 0.98, 10.24%, 5.43, 1.51, 3.43, respectively, which exceeds the state-of-the-art model. • A two-branch speech enhancement method incorporating complex spectral masking and complex spectral mapping is proposed. • A novel deep interactive temporal-frequency attention module can effectively improve the information interaction between the two branches. • This paper discusses the effect of temporal length of temporal attention on model performance in speech enhancement tasks. • The proposed model has state-of-the-art performance in the denoising and dereverberation tasks. [ABSTRACT FROM AUTHOR]

Nanofiltration (NF) plays an increasingly central role in water/salts separation, which puts forward tailored requirements on NF membranes in a variety of application scenarios. However, the ambiguous separation mechanisms of NF including membrane structure parameters and operating conditions hinder the rational design of versatile NF membranes. Herein, machine learning was used to explore the correlation between membrane structure parameters and operating conditions with water/salts selectivity, and reveal the importance of the diverse features based on literature data. Two structural features of polyamide NF membrane (pore radius and zeta potential) and two operating parameters (pressure and feed concentration) were typically extracted and associated with water/salts selectivity. Random Forest and XGBoost models were employed to learn from relevant variables and assess their importance. The results showed that membrane structure parameters attached more importance to water/salts selectivity than that of operating conditions accompanying the variable influence for different typed salts, where symmetrical salts were mainly governed by size sieving while Donnan exclusion for asymmetrical salts. Structure-performance relationships between pore radius, zeta potential and diverse water/salts selectivity were established using partial dependence plot analysis. It is anticipated that the constructed comprehensive insights can be further leveraged to tackle performance modulation and oriented design of multi-scenarios NF membranes. [Display omitted] • Machine learning was used to understand NF separation mechanisms. • Random Forest and XGBoost models were employed to learn from relevant variables and assess features importance. • Symmetrical salts were mainly governed by size sieving while Donnan exclusion for asymmetrical salts. • The integrated management of pore size and zeta potential for the oriented design of versatile NF membranes was highlighted. [ABSTRACT FROM AUTHOR]

In this study, aminated PES substrates were prepared and applied for the investigation on the interfacial polymerization of piperazine (PIP) and 1,3,5-benzenetricarbonyl trichloride (TMC) thereon, with relatively low (PIP: 0.1 wt%, TMC: 0.01 wt%) and high (PIP: 0.5 wt%, TMC: 0.05 wt%) monomer concentration. In low concentration condition, thin, dense, and defect-free selective layers were synthesized on the aminated substrates. In high concentration condition, thin film composite (TFC) membranes with thin selective layers and without the intrusion of polyamide into the substrates were formed. The reactions between the aminated substrate and selective layer were confirmed by XPS analysis on the back surface of the selective layer. The aminated substrates based TFC membrane (TFC-48-H) showed high separation performance, including high water permeability as 20.6 ± 0.1 L/m2 h bar and high Na 2 SO 4 to NaCl selectivity as 86.7, indicating the application potential in divalent to monovalent salts separation process. A conceptual model was proposed to highlight the role of the aminated substrates in the interfacial polymerization process as (1) PIP loaders, (2) PIP diffusion hinders, and (3) polyamide intrusion chemically inhibitors in high monomer concentration condition. [Display omitted] • Interfacial polymerization process on the aminated substrate was investigated. • Thin, dense and defect-free selective layer was formed in low C PIP concentration. • In high C PIP condition, TFC membrane without the intrusion of polyamide was formed. • Aminated substrate based TFC membrane showed greatly improved Na 2 SO 4 to NaCl selectivity. • Conceptual model that highlighted the role of aminated substrate was proposed. [ABSTRACT FROM AUTHOR]