AIMC Topic: Oxidation-Reduction

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Au nanozyme-based colorimetric sensor array integrates machine learning to identify and discriminate monosaccharides.

Journal of colloid and interface science
As different monosaccharides exhibit different redox characteristics, this paper presented a novel colorimetric sensor array based on the glucose oxidase-like (GOx-like) activity of Au nanoparticles (NPs) for monosaccharides identification. AuNPs can...

Artificial neural network modeling for the oxidation kinetics of divalent manganese ions during chlorination and the role of arsenite ions in the binary/ternary systems.

Water research
This study investigated the coexistence and contamination of manganese (Mn(II)) and arsenite (As(III)) in groundwater and examined their oxidation behavior under different equilibrating parameters, including varying pH, bicarbonate (HCO) concentratio...

Machine learning-aided evaluation of oxidative strength of cold atmospheric plasma-treated water.

Biomedical physics & engineering express
Plasma medicine is gaining attraction in the medical field, particularly the use of cold atmospheric plasma (CAP) in biomedicine. The chemistry of the plasma is complex, and the reactive oxygen species (ROS) within it are the basis for the biological...

Biomimetic piezoelectric nanomaterial-modified oral microrobots for targeted catalytic and immunotherapy of colorectal cancer.

Science advances
Lactic acid (LA) accumulation in the tumor microenvironment poses notable challenges to effective tumor immunotherapy. Here, an intelligent tumor treatment microrobot based on the unique physiological structure and metabolic characteristics of (VA) ...

Unveiling the potential of machine learning in cost-effective degradation of pharmaceutically active compounds: A stirred photo-reactor study.

Chemosphere
In this study, neural networks and support vector regression (SVR) were employed to predict the degradation over three pharmaceutically active compounds (PhACs): Ibuprofen (IBP), diclofenac (DCF), and caffeine (CAF) within a stirred reactor featuring...

Machine-Learning-Assisted Descriptors Identification for Indoor Formaldehyde Oxidation Catalysts.

Environmental science & technology
The development of highly efficient catalysts for formaldehyde (HCHO) oxidation is of significant interest for the improvement of indoor air quality. Up to 400 works relating to the catalytic oxidation of HCHO have been published to date; however, th...

Machine Learning-Based Prediction of Reduction Potentials for Pt Complexes.

Journal of chemical information and modeling
Some of the well-known drawbacks of clinically approved Pt complexes can be overcome using six-coordinate Pt complexes as inert prodrugs, which release the corresponding four-coordinate active Pt species upon reduction by cellular reducing agents. Th...

Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.

Water research
Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR ...

Comparison of hybrid RNA-based models to predict the degradation and mineralization of the microcontaminant hormone 17β-estradiol.

Chemosphere
New alternatives for effluent decontamination, such as electrochemical oxidation, are being developed to provide adequate removal of endocrine disruptors such as 17β-estradiol in wastewater. In this study, data-driven models of response surface metho...

Optimization of catalytic wet air oxidation process in microchannel reactor for TBBS wastewater treatment.

Environmental technology
Catalytic wet air oxidation (CWAO) process is employed for the treatment of N-tert-butyl-2-benzothiazolesulfenamide (TBBS) wastewater in a microchannel reactor that enables continuous operation of the reaction and allows for thorough mixing of oxygen...