AIMC Topic: Kinetics
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Integrating Chemical Mechanisms and Feature Engineering in Machine Learning Models: A Novel Approach to Analyzing HONO Budget.
Environmental science & technology
Dec 5, 2024
Nitrous acid (HONO) serves as the primary source of OH radicals in the atmosphere, exerting significant impacts on atmospheric secondary pollution. The heterogeneous reactions of NO on surfaces and photolysis of particulate nitrate or adsorbed nitric...
High-throughput Kinetics using capillary Electrophoresis and Robotics (HiKER) platform used to study T7, T3, and Sp6 RNA polymerase misincorporation.
PloS one
Dec 2, 2024
T7 RNA Polymerase (RNAP) is a widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as key analysis tools for probing the nucleotide addition mechanisms of T7 RNAP a...
Design and synthesis of a new recyclable nanohydrogel based on chitosan for Deltamethrin removal from aqueous solutions: Optimization and modeling by RSM-ANN.
International journal of biological macromolecules
Nov 27, 2024
In this study, a new magnetic biocompatible hydrogel was synthesized as an adsorbent for Deltamethrin pesticide removal. The optimal conditions and adsorption process of Deltamethrin by chitosan/polyacrylic acid/FeO nanocomposite hydrogel was studied...
A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems.
Scientific reports
Nov 22, 2024
The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing embryos has paved the way for deep-learning based computer vision algorithms to assist embryologists in their morphokinetic evaluation. Today, most of the l...
Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning.
Nature communications
Nov 6, 2024
mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried ou...
Biosorption of cobalt and chromium from wastewater using manganese dioxide and iron oxide nanoparticles loaded on cellulose-based biochar: Modeling and optimization with machine learning (artificial neural network).
International journal of biological macromolecules
Oct 28, 2024
In this study, two nanomaterials with excellent adsorption capacities were developed to remove heavy metals efficiently from wastewater. Manganese dioxide MnO nanoparticles and iron oxide FeO nanoparticles were successfully synthesized using cassava ...
Uncertainty Qualification for Deep Learning-Based Elementary Reaction Property Prediction.
Journal of chemical information and modeling
Oct 23, 2024
The prediction of the thermodynamic and kinetic properties of elementary reactions has shown rapid improvement due to the implementation of deep learning (DL) methods. While various studies have reported the success in predicting reaction properties,...
A machine learning-guided modeling approach to the kinetics of α-tocopherol and myricetin synergism in bulk oil oxidation.
Food chemistry
Sep 27, 2024
The shelf-life and quality of food products depend heavily on antioxidants, which protect lipids from free radical degradation. α-Tocopherol and myricetin, two potent antioxidants, synergistically enhance the prevention of oxidative rancidity in bulk...
Effective Removal of Selenium from Aqueous Solution using Iron-modified Dolochar: A Comprehensive Study and Machine Learning Predictive Analysis.
Environmental research
Sep 16, 2024
Selenium (Se) is an essential micronutrient for human beings, but excess concentration can lead to many health issues and degrade the ecosystem. This study focuses on the removal of selenium from an aqueous solution using iron-doped dolochar. SEM, ED...
Linear symmetric self-selecting 14-bit kinetic molecular memristors.
Nature
Sep 11, 2024
Artificial Intelligence (AI) is the domain of large resource-intensive data centres that limit access to a small community of developers. Neuromorphic hardware promises greatly improved space and energy efficiency for AI but is presently only capable...
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