Construction of self-repairing polyethersulfone membrane with high density hydrophilic microregions by two dimensional restricted channels for enhanced dyes/salts selective separation.

Based on the dye/salts separation efficiency and membrane injury caused by serious pollution of dye/salts wastewater, this study constructed a 2D tight ultrafiltration membrane that could both solve the membrane injury problem and improve the dye/salts separation efficiency, the compatibility of good self-healing performance and penetration performance by 2D material magnesium-aluminum Layered double hydroxide (MgAl-LDH). The self-repairing of physical injury was achieved through the swelling effect of AMPS-PAN, this property was proved by permeate flux, the retention performance of salts in dye/salts solution, the comparison of scanning electron microscope (SEM), and the mechanical strength after physical injury. The healing of chemical injury occured through the reaction of CC and polyethersulfone chain breakage, which was confirmed by X-ray photoelectron spectroscopy (XPS), permeate flux, the retention performance of salts in dye/salts solution, and mechanical property. The high separation efficiency of dye/salts was achieved through 2D material MgAl-LDH, which was proved by separation selectivity ɑ. The compatibility of good self-healing performance and penetration performance was obtained by 2D material MgAl-LDH, which was proved by the penetration and self-healing performance. Morever, the membrane illustrated excellent both permeability and dye/sals separation efficiency, just like the permeate flux, the retention performance of sodium sulfate in methyl blue/sodium sulfate solution, the retention performance of Na2SO4 in methyl blue/Na2SO4 solution, the retention rate of methyl blue were 99.1 L/m2h, 12.5%, 7.9%, 97.7%, respectively. The results of pollution index and contact angle also proved that the membrane had anti-pollution performance.

Machine Learning-Based Evaluation of Shear Capacity of Recycled Aggregate Concrete Beams.

Recycled aggregate concrete (RAC) is a promising solution to address the challenges raised by concrete production. However, the current lack of pertinent design rules has led to a hesitance to accept structural members made with RAC. It would entail even more difficulties when facing application scenarios where brittle failure is possible (e.g., beam in shear). In this paper, existing major shear design formulae established primarily for conventional concrete beams were assessed for RAC beams. Results showed that when applied to the shear test database compiled for RAC beams, those formulae provided only inaccurate estimations with surprisingly large scatter. To cope with this bias, machine learning (ML) techniques deemed as potential alternative predictors were resorted to. First, a Grey Relational Analysis (GRA) was carried out to rank the importance of the parameters that would affect the shear capacity of RAC beams. Then, two contemporary ML approaches, namely, the artificial neural network (ANN) and the random forest (RF), were leveraged to simulate the beams' shear strength. It was found that both models produced even better predictions than the evaluated formulae. With this superiority, a parametric study was undertaken to observe the trends of how the parameters played roles in influencing the shear resistance of RAC beams. The findings indicated that, though less influential than the structural parameters such as shear span ratio, the effect of the replacement ratio of recycled aggregate (RA) was still significant. Nevertheless, the value of vc/(fc)1/2 (i.e., the shear contribution from RAC normalized with respect to the square root of its strength) predicted by the ML-based approaches appeared to be insignificantly affected by the replacement level. Given the existing inevitable large experimental scatter, more shear tests are certainly needed and, for safe application of RAC, using partial factors calibrated to consider the uncertainty is feasible when designing the shear strength of RAC beams. Some suggestions for future works are also given at the end of this paper.