AIMC Topic: Catalysis

Clear Filters Showing 61 to 70 of 109 articles

Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 1, 2022
At present, alloys have broad application prospects in heterogeneous catalysis, due to their various catalytic active sites produced by their vast element combinations and complex geometric structures. However, it is the diverse variables of alloys t...
Machine Learning Catalysis Alloys
View on PubMed DOI

Enzyme-Photocatalyst Tandem Microrobot Powered by Urea for Escherichia coli Biofilm Eradication.

Small (Weinheim an der Bergstrasse, Germany) Feb 5, 2022
Urinary-based infections affect millions of people worldwide. Such bacterial infections are mainly caused by Escherichia coli (E. coli) biofilm formation in the bladder and/or urinary catheters. Herein, the authors present a hybrid enzyme/photocataly...
Titanium Urease Robotics Catalysis Humans Biofilms Escherichia coli Urea
View on PubMed DOI

Pd/silicalite-1: An highly active catalyst for the oxidative removal of toluene.

Journal of environmental sciences (China) Dec 29, 2021
Catalytic combustion is thought as an efficient and economic pathway to remove volatile organic compounds, and its critical issue is the development of high-performance catalytic materials. In this work, we used the in situ synthesis method to prepar...
Catalysis Oxidative Stress Oxidation-Reduction Toluene Oxides
View on PubMed DOI

Tungsten oxide polymorphs and their multifunctional applications.

Advances in colloid and interface science Dec 29, 2021
Owing to the natural abundance, easy availability, high stability, non-stoichiometry, and chemical diversity, considerable interest has been devoted to tungsten oxide (WO) nanomaterials, and many advances have been achieved ranging from traditional c...
Catalysis Tungsten Artificial Intelligence Oxides
View on PubMed DOI

Machine learning based analysis of reaction phenomena in catalytic lignin depolymerization.

Bioresource technology Dec 7, 2021
Heterogeneously catalyzed lignin solvolysis opens the possibility of transforming low value biomass into high value, useful aromatic chemicals, however, its reaction behavior is poorly understood due to the many possible interactions between reaction...
Lignin Biomass Catalysis Machine Learning
View on PubMed DOI

Atomic Structure-Free Representation of Active Motifs for Expedited Catalyst Discovery.

Journal of chemical information and modeling Aug 23, 2021
To discover new catalysts using density functional theory (DFT) calculations, binding energies of reaction intermediates are considered as descriptors to predict catalytic activities. Recently, machine learning methods have been developed to reduce t...
Catalysis Binding Sites Machine Learning
View on PubMed DOI

Machine learning differentiates enzymatic and non-enzymatic metals in proteins.

Nature communications Jun 17, 2021
Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate b...
Static Electricity Binding Sites Enzymes Metalloproteins Catalysis Catalytic Domain Models, Molecular Machine Learning Metals Algorithms Databases, Protein
View on PubMed DOI

Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion.

Faraday discussions Jan 14, 2021
A central ambition of the robotics field has been to increasingly miniaturize such systems, with perhaps the ultimate achievement being the synthetic microbe or cell sized machine. To this end, we have introduced and demonstrated prototypes of what w...
Humans Hydrogen Peroxide Graphite Robotics Locomotion Catalysis
View on PubMed DOI

Self-assembled Janus plasmene nanosheets as flexible 2D photocatalysts.

Materials horizons Nov 16, 2020
A leaf is a free-standing photocatalytic system that can effectively harvest solar energy and convert CO and HO into carbohydrates in a continuous manner without the need for regeneration or tedious product extraction steps. Despite encouraging advan...
Hydrophobic and Hydrophilic Interactions Solar Energy Nanostructures Nanoparticles Catalysis
View on PubMed DOI

Cautionary Guidelines for Machine Learning Studies with Combinatorial Datasets.

ACS combinatorial science Oct 1, 2020
Regression modeling is becoming increasingly prevalent in organic chemistry as a tool for reaction outcome prediction and mechanistic interrogation. Frequently, to acquire the requisite amount of data for such studies, researchers employ combinatoria...
Catalysis Stereoisomerism Quantitative Structure-Activity Relationship Machine Learning Sulfhydryl Compounds Combinatorial Chemistry Techniques Models, Chemical Imines Databases, Factual
View on PubMed DOI
Popular Topics
Recent Journals