AIMC Topic: Membranes, Artificial
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Multimodal Wearable Sensing for Biomechanics and Biomolecules Enabled by the M-MPM/VCFs@Ag Interface with Machine Learning Pipeline.
ACS sensors
Jun 6, 2025
The addition sensing device of sweat to wearable biostress sensors would eliminate the need for using multiple gadgets for healthcare analysis. Due to the distinct package fashion of sensor interface for biostress and biomolecule, achieving permeabil...
Machine learning algorithms for predicting membrane bioreactors performance: A review.
Journal of environmental management
Mar 17, 2025
Membrane bioreactors (MBR) are recognized as a sustainable technology for treating polluted effluents. Machine learning (ML) algorithms have emerged as a modeling option to predict pollutant removal and operational variables such as membrane fouling,...
Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.
Scientific reports
Jan 28, 2025
Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility an...
Deep eutectic solvent-modified polyvinyl alcohol/chitosan thin film membrane for dye adsorption: Machine learning modeling, experimental, and density functional theory calculations.
International journal of biological macromolecules
Jan 3, 2025
The polyvinyl alcohol/chitosan (PVA/CS) thin film membrane was modified using a deep eutectic solvent (DES) to enhance its adsorption capability and mechanical strength for the removal of brilliant green (BG) dye. Batch adsorption experiments, machin...
Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation.
Environmental science & technology
Dec 16, 2024
Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility and high tunability. Traditional trial-and-error methods for material synthe...
How peptide migration and fraction bioactivity are modulated by applied electrical current conditions during electromembrane process separation: A comprehensive machine learning-based peptidomic approach.
Food research international (Ottawa, Ont.)
Nov 28, 2024
Industrial wastewaters are significant global concerns due to their environmental impact. Yet, protein-rich wastewaters can be valorized by enzymatic hydrolysis to release bioactive peptides. However, achieving selective molecular differentiation and...
Machine learning integration with response surface methodology to enhance the removal efficacy of arsenate (V) through sulfur-functionalized mxene coated QPPO/PVA AEM.
Journal of environmental management
Nov 7, 2024
Arsenic, a poisonous and carcinogenic heavy metal in drinking water, presents severe health risks to humans, including skin lesions, neurological damage, and circulatory disorders. Despite extensive research efforts have been carried out on removing ...
A machine learning based framework to tailor properties of nanofiltration and reverse osmosis membranes for targeted removal of organic micropollutants.
Water research
Oct 20, 2024
Nanofiltration (NF) and reverse osmosis (RO) membranes play an increasingly important role in the removal of organic micropollutants (OMPs), which puts higher demands on the customization of membranes suitable for OMPs removal based on the rejection ...
Ultralow-resistance and self-sterilization biodegradable nanofibrous membranes for efficient PM removal and machine learning-assisted health management.
Journal of hazardous materials
Sep 16, 2024
The development of multifunctional nanofibrous membranes (NFMs) that enable anti-viral protection during air purification and respiratory disease diagnosis for health management is of increasing importance. Herein, we unraveled a heterostructure-enha...
Machine learning models for predicting the rejection of organic pollutants by forward osmosis and reverse osmosis membranes and unveiling the rejection mechanisms.
Water research
Aug 30, 2024
While forward osmosis (FO) and reverse osmosis (RO) processes have been proven effective in rejecting organic pollutants, the rejection rate is highly dependent on compound and membrane characteristics, as well as operating conditions. This study aim...
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