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Membrane-based separation processes has been recently of significant global interest compared to other conventional separation approaches due to possessing undeniable advantages like superior performance, environmentally-benign nature and simplicity of application. Computational simulation of fluids has shown its undeniable role in modeling and simulation of numerous physical/chemical phenomena including chemical engineering, chemical reaction, aerodynamics, drug delivery and plasma physics. Definition of fluids can be occurred using the Navier-Stokes equations, but solving the equations remains an important challenge. In membrane-based separation processes, true perception of fluid's manner through disparate membrane modules is an important concern, which has been significantly limited applying numerical/computational procedures such s computational fluid dynamics (CFD). Despite this noteworthy advantage, the optimization of membrane processes using CFD is time-consuming and expensive. Therefore, combination of artificial intelligence (AI) and CFD can result in the creation of a promising hybrid model to accurately predict the model results and appropriately optimize membrane processes and phase separation. This paper aims to provide a comprehensive overview about the advantages of commonly-employed ML-based techniques in combination with the CFD to intelligently increase the optimization accuracy and predict mass transfer and the unfavorable events (i.e., fouling) in various membrane processes. To reach this objective, four principal strategies of AI including SL, USL, SSL and ANN were explained and their advantages/disadvantages were discussed. Then after, prevalent ML-based algorithm for membrane-based separation processes. Finally, the application potential of AI techniques in different membrane processes (i.e., fouling control, desalination and wastewater treatment) were presented.
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http://dx.doi.org/10.1016/j.ecoenv.2023.115066 | DOI Listing |
J Phys Chem B
September 2025
School of Science, RMIT University, Melbourne 3000, Australia.
Pentameric ligand-gated ion channels control synaptic neurotransmission via an allosteric mechanism, whereby agonist binding induces global protein conformational changes that open an ion-conducting pore. For the proton-activated bacterial () ligand-gated ion channel (GLIC), high-resolution structures are available in multiple conformational states. We used a library of atomistic molecular dynamics (MD) simulations to study conformational changes and to perform dynamic network analysis to elucidate the communication pathways underlying the gating process.
View Article and Find Full Text PDFJ Intensive Care Med
September 2025
Division of Critical Care Medicine, Department of Medicine, The Queen's Medical Center, Honolulu, HI, USA.
PurposeTo summarize the currently available evidence regarding the effectiveness and safety of extracorporeal membrane oxygenation (ECMO) cannulation performed by intensivists.MethodsWe conducted a systematic search of MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials for studies of any design in which patients underwent ECMO cannulation by intensivists. The search was updated on Dec 15, 2024.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
School of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, 333 Long Teng Road, Shanghai 201620, P.R. China.
Silicon carbide (SiC) membranes combine exceptional chemical, thermal, and mechanical stability but suffer from surface inertness that precludes functionalization. Conversely, MOFs offer unmatched molecular selectivity but are typically powders, severely limiting their practical use. To address this, we develop a generalizable route to fabricate ultrastable MOF@SiC membranes via sequential oxidation and acidification, creating abundant Si-OH sites on SiC surfaces that covalently bond with Zr-MOF crystals; the bonding mechanism between MOFs and substrates has been extensively studied.
View Article and Find Full Text PDFNano Lett
September 2025
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan 430070, China.
Constructing heterogeneous dual-site catalysts is anticipated for oxygen evolution reaction (OER). However, compared to the adsorbate evolution mechanism (AEM), the triggering oxide pathway mechanism (OPM) for catalysts poses challenges due to elusive structural evolution and low intrinsic activity. Herein, considering the distinct adsorption propensity of heterogeneous Ni-Fe sites toward differential intermediates (OH-O), the PO-induced deep reconstruction triggers a dual-site Ni-Fe discrepant oxide pathway mechanism (DOPM) for R-PO-NiCoFeOOH.
View Article and Find Full Text PDFFront Mol Neurosci
August 2025
Department of Cardiovascular Sciences, Lewis Katz School of Medicine, Lemole Center for Integrated Lymphatics and Vascular Research, Temple University, Philadelphia, PA, United States.
Introduction: Endothelial-to-mesenchymal transition (EndoMT), cell death, and fibrosis are increasingly recognized as contributing factors to Alzheimer's disease (AD) pathology, but the underlying transcriptomic mechanisms remain poorly defined. This study aims to elucidate transcriptomic changes associated with EndoMT, diverse cell death pathways, and fibrosis in AD using the 3xTg-AD mouse model.
Methods: Using RNA-seq data and knowledge-based transcriptomic analysis on brain tissues from the 3xTg-AD mouse model of AD.