Research graph
References from A method for optimizing catalyst preparation conditions based on machine learning and genetic algorithm. Local targets link to admitted publications; unresolved targets remain external evidence.
Recent advances in VOC elimination by catalytic oxidation technology onto various nanoparticles catalysts: a critical review
10.1016/j.apcatb.2020.119447 · 2021 · External reference
Recent advances in catalyst technology for volatile organic compound (VOC) removal
2016 · External reference
Non-noble metal catalysts for catalytic oxidation of volatile organic compounds: a review
2022 · External reference
Double redox process to synthesize CuO-CeO₂ catalysts with strong Cu-Ce interaction for efficient toluene oxidation
10.1016/j.jhazmat.2020.124088 · 2021 · External reference
Evaluation of a data-driven machine learning approach for identifying potential candidates for environmental catalysts: from database development to prediction
10.1021/acsestengg.1c00125 · 2021 · External reference
Prediction of catalytic activity of Cu-Ce/γ-al₂o₃ catalysts by artificial neural networks
2012 · External reference
A unified approach to interpreting model predictions
2017 · External reference
Surface reconstruction of Pt nanoparticles for enhanced CO oxidation: a combined experimental and DFT study
10.1021/cs5018369 · 2015 · External reference
Theoretical optimization of bed packing arrangement in cascade Dual-Catalyst system with side reactions
10.1016/j.ces.2024.120500 · 2024 · External reference
Predicting adsorption ability of adsorbents at arbitrary sites for pollutants using deep transfer learning
2020 · External reference
Big-data science in porous materials: materials genomics and machine learning
10.1021/acs.chemrev.0c00004 · 2020 · External reference
Machine Learning for catalytic reaction systems: a framework for complex chemical processes
10.1021/acsengineeringau.5c00093 · 2026 · External reference
Random forests
10.1023/a:1010933404324 · 2001 · External reference
Machine learning-assisted design of porous materials for VOC adsorption
2019 · External reference
Comparison of random forest and traditional classical method in regression and classification problems
2023 · External reference
Machine learning-driven optimal design of iron-based catalysts and the catalytic oxidation characteristics for ammonia
2025 · External reference
Unresolved reference
2021 · External reference
Development of NOx reduction system utilizing artificial neural network and genetic algorithm
10.1016/j.jclepro.2019.05.276 · 2019 · External reference
Catalytic oxidation of toluene by ozone over alumina supported manganese oxides: effect of catalyst
10.1016/j.apcatb.2013.01.061 · 2013 · External reference
Effect of calcination temperature on the activity and structure of MnOx/γ-Al2O3 catalysts for formaldehyde oxidation
10.1016/j.jcat.2017.08.030 · 2017 · External reference
Recent advances in catalytic ozonation for water treatment
2020 · External reference
Effect of calcination temperature on the performance of SiO2@Co@CeO2 catalyst in CO2 reforming with ethanol
10.1007/s10562-023-04282-6 · 2023 · External reference
Structure-activity relationship model of volatile organic compounds pollution control catalysts based on machine learning
2026 · External reference
Unresolved reference
2014 · External reference
Unresolved reference
2021 · External reference
From local explanations to global understanding with explainable AI for trees
10.1038/s42256-019-0138-9 · 2020 · External reference
Machine-learning-assisted materials discovery using failed experiments
10.1038/nature17439 · 2016 · External reference
Effect of calcination temperature on the performance of SiO2@Co@CeO2 catalyst in CO2 reforming with ethanol
10.1007/s10562-023-04282-6 · ExternalCitation · doi-reference
Catalytic oxidation of toluene by ozone over alumina supported manganese oxides: effect of catalyst
10.1016/j.apcatb.2013.01.061 · ExternalCitation · doi-reference
Recent advances in VOC elimination by catalytic oxidation technology onto various nanoparticles catalysts: a critical review
10.1016/j.apcatb.2020.119447 · ExternalCitation · doi-reference
Theoretical optimization of bed packing arrangement in cascade Dual-Catalyst system with side reactions
10.1016/j.ces.2024.120500 · ExternalCitation · doi-reference
Effect of calcination temperature on the activity and structure of MnOx/γ-Al2O3 catalysts for formaldehyde oxidation
10.1016/j.jcat.2017.08.030 · ExternalCitation · doi-reference
Development of NOx reduction system utilizing artificial neural network and genetic algorithm
10.1016/j.jclepro.2019.05.276 · ExternalCitation · doi-reference
Double redox process to synthesize CuO-CeO₂ catalysts with strong Cu-Ce interaction for efficient toluene oxidation
10.1016/j.jhazmat.2020.124088 · ExternalCitation · doi-reference
Big-data science in porous materials: materials genomics and machine learning
10.1021/acs.chemrev.0c00004 · ExternalCitation · doi-reference
Machine Learning for catalytic reaction systems: a framework for complex chemical processes
10.1021/acsengineeringau.5c00093 · ExternalCitation · doi-reference
Evaluation of a data-driven machine learning approach for identifying potential candidates for environmental catalysts: from database development to prediction
10.1021/acsestengg.1c00125 · ExternalCitation · doi-reference
Surface reconstruction of Pt nanoparticles for enhanced CO oxidation: a combined experimental and DFT study
10.1021/cs5018369 · ExternalCitation · doi-reference
Random forests
10.1023/a:1010933404324 · ExternalCitation · doi-reference
Machine-learning-assisted materials discovery using failed experiments
10.1038/nature17439 · ExternalCitation · doi-reference
From local explanations to global understanding with explainable AI for trees
10.1038/s42256-019-0138-9 · ExternalCitation · doi-reference
