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The Journal of Physical Chemistry Letters|April 21, 2025
Fast-Track to Catalyst Stability: Machine Learning Optimized Predictions for M1/M2-N<sub>6</sub>-Gra CatalystsPengxin Pu, Xin Song, Hu Ding, et al.ACS Applied Materials & Interfaces|July 25, 2025
Transforming Catalysis with Machine Learning: Emerging Tools and Next-Gen StrategiesPengxin Pu, Haisong Feng, Xin Song, et al.The Journal of Physical Chemistry Letters|December 26, 2025
Ni-Based Alloy Catalysts for Liquid Organic Hydrogen Storage: Mechanistic Insights from First-Principles CalculationsShilong Zhang, Na Liu, Pengxin Pu, et al.The Journal of Physical Chemistry Letters|May 18, 2026
Theoretical Investigation into the Oxidation of 5-Hydroxymethylfurfural to 2,5-Diformylfuran over Metal-Nitrogen-Doped Carbon CatalystsSi Wang, Pengxin Pu, Tianyong Liu, et al.ACS Applied Materials & Interfaces|February 28, 2023
Active Learning Accelerating to Screen Dual-Metal-Site Catalysts for Electrochemical Carbon Dioxide Reduction ReactionHu Ding, Yawen Shi, Zeyang Li, et al.ACS Applied Materials & Interfaces|October 2, 2024
Integrating Active Learning and DFT for Fast-Tracking Single-Atom Alloy Catalysts in CO<sub>2</sub>-to-Fuel ConversionXin Song, Pengxin Pu, Haisong Feng, et al.ACS Applied Materials & Interfaces|November 23, 2023
Designing Efficient Single-Atom Alloy Catalysts for Selective C═O Hydrogenation: A First-Principles, Active Learning and Microkinetic StudyHaisong Feng, Meng Zhang, Zhen Ge, et al.Pageof 1