AIMC Topic: Kinetics

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Investigating PCB degradation by indigenous fungal strains isolated from the transformer oil-contaminated site: degradation kinetics, Bayesian network, artificial neural networks, QSAR with DFT, molecular docking, and molecular dynamics simulation.

Environmental science and pollution research international
The widespread prevalence of polychlorinated biphenyls (PCBs) in the environment has raised major concerns due to the associated risks to human health, wildlife, and ecological systems. Here, we investigated the degradation kinetics, Bayesian network...

Synthesis and characterization of Fe(III)-doped beta-cyclodextrin-grafted chitosan cryogel beads for adsorption of diclofenac in aqueous solutions: Adsorption experiments and deep-learning modeling.

International journal of biological macromolecules
Diclofenac (DCF) is frequently detected in aquatic environments, emphasizing the critical need for its efficient removal globally. Here, we present the synthesis of Fe(III)-doped β-CD-grafted chitosan (Fe/β-CD@CS) cryogel beads designed for adsorbing...

Deep Learning-Based Kinetic Analysis in Paper-Based Analytical Cartridges Integrated with Field-Effect Transistors.

ACS nano
This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity cha...

Sustainable utilization of FeO-modified activated lignite for aqueous phosphate removal and ANN modeling.

Environmental research
Lignites are widely available and cost-effective in many countries. Sustainable methods for their utilization drive innovation, potentially advancing environmental sustainability and resource efficiency. In the present study, FeO (∼25.1 nm) supported...

Artificial neural networks (ANN)-genetic algorithm (GA) optimization on thermosonicated achocha juice: kinetic and thermodynamic perspectives of retained phytocompounds.

Preparative biochemistry & biotechnology
The extraction of phytocompounds from Achocha () vegetable juice using traditional methods often results in suboptimal yields and efficiency. This study aimed to enhance the extraction process through the application of thermosonication (TS). To achi...

Prediction of hydroxyl radical exposure during ozonation using different machine learning methods with ozone decay kinetic parameters.

Water research
The abatement of micropollutants by ozonation can be accurately calculated by measuring the exposures of molecular ozone (O) and hydroxyl radical (OH) (i.e., ∫[O]dt and ∫[OH]dt). In the actual ozonation process, ∫[O]dt values can be calculated by mon...

Prediction of micropollutant degradation kinetic constant by ultrasonic using machine learning.

Chemosphere
A prediction model based on XGBoost is proposed for ultrasonic degradation of micropollutants' kinetic constants. After parameter optimization through iteration, the model achieves Evaluation metrics with R and SMAPE reaching 0.99 and 2.06%, respecti...

The use of artificial neural network for modelling adsorption of Congo red onto activated hazelnut shell.

Environmental monitoring and assessment
Activated hazelnut shell (HSAC), an organic waste, was utilized for the adsorptive removal of Congo red (CR) dye from aqueous solutions, and a modelling study was conducted using artificial neural networks (ANNs). The structure and characteristic fun...

A parameter estimation method for chromatographic separation process based on physics-informed neural network.

Journal of chromatography. A
Chromatographic separation processes are most often modeled in the form of partial differential equations (PDEs) to describe the complex adsorption equilibria and kinetics. However, identifying parameters in such a model requires substantial computat...

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation.

Environment international
A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determinatio...