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Adsorption

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Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Postcombustion CO Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models.

Environmental science & technology
Postcombustion CO capture and storage (CCS) is a key technological approach to reducing greenhouse gas emission while we transition to carbon-free energy production. However, current solvent-based CO capture processes are considered too energetically...

Modeling and optimization by particle swarm embedded neural network for adsorption of methylene blue by jicama peroxidase immobilized on buckypaper/polyvinyl alcohol membrane.

Environmental research
Jicama peroxidase (JP) immobilized functionalized Buckypaper/Polyvinyl alcohol (BP/PVA) membrane was synthesized and evaluated as a promising nanobiocomposite membrane for methylene blue (MB) dye removal from aqueous solution. The effects of independ...

Single and competitive dye adsorption onto chitosan-based hybrid hydrogels using artificial neural network modeling.

Journal of colloid and interface science
Chitosan-based hybrid hydrogels such as chitosan hydrogel (CH), chitosan hydrogel with activated carbon (CH-AC), scaffold-chitosan hydrogel (SCH), scaffold-chitosan hydrogel with activated carbon (SCH-AC) and scaffold-chitosan hydrogel with carbon na...

Artificial Neural Network Approach for Modelling of Mercury Ions Removal from Water Using Functionalized CNTs with Deep Eutectic Solvent.

International journal of molecular sciences
Multi-walled carbon nanotubes (CNTs) functionalized with a deep eutectic solvent (DES) were utilized to remove mercury ions from water. An artificial neural network (ANN) technique was used for modelling the functionalized CNTs adsorption capacity. T...

Cloisite Microrobots as Self-Propelling Cleaners for Fast and Efficient Removal of Improvised Organophosphate Nerve Agents.

ACS applied materials & interfaces
Naturally available microclays are well-known materials with great adsorption capabilities that are available in nature in megatons quantities. On the contrary, artificial nanostructures are often available at high cost via precision manufacturing. S...

Supervised Learning and Mass Spectrometry Predicts the Fate of Nanomaterials.

ACS nano
The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. He...

The application of machine learning methods for prediction of metal sorption onto biochars.

Journal of hazardous materials
The adsorption of six heavy metals (lead, cadmium, nickel, arsenic, copper, and zinc) on 44 biochars were modeled using artificial neural network (ANN) and random forest (RF) based on 353 dataset of adsorption experiments from literatures. The regres...

A highly effective, recyclable, and novel host-guest nanocomposite for Triclosan removal: A comprehensive modeling and optimization-based adsorption study.

Journal of colloid and interface science
In this research paper, response surface methodology (RSM), generalized regression neural network (GRNN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) were employed to develop prediction models for Triclosan (TCS) removal by a novel inclusion co...

Machine Learning Prediction of H Adsorption Energies on Ag Alloys.

Journal of chemical information and modeling
Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. High-throughput adsorption energy predictions can therefore help accelerate first-principles catalyst design. To this end, ...

Determining gradient conditions for peptide purification in RPLC with machine-learning-based retention time predictions.

Journal of chromatography. A
A strategy for determining a suitable solvent gradient in silico in preparative peptide separations is presented. The strategy utilizes a machine-learning-based method, called ELUDE, for peptide retention time predictions based on the amino acid sequ...