AIMC Topic: Adsorption
Clear Filters Showing 21 to 30 of 167 articles
Application of supervised learning models for enhanced lead (II) removal from wastewater via modified cellulose nanocrystals (CNCs).
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jan 16, 2025
Heavy metal ions are acknowledged to impact the environment and human health adversely. CNCs are effective materials for removing heavy metal ions in industrial applications and process innovations since they can be used in static and dynamic adsorpt...
Artificial neural networks to estimate the sorption and desorption of the herbicide linuron in Brazilian soils.
Environmental pollution (Barking, Essex : 1987)
Jan 15, 2025
Generally, herbicides used in Brazil follow manufacturer's recommendations, which often do not consider soil attributes. Statistical models that include the physicochemical properties of the soil involved in herbicide retention processes could enable...
Accelerated Screening of Highly Sensitive Gas Sensor Materials for Greenhouse Gases Based on DFT and Machine Learning Methods.
ACS sensors
Jan 6, 2025
Greenhouse gases (GHGs) have caused great harm to the ecological environment, so it is necessary to screen gas sensor materials for detecting GHGs. In this study, we propose an ideal gas sensor design strategy with high screening efficiency and low c...
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...
Efficient and stable extraction of nano-sized plastic particles enabled by bio-inspired magnetic "robots" in water.
Environmental pollution (Barking, Essex : 1987)
Dec 31, 2024
In this research, a rationally-designed strategy was employed to address the crucial issue of removing nano-plastics (NPs) from aquatic environments, which was based on fabricating sea urchin-like structures of FeO magnetic robots (MagRobots). Throug...
MGT: Machine Learning Accelerates Performance Prediction of Alloy Catalytic Materials.
Journal of chemical information and modeling
Dec 19, 2024
The application of deep learning technology in the field of materials science provides a new method for predicting the adsorption energy of high-performance alloy catalysts in hydrogen evolution reactions and material discovery. The activity and sele...
Predicting the adsorption of ammonia nitrogen by biochar in water bodies using machine learning strategies: Model optimization and analysis of key characteristic variables.
Environmental research
Dec 14, 2024
Biochar adsorption technology has been widely used to remove ammonia nitrogen from water bodies. However, existing methods for predicting adsorption efficiency often lack sufficient accuracy and practical usability. This study evaluated eight machine...
Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning.
Bioresource technology
Nov 28, 2024
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...
Design and synthesis of a new recyclable nanohydrogel based on chitosan for Deltamethrin removal from aqueous solutions: Optimization and modeling by RSM-ANN.
International journal of biological macromolecules
Nov 27, 2024
In this study, a new magnetic biocompatible hydrogel was synthesized as an adsorbent for Deltamethrin pesticide removal. The optimal conditions and adsorption process of Deltamethrin by chitosan/polyacrylic acid/FeO nanocomposite hydrogel was studied...
Cd adsorption prediction of Fe mono/composite modified biochar based on machine learning: Application for controllable preparation.
Environmental research
Nov 26, 2024
In this study, artificial neural network (ANN) and random forest (RF) were constructed to predict the Cd adsorption capacity of Fe-modified biochar. The RF model outperformed ANN model in accuracy and predictive performance (R = 0.98). Through the co...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31964
- Neural Networks, Computer 30201
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24818
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4328
- Brain 4125
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853