AIMC Topic: Oxidation-Reduction
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Quantitative determination of acid value in palm oil during thermal oxidation using Raman spectroscopy combined with deep learning models.
Food chemistry
May 15, 2025
Accurate monitoring of acid value (AV) is critical for edible oil quality control, yet traditional chemometric methods often face limitations in handling complex spectral data. This study combines Raman spectroscopy with deep learning, including Conv...
Machine Learning-Assisted Molecular Structure Embedding for Accurate Prediction of Emerging Contaminant Removal by Ozonation Oxidation.
Environmental science & technology
May 13, 2025
Ozone has demonstrated high efficacy in depredating emerging contaminants (ECs) during drinking water treatment. However, traditional quantitative structure-activation relationship (QSAR) models often fall short in effectively normalizing and charact...
Machine learning-assisted surface-enhanced raman spectroscopy for the rapid determination of the glutathione redox ratio.
The Analyst
May 12, 2025
Rapid and accurate detection of glutathione in its reduced (GSH) and oxidized (GSSG) forms is essential for monitoring oxidative stress in biological systems. Oxidative stress is a key indicator of various diseases, and glutathione plays a vital role...
CHCHD4 Oxidoreductase Activity: A Comprehensive Analysis of the Molecular, Functional, and Structural Properties of Its Redox-Regulated Substrates.
Molecules (Basel, Switzerland)
May 10, 2025
The human CHCHD4 protein, which is a prototypical family member, carries a coiled-coil-helix-coiled-coil-helix motif that is stabilized by two disulfide bonds. Using its CPC sequence motif, CHCHD4 plays a key role in mitochondrial metabolism, cell su...
Estimation of mesophyll conductance in Ginkgo biloba from the PSII redox state using a machine learning approach.
Tree physiology
Mar 28, 2025
Mesophyll conductance (gm) has been proved to be one of the important factors limiting photosynthesis and thus affects the estimation of plant productivity and terrestrial carbon balance. However, beyond the leaf scale, gm is usually assumed to be in...
Automated workflow for computation of redox potentials, acidity constants, and solvation free energies accelerated by machine learning.
The Journal of chemical physics
Jul 14, 2022
Fast evolution of modern society stimulates intense development of new materials with novel functionalities in energy and environmental applications. Due to rapid progress of computer science, computational design of materials with target properties ...
A graph-convolutional neural network for addressing small-scale reaction prediction.
Chemical communications (Cambridge, England)
Apr 27, 2021
We describe a graph-convolutional neural network (GCN) model, the reaction prediction capabilities of which are as potent as those of the transformer model based on sufficient data, and we adopt the Baeyer-Villiger oxidation reaction to explore their...
Micrometer-sized electrically programmable shape-memory actuators for low-power microrobotics.
Science robotics
Mar 17, 2021
Shape-memory actuators allow machines ranging from robots to medical implants to hold their form without continuous power, a feature especially advantageous for situations where these devices are untethered and power is limited. Although previous wor...
Kinetic study of dye removal using TiO supported on polyethylene terephthalate by advanced oxidation processes through neural networks.
Water science and technology : a journal of the International Association on Water Pollution Research
Mar 1, 2019
This work investigated the efficiency of polyethylene terephthalate (PET) as support material for TiO films in the photocatalytic degradation of red Bordeaux and yellow tartrazine dyes. The optimum operating conditions were determined by a factorial ...
Application of the advanced oxidative process on the degradation of the green leaf and purple açaí food dyes with kinetic monitoring and artificial neural network modelling.
Water science and technology : a journal of the International Association on Water Pollution Research
Oct 1, 2018
The study evaluated the advanced oxidative processes concerning the degradation of green leaf and purple açaí dyes, as well as the prediction of data through artificial neural networks (ANNs). It was verified that percentage of degradation on the wav...
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