AIMC Topic: Adsorption

Clear Filters Showing 91 to 100 of 167 articles

Combined Deep Learning and Classical Potential Approach for Modeling Diffusion in UiO-66.

Journal of chemical theory and computation Jun 2, 2022
Modeling of diffusion of adsorbates through porous materials with atomistic molecular dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be included. This is because potentials need to be developed that accurately ac...
Deep Learning Diffusion Phthalic Acids Adsorption Metal-Organic Frameworks
View on PubMed DOI

Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements.

Nature communications May 30, 2022
Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be particularly effective in conducting atomistic simulations for such pur...
Adsorption Neural Networks, Computer Catalysis Metal-Organic Frameworks
View on PubMed DOI

Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar.

Chemosphere May 23, 2022
Environmental distresses linked to heavy metal (HM) impurity in the water received significant attention among research communities. Recently, advancements in industrial sectors like paper industries, mining, non-ferrous metallurgy, electroplating, m...
Metals, Heavy Adsorption Charcoal Wastewater Deep Learning Water Pollutants, Chemical
View on PubMed DOI

Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes.

Journal of chromatography. A Apr 9, 2022
The design and optimization of chromatographic processes is essential for enabling efficient separations. To this end, hyperbolic partial differential equations (PDEs) along with nonlinear adsorption isotherms must be solved using computationally exp...
Neural Networks, Computer Adsorption Chromatography Computers Computer Simulation Physics
View on PubMed DOI

Prediction of nanoscale thermal transport and adsorption of liquid containing surfactant at solid-liquid interface via deep learning.

Journal of colloid and interface science Jan 12, 2022
HYPOTHESIS: Recent advances in deep learning (DL) have enabled high level of real-time prediction of thermophysical properties of materials. On the other hand, molecular dynamics (MD) have been long used as a numerical microscope to observe detailed ...
Pulmonary Surfactants Adsorption Surface-Active Agents Neural Networks, Computer Deep Learning
View on PubMed DOI

A novel artificial intelligent model for predicting water treatment efficiency of various biochar systems based on artificial neural network and queuing search algorithm.

Chemosphere Sep 20, 2021
This study aims at providing a robust artificial intelligent model for predicting the efficiency of heavy metal removal from aqueous solutions of biochar systems with high accuracy and reliability. Not only is it environmentally significant, but it i...
Adsorption Charcoal Water Purification Humans Reproducibility of Results Neural Networks, Computer Algorithms
View on PubMed DOI

Artificial intelligence (AI) applications in adsorption of heavy metals using modified biochar.

The Science of the total environment Aug 18, 2021
The process of removal of heavy metals is important due to their toxic effects on living organisms and undesirable anthropogenic effects. Conventional methods possess many irreconcilable disadvantages pertaining to cost and efficiency. As a result, t...
Charcoal Metals, Heavy Artificial Intelligence Adsorption
View on PubMed DOI

Intelligent modeling and experimental study on methylene blue adsorption by sodium alginate-kaolin beads.

International journal of biological macromolecules Jul 5, 2021
As tighter regulations on color in discharges to water bodies are more widely implemented worldwide, the demand for reliable inexpensive technologies for dye removal grows. In this study, the removal of the basic dye, methylene blue, by adsorption on...
Powders Chemical Fractionation Surface Properties Alginates Regression Analysis Kinetics Adsorption Methylene Blue Kaolin Neural Networks, Computer Water Pollutants, Chemical
View on PubMed DOI

Hybrid Models for the simulation and prediction of chromatographic processes for protein capture.

Journal of chromatography. A May 13, 2021
The biopharmaceutical industries are continuously faced with the pressure to reduce the development costs and accelerate development time scales. The traditional approach of heuristic-based or platform process-based optimization is soon getting obsol...
Proteins Kinetics Computer Simulation Neural Networks, Computer Adsorption Chromatography Chemistry Techniques, Analytical
View on PubMed DOI

On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.

BioMed research international Apr 26, 2021
Biosurfactants are a series of organic compounds that are composed of two parts, hydrophobic and hydrophilic, and since they have properties such as less toxicity and biodegradation, they are widely used in the food industry. Important applications i...
Surface-Active Agents Adsorption Polystyrenes Models, Chemical Glycolipids Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals