Meta-analyzing the mechanism of pyrogenic biochar strengthens nitrogen removal performance in sulfur-driven autotrophic denitrification system: Evidence from metatranscriptomics.

Sulfur-driven autotrophic denitrification (SAD) exhibits significant benefits in treating low carbon/nitrogen wastewater. This study presents an eco-friendly, cost-effective, and highly efficient method for enhancing nitrogen removal performance. The addition of biochar prepared at 300 °C (BC300) notably increased nitrogen removal efficiency by 31.

Quantifying interfacial interactions for improved membrane antifouling: A novel approach using triangulation and surface element integration method.

To gain a thorough understanding of interfacial behaviors such as adhesion and flocculation controlling membrane fouling, it is necessary to simulate the actual membrane surface morphology and quantify interfacial interactions. In this work, a new method integrating the rough membrane morphology reconstruction technology (atomic force microscopy (AFM) combining with triangulation technique), the surface element integration (SEI) method, the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, the compound Simpson's approach, and the computer programming was proposed. This new method can exactly mimic the real membrane surface in terms of roughness and shape, breaking the limitation of previous fractal theory and Gaussian method where the simulated membrane surface is only statistically similar to the real rough surface, thus achieving a precise description of the interfacial interactions between sludge foulants and the real membrane surface.

A novel composite membrane for simultaneous separation and catalytic degradation of oil/water emulsion with high performance.

It is of great significance to develop novel membranes with dual-function of simultaneously separating oil/water emulsion and degrading the contained water-miscible toxic organic components. To meet this requirement, a dual-functional Ni nanoparticles (NPs)@Ag/C-carbon nanotubes (CNTs) composite membrane was fabricated via electroless nickel plating strategy in this study. The as-prepared composite membrane possessed superhydrophilicity with water contact angle of 0° and splendid underwater oleophobic property with oil contact angle of 142°.

Synergistic fouling behaviors and mechanisms of calcium ions and polyaluminum chloride associated with alginate solution in coagulation-ultrafiltration (UF) process.

Effects of calcium ions and polyaluminum chloride (PACl) on membrane fouling in coagulation-ultrafiltration (UF) process were investigated in this study. Filtration tests demonstrated three interesting filtration behaviors: 1) high specific filtration resistance (SFR) of alginate solution with low CaCl or PACl addition (e. g.

New insights into membrane fouling by alginate: Impacts of ionic strength in presence of calcium ions.

While water chemistry (e.g., ionic strength, calcium concentration and organic foulants) is the primary property of surface water, its effects on membrane fouling in process of membrane-based water production and seawater pretreatment have not well investigated.

Filtration behaviors and fouling mechanisms of ultrafiltration process with polyacrylamide flocculation for water treatment.

This study aims to investigate thermodynamic mechanisms of filtration behaviors of ultrafiltration (UF) process with polyacrylamide (PAM) flocculation for surface water treatment, which has not been investigated previously. It was interestingly found that, filtration of durably mixed sodium alginate (SA) solution corresponded to an extraordinarily high specific filtration resistance (SFR) (3.28 × 10 m·kg without polyacrylamide addition) and a V-shaped profile of SFR characterized by a sharp fall followed by a correspondingly sharp rise along with the increase in PAM addition concentration.

Application of radial basis function artificial neural network to quantify interfacial energies related to membrane fouling in a membrane bioreactor.

Efficient quantification of interfacial energy related with membrane fouling represents the primary interest in membrane bioreactors (MBRs) as interfacial energy determines foulant layer formation. In this study, radial basis function (RBF) artificial neural networks (ANNs) with five related factors as input variables were applied to quantify interfacial energy with randomly rough membrane surface. It was found that, RBF ANNs could well capture the complex non-linear relationships between the related factors and interfacial energy.