Runjie Bao

Hefei University of Technology — China

Chemical Engineering · Physical Sciences

8h-index134citations17works8.42yr avg
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Research Topics

Catalysis and Oxidation Reactions(6), Machine Learning in Materials Science(5), Catalytic Processes in Materials Science(4), Catalysts for Methane Reforming(4), Process Optimization and Integration(4)

Publications17 total

Machine learning-guided optimization of iron-based catalysts toward minimal-resource and efficient peroxymonosulfate activation for hazardous organic pollutants degradation
Journal of Hazardous Materials·2025· 1 cited
Bio-Digital Catalyst Design: Generative Deep Learning for Multi-Objective Optimization and Chemical Insights in CO<sub>2</sub> Methanation
ACS Catalysis·2025· 5 cited
Ensemble learning-driven multi-objective optimization of the co-pyrolysis process of biomass and coal for high economic and environmental performance
Chinese Journal of Chemical Engineering·2025· 2 cited
Naphthaleneimide functionalized NU-1000 as an efficient donor-acceptor photo-catalyst for the visible-light-driven oxidation of benzylamine coupling
Microporous and Mesoporous Materials·2025· 3 cited
Linker engineering of ternary donor–acceptor photosensitizers in chem-stable metal–organic frameworks for efficient photo-catalytic aerobic oxidation
Chemical Engineering Journal·2025· 7 cited
Unlocking prediction and optimal design of CO2 methanation catalysts via active learning-enhanced interpretable ensemble learning
Chemical Engineering Journal·2025· 17 cited
An auto-configurable and interpretable ensemble learning framework for optimal catalyst design of green methanol production via Bayesian optimization
Journal of Cleaner Production·2025· 9 cited
Linker Engineering of Ternary Donor-Acceptor Photosensitizers in Chem-Stable Metal-Organic Frameworks for Efficient Photo-Catalytic Aerobic Oxidation
SSRN Electronic Journal·2025Open Access
An automatic recognition of target product and multiparameter collaborative regulation-based machine learning framework for dimethyl oxalate hydrogenation catalysts optimization and prediction
Chemical Engineering Science·2024· 3 cited
Interpretable machine learning-assisted advanced exergy optimization for carbon-neutral olefins production
Renewable and Sustainable Energy Reviews·2024· 9 cited
Machine learning-based techno-econo-environmental analysis of CO2-to-olefins process for screening the optimal catalyst and hydrogen color
Energy·2024· 10 cited
An interpretable machine learning-based optimization framework for the optimal design of carbon dioxide to methane process
Energy Conversion and Management·2024· 16 cited
Interpretable Machine Learning for Accelerating Reverse Design and Optimizing CO<sub>2</sub> Methanation Catalysts with High Activity at Low Temperatures
Industrial & Engineering Chemistry Research·2024· 16 cited
Optimization and prediction of catalysts for precise synthesis of methyl glycolate from dimethyl oxalate using machine learning coupled with particle swarm optimization algorithm
Chemical Engineering Science·2024· 19 cited
Nanostructured CoMoO4 Supported on Mesoporous SBA-15 for Catalytic Oxidative Dehydrogenation of Propane to Propene
Acta Physico-Chimica Sinica·2008· 3 cited
Hydrothermal Synthesis and Thermal Stability of Natural Mineral Lindgrenite1
Chemical Research in Chinese Universities·2006· 14 cited
Hydrothermal synthesis and thermal stability of natural mineral lindgrenite Note: atomic coordinates transformed to standard setting
2006

Frequent Co-authors

Qingchun Yang(11), Dongwen Rong(8), Zhao Wang(6), Qiwen Guo(6), Zhou Jianlong(5), Dawei Zhang(3), Mingxue Shao(3), Huadong Guo(3), Chunyu Liu(3), Xianmin Guo(3), Lei Zhao(2), Dawei Zhang(2), Zu‐Ping Kong(2), Bin Yue(2), Yao Cen(2), Yutong Song(2), Lei Zhao(1), Yukai Pan(1), Xin Zhou(1), Fu Zhang(1)