AIMC Topic: Catalysis
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Identification of cariogenic bacteria by click chemistry mediated polyethylene glycolized graphyne nanozymes.
Mikrochimica acta
Jul 28, 2025
Dental caries, one of the most common oral diseases, is mainly induced by multiple cariogenic bacteria in the oral microenvironment, so it is important to construct a method that can identify oral multiply cariogenic bacteria. Herein, a machine learn...
A neural network-shaped composite of α-MnO with N-doped graphene for electrocatalytic reduction of hydrogen peroxide in human urine samples.
The Analyst
Jul 21, 2025
A neural network-shaped composite fusing α-MnO and nitrogen-doped graphene (N@Gr/α-MnO) was synthesized a hydrothermal method. The resulting composite demonstrates enhanced electrocatalytic activity for hydrogen peroxide (HO) compared with each sing...
Dual-Channel Catalytic Immunochromatography Empowered by Machine Learning: Ultrasensitive Detection of O157:H7 via Magnetic CoFeO@HRP Nanocomposites.
Analytical chemistry
Jul 2, 2025
Traditional immunochromatographic test strips face significant limitations in detecting trace levels of O157:H7 due to insufficient sensitivity and reliability. To address this challenge, we developed a novel "three-In-One" nanoplatform based on mag...
Photocatalytic microrobots for treating bacterial infections deep within sinuses.
Science robotics
Jun 25, 2025
Microrobotic techniques are promising for treating biofilm infections located deep within the human body. However, the presence of highly viscous pus presents a formidable biological barrier, severely restricting targeted and minimally invasive treat...
Machine Learning Driven Synthesis of Cobalt Oxide Entrapped Heteroatom-Doped Graphitic Carbon Nitride for Enhanced Oxygen Evolution Reaction.
PloS one
Jun 11, 2025
Developing highly efficient electrocatalysts for the oxygen evolution reaction is hindered by sluggish multi-electron kinetics, poor charge transfer efficiency, and limited active site accessibility. Transition metal-based electrocatalysts, such as c...
Developing Pharmaceutically Relevant Pd-Catalyzed C-N Coupling Reactivity Models Leveraging High-Throughput Experimentation.
Journal of the American Chemical Society
May 29, 2025
This manuscript presents machine learning models for Pd-catalyzed C-N couplings constructed using a large, pharmaceutically relevant, structurally diverse dataset (4204 unique products) generated using high-throughput experimentation. The dataset ge...
In-situ conversion of hemicellulose to furfural by Lewis acid-enhanced deep eutectic solvents to maintain stable pretreatment performance and trigger profitable biorefining processes.
International journal of biological macromolecules
Apr 30, 2025
Deep eutectic solvents (DESs) are gaining attention for lignocellulose pretreatment, yet screening methods and stable cyclic processes remain underexplored. This study compared solubility and machine learning to predict delignification, screening the...
Artificial intelligence driven platform for rapid catalytic performance assessment of nanozymes.
Scientific reports
Apr 17, 2025
Traditional methods for synthesizing nanozymes are often time-consuming and complex, hindering efficiency. Artificial intelligence (AI) has the potential to simplify these processes, but there are very few dedicated nanozyme databases available, limi...
Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications.
Environmental science & technology
Mar 30, 2025
Covalent organic frameworks (COFs) are porous crystalline materials obtained by linking organic ligands covalently. Their high surface area and adjustable pore sizes make them ideal for a range of applications, including CO capture, CH storage, gas s...
Machine learning-based activity prediction of phenoxy-imine catalysts and its structure-activity relationship study.
Molecular diversity
Mar 7, 2025
This study systematically investigates the structure-activity relationships of 30 Ti-phenoxy-imine (FI-Ti) catalysts using machine learning (ML) approaches. Among the tested algorithms, XGBoost demonstrated superior predictive performance, achieving ...
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