AIMC Topic: Adsorption

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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
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
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 ...

Addressing data handling shortcomings in machine learning studies on biochar for heavy metal remediation.

Journal of hazardous materials
Recent advancements in machine learning (ML) technologies have significantly enhanced their applications in environmental sciences, particularly in the domains of soil and water remediation. This paper reviews recent studies that employ ML to optimiz...

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
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
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
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...

Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Journal of hazardous materials
Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Research on this topic has been limited to specific types of MPs and ATs, resulting in inconsistent findings, particularly for the influencing factors an...

Developing a machine learning-based predictive model for cesium sorption distribution coefficient on crushed granite.

Journal of environmental radioactivity
The sorption of radionuclides on granite has been extensively studied over the past few decades due to its significance in the safety assessment of geological disposal for high-level radioactive waste (HLW). The sorption properties of granite for rad...

Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.

Environmental monitoring and assessment
Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on...

ANN-assisted comprehensive screening of silica gel-alunite composite sorbent system for efficient adsorption of toxic nickel ions: Batch and continuous mode water treatment applications.

Chemosphere
Through batch and fixed-bed column operations, nickel ions were extracted from a contaminated aqueous media by adsorption onto silica gel-immobilized alunite (Sg@Aln). A three-layer backward-propagating network with an ideal pattern of 5-10-1 and 4-1...