Design and fabrication of whisker hybrid ceramic membranes with narrow pore size distribution and high permeability via co-sintering process

Ceramic microfiltration membranes (MF) with narrow pore size distribution and high permeability are widely used for the preparation of ceramic ultrafiltration membranes (UF) and in wastewater treatment. In this work, a whisker hybrid ceramic membrane (WHCM) consisting of a whisker layer and an alumina layer was designed to achieve high permeability and narrow pore size distribution based on the relative resistance obtained using the Hagen-Poiseuille and Darcy equations. The whisker layer was designed to prevent the penetration of alumina particles into the support and ensure a high porosity of the membrane, while the alumina layer provided a smooth surface and narrow pore size distribution. Mass transfer resistance is critical to reduce the effect of the membrane layers. It was found that the resistance of the WHCM depended largely on the alumina layer. The effect of the support and whisker layer on the resistance of the WHCM was negligible. This was consistent with theoretical calculations. The WHCM was co-sintered at 1000 °C, which resulted in a high permeability of ~ 645 L m−1 h−1 ;bar−1 and a narrow pore size distribution of ~ 100 nm. Co-sintering was carried out on a macroporous ceramic support (just needed one sintering process), which greatly reduced the preparation cost and time. The WHCM (as the sub-layer) also showed a great potential to be used for the fabrication of ceramic UF membranes with high repeatability. Hence, this study provides an efficient approach for the fabrication of advanced ceramic MF membranes on macroporous supports, allowing for rapid prototyping with scale-up capability

LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST

Subcellular location of a protein is one of the key functional characters as proteins must be localized correctly at the subcellular level to have normal biological function. In this paper, a novel method named LOCSVMPSI has been introduced, which is based on the support vector machine (SVM) and the position-specific scoring matrix generated from profiles of PSI-BLAST. With a jackknife test on the RH2427 data set, LOCSVMPSI achieved a high overall prediction accuracy of 90.2%, which is higher than the prediction results by SubLoc and ESLpred on this data set. In addition, prediction performance of LOCSVMPSI was evaluated with 5-fold cross validation test on the PK7579 data set and the prediction results were consistently better than the previous method based on several SVMs using composition of both amino acids and amino acid pairs. Further test on the SWISSPROT new-unique data set showed that LOCSVMPSI also performed better than some widely used prediction methods, such as PSORTII, TargetP and LOCnet. All these results indicate that LOCSVMPSI is a powerful tool for the prediction of eukaryotic protein subcellular localization. An online web server (current version is 1.3) based on this method has been developed and is freely available to both academic and commercial users, which can be accessed by at

Learning-Based Client Selection for Federated Learning Services Over Wireless Networks with Constrained Monetary Budgets

We investigate a data quality-aware dynamic client selection problem for multiple federated learning (FL) services in a wireless network, where each client offers dynamic datasets for the simultaneous training of multiple FL services, and each FL service demander has to pay for the clients under constrained monetary budgets. The problem is formalized as a non-cooperative Markov game over the training rounds. A multi-agent hybrid deep reinforcement learning-based algorithm is proposed to optimize the joint client selection and payment actions, while avoiding action conflicts. Simulation results indicate that our proposed algorithm can significantly improve training performance.Comment: 6 pages,8 figure

Facile co-sintering process to fabricate sustainable antifouling silver nanoparticles (AgNPs)-enhanced tight ceramic ultrafiltration membranes for protein separation

Protein separation in chemical industry applications using tight ceramic ultrafiltration (UF) membranes with multilayer asymmetric structures is hindered by challenges in their fabrication and fouling phenomenon. In this study, a facile co-sintering method for fabrication of silver nanoparticles (AgNPs)-enhanced tight ceramic ultrafiltration membranes was comprehensively investigated. The introduction of AgNPs into the membrane layer not only controlled the membrane surface charge properties, but also alleviated the sintering stress in the co-sintering process, ensuring a complete membrane layer owing to the higher ductility. The AgNPs obtained from silver nitrate were introduced before the formation of boehmite nucleation, providing a uniform distribution of AgNPs within boehmite owing to the electric double layer. The final UF membranes prepared by the co-sintering process exhibited a molecular weight cut-off of 9000 Da and permeance of 62 Lm−2h−1bar−1. Furthermore, the isoelectric point of the membrane surface could be controlled by the AgNPs (from 9.0 to 2.7), providing sustainable antifouling properties for protein purification owing to the electrostatic repulsion force. The AgNPs-enhanced ceramic membrane material also exhibits a higher stability without silver leakage due to the thermal treatment at 1000 °C. The proposed facile co-sintering process for fabrication of antifouling ceramic UF membranes with the assistance of AgNPs could decrease the sintering time and energy consumption, and thus is promising for industrial protein separation applications

Ultrasound Assisted Synthesis of Size-Controlled Aqueous Colloids for the Fabrication of Nanoporous Zirconia Membrane

Permeation and separation efficiency of ceramic membranes are strongly dependent on their nanoporous structures, especially on the pore size. In this work, ultrasound is employed to form the size-controlled ZrO2 nanoparticles, and a ceramic membrane is prepared with tunable pore size. Under the ultrasound treatment, H+ from water plays a key role in the synthesis process. The cavitation caused by ultrasound promotes the hydrolysis of the precursor in water, which produces a large number of H+. These H+ will react with precipitant added and generate cyclic tetrameric units. Excess H+ can peptize cyclic tetrameric units and form an electrical double layer, resulting in a stable sol. Unlike ultrasound treatment, precipitant will react directly with the precursor and generate precipitation if there is no ultrasound added. Moreover, cavitation is good for the dispersion of cyclic tetrameric units. The particle size of Zr-based colloidal sol can be tuned in the ranges of 1.5 to 120 nm by altering the molar ratio of precursor to precipitant, ultrasonic power density and radiation time. Meanwhile, ultrasonic power density and radiation time have effects on grain size and the crystalline transition temperature of particles which influence performance of the ceramic membrane. As a result, membranes exhibit high performance together with high permeability and desirable rejection. To develop such a simple and controllable method for tuning particle size is extremely important in the preparation of nanoporous ceramic membranes