A machine learning approach for prediction of reverse solute flux in forward osmosis
This study introduces a novel approach using a supervised machine learning model to
accurately predict reverse solute flux (RSF) in the forward osmosis process. This study …
accurately predict reverse solute flux (RSF) in the forward osmosis process. This study …
Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation
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 …
industrial applications over the past few decades because of their exceptional versatility and …
Modeling sulfamethoxazole removal by pump-less in-series forward osmosis–ultrafiltration hybrid processes using artificial neural network, adaptive neuro-fuzzy …
This study presented an in-series forward osmosis–ultrafiltration (FO–UF) hybrid system for
sulfamethoxazole (SMX) removal. Artificial neural network (ANN), adaptive neuro-fuzzy …
sulfamethoxazole (SMX) removal. Artificial neural network (ANN), adaptive neuro-fuzzy …
Universal model for predicting maximum spreading of drop impact on a smooth surface developed using boosting machine learning models
J Tang, S Yu, X Hou, T Wu, H Liu - Industrial & Engineering …, 2023 - ACS Publications
Drop impact on a solid surface is a fundamental phenomenon in nature and engineering.
Prediction of the maximum spreading ratio during drop impact is critical for modeling and …
Prediction of the maximum spreading ratio during drop impact is critical for modeling and …
Predicting and optimizing forward osmosis membrane operation using machine learning
Forward osmosis (FO) utilizes a draw solution to transport water across a semipermeable
membrane, offering energy-efficient water treatment and resource recovery. This study …
membrane, offering energy-efficient water treatment and resource recovery. This study …
Accurate prediction of reverse solute flux in forward osmosis systems using comparative machine learning models
Forward osmosis (FO) is a promising technology that can help to recover freshwater from
saline and wastewater streams. However, it faces challenges such as reverse solute flux …
saline and wastewater streams. However, it faces challenges such as reverse solute flux …
[HTML][HTML] Artificial Intelligence Applications in Forward Osmosis for Water Treatment: Recent Developments and Research Directions
SO Alaswad, E Almatrafi - Desalination and Water Treatment, 2024 - Elsevier
Forward osmosis (FO) studies for water treatment until recently have been dominated by
conventional empirical and mathematical modeling approaches. Artificial intelligence (AI) …
conventional empirical and mathematical modeling approaches. Artificial intelligence (AI) …
Molecular simulations and deep neural networks‐based interpretable machine learning modelling of reverse adsorptive MOFs for ethane/ethylene separation
The thermal decomposition of ethane (C2H6) and the steam cracking of fossil fuels are the
main sources of ethylene (C2H4). However, it usually contains 5%–9% of C2H6 residue …
main sources of ethylene (C2H4). However, it usually contains 5%–9% of C2H6 residue …
From comparison to integration: Enhancing forward osmosis performance prediction with mathematical and RBF neural network models
Reliable prediction of forward osmosis (FO) performance requires advanced models that
can handle the complex, nonlinear interactions within operational conditions. This study …
can handle the complex, nonlinear interactions within operational conditions. This study …
Explainable AI for permeate flux prediction in forward osmosis: SHAP interpretability and theoretical validation for enhanced predictive reliability
This study presents an integrated machine learning (ML) and explainable artificial
intelligence (XAI) framework for predicting permeate flux in forward osmosis (FO) …
intelligence (XAI) framework for predicting permeate flux in forward osmosis (FO) …