Jun Jiang
Affiliations: | Department of Chemical Physics | University of Science and Technology of China, Hefei Shi, Anhui Sheng, China |
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Sign in to add trainee| Xijun Wang | grad student | 2012-2018 | University of Science & Technology of China |
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| Jia C, Li B, Yang J, et al. (2025) Prediction of CN-Supported Double-Atom Catalysts with Individual/Integrated Descriptors for Electrochemical and Thermochemical CO Reduction. Journal of the American Chemical Society |
| Wang Y, Wang Q, Wang X, et al. (2025) Accelerated Design of Dual-Metal-Site Catalysts via Machine-Learning Prediction. The Journal of Physical Chemistry Letters. 1424-1431 |
| Yang L, Zhao Z, Yang T, et al. (2024) Monitoring C-C coupling in catalytic reactions via machine-learned infrared spectroscopy. National Science Review. 12: nwae389 |
| Cui CX, Shen Y, He JR, et al. (2024) Quantitative Insight into the Electric Field Effect on CO Electrocatalysis via Machine Learning Spectroscopy. Journal of the American Chemical Society. 146: 34551-34559 |
| Sun K, Huang Y, Sun F, et al. (2024) Dynamic structural twist in metal-organic frameworks enhances solar overall water splitting. Nature Chemistry |
| Zhang Y, Wang D, Wei G, et al. (2024) Engineering Spin Polarization of the Surface-Adsorbed Fe Atom by Intercalating a Transition Metal Atom into the MoS Bilayer for Enhanced Nitrogen Reduction. Jacs Au. 4: 1509-1520 |
| Jiang S, Wang X, Chong Y, et al. (2024) Spectra-Based Machine Learning for Predicting the Statistical Interaction Properties of CO Adsorbates on Surface. The Journal of Physical Chemistry Letters. 2400-2404 |
| Ye K, Wang S, Huang Y, et al. (2024) Machine Learning Prediction of Molecular Binding Profiles on Metal-Porphyrin via Spectroscopic Descriptors. The Journal of Physical Chemistry Letters. 1956-1961 |
| Eshete M, Li X, Yang L, et al. (2023) Charge Steering in Heterojunction Photocatalysis: General Principles, Design, Construction, and Challenges. Small Science. 3: 2200041 |
| Guo S, Jiang J, Ren H, et al. (2023) Fusion of Multiple Spectra for Investigating Chemical Bonding Properties via Machine Learning. The Journal of Physical Chemistry Letters. 14: 7461-7468 |