AIMC Topic: Adsorption
Clear Filters Showing 1 to 10 of 162 articles
High-Throughput Analysis of Protein Adsorption to a Large Library of Polymers Using Liquid Extraction Surface Analysis-Tandem Mass Spectrometry (LESA-MS/MS).
Analytical chemistry
Jun 10, 2025
Biomaterials play an important role in medicine from contact lenses to joint replacements. High-throughput screening coupled with machine learning has identified synthetic polymers that prevent bacterial biofilm formation, prevent fungal cell attachm...
Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning.
Nanoscale
May 2, 2025
The adsorption of biomolecules on the surface of nanomaterials (NMs) is a critical determinant of their behavior, toxicity, and efficacy in biological systems. Experimental testing of these phenomena is often costly or complicated. Computational appr...
Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis.
Bioresource technology
Apr 20, 2025
Alum sludge (AlS) has emerged as an effective adsorbent for anionic contaminants, with traditional activation methods like acid/base treatments and calcination employed to enhance its adsorption capacity. However, these approaches encounter significa...
Modeling PFAS Sorption in Soils Using Machine Learning.
Environmental science & technology
Apr 11, 2025
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...
Biohybrid microrobots with a Spirulina skeleton and MOF skin for efficient organic pollutant adsorption.
Nanoscale
Mar 24, 2025
Wastewater treatment is a key component in maintaining environmental health and sustainable urban life, and the rapid development of micro/nanotechnology has opened up new avenues for more efficient treatment processes. This work developed a novel bi...
Machine Learning for Quantitative Prediction of Protein Adsorption on Well-Defined Polymer Brush Surfaces with Diverse Chemical Properties.
Langmuir : the ACS journal of surfaces and colloids
Mar 12, 2025
Polymer informatics has attracted increasing attention because machine learning can establish quantitative structure-property relationships in polymer materials. Understanding and controlling protein adsorption on polymer surfaces are crucial for var...
Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.
Scientific reports
Mar 12, 2025
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...
Comparative immobilization of 30 PFAS mixtures onto biochar, clay, nanoparticle, and polymer derived engineered adsorbents: Machine learning insights into carbon chain length and removal mechanism.
Journal of hazardous materials
Feb 25, 2025
Per- and polyfluoroalkyl substances (PFAS) are a group of fluorinated chemicals that cause potential risk in PFAS-impacted soil and water. The adsorption efficiency of 30 PFAS mixtures using different adsorbents in environmentally relevant concentrat...
Integrated learning framework for enhanced specific surface area, pore size, and pore volume prediction of biochar.
Bioresource technology
Feb 21, 2025
Specific surface area, pore size, and pore volume are essential biochar properties. Optimization typically reduces yield by focusing on per gram of biochar. This work introduces new indicators and an integrated model to balance quality and quantity, ...
Selective gas adsorption using graphitic carbon nitride: Exploring the role of molecular descriptors by artificial intelligence frameworks.
Journal of environmental management
Feb 10, 2025
Artificial Intelligence (AI) frameworks estimate the adsorption energies of crucial pollutants like CO, O, NO, NO, SOF, HCHO, and CO on Graphitic Carbon Nitride (g-CN) surfaces. The predictive capabilities of two AI-based models, namely, Artificial N...
Don't Miss the Future of Medicine
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 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- 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 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823