Workshop Announcement

The AI-Accelerated Dynamic Catalysis and Free Energy Calculation Workshop will be held on April 12, 2025, at the Siming Campus of Xiamen University!

In catalysis research, advances in experimental and theoretical simulation techniques have increasingly revealed that catalyst structures undergo dynamic evolution under in-situ reaction conditions, as demonstrated by numerous in-situ spectroscopic, microscopic, and computational studies. Traditional first-principles calculations based on single, static structural models are no longer sufficient to address the growing complexity of catalytic science. Structural search across potential energy surfaces or molecular dynamics (MD) simulations of heterogeneous catalytic systems have become essential tools for uncovering dynamic catalyst structures and reaction mechanisms.

To address these challenges, this workshop brings together leading experts to present recent advances in theoretical and computational approaches for dynamic catalysis. Topics will span catalytic reaction mechanisms, machine learning (ML)-accelerated methods, and practical applications of workflow software. By integrating cutting-edge ML techniques and automation tools with theoretical catalysis research, the workshop aims to demonstrate powerful new capabilities for tackling complex, dynamic catalytic processes.

Notably, ML-based interatomic potentials have dramatically accelerated molecular dynamics simulations. However, a key challenge lies in constructing high-quality training datasets. For catalytic reactions, comprehensive datasets must cover the complex conformational space—including all possible reactive configurations—posing significant time and computational costs. To address this bottleneck, the AI4EC Lab launched ai²-cat, an in-house developed intelligent computational workflow for dynamic catalysis, in April 2024. Starting from initial structures, ai²-cat automates an active learning loop involving sampling, first-principles calculation labeling, and potential function training, enabling rapid construction of highly accurate potential functions and facilitating efficient in-situ dynamic simulations of complex catalytic systems.

This workshop will also include a hands-on session on the ai²-cat dynamic catalysis workflow, allowing participants to gain practical experience and deepen their understanding of both the theoretical content and software tools, thereby supporting cutting-edge research.

Event Details  

Date: April 12, 2025 (Saturday)

Venue: Siming Campus, Xiamen University

Address: No. 422 Siming South Road, Siming District, Xiamen

Agenda

Section 1: Academic Talks (Morning, April 12)

1.Suilei Hu ：

Professor and PhD Supervisor, University of Science and Technology of China (USTC). Recipient of the National Young Top-Notch Talent Program, Anhui Provincial Outstanding Young Fund, Tang Aoqing Award for Young Theoretical Chemists (Chinese Chemical Society), and the Mozi Outstanding Young Talent Fellowship (USTC). Has led projects supported by the Youth Innovation Promotion Association of the Chinese Academy of Sciences, USTC’s Key Youth Innovation Fund, and the National Natural Science Foundation of China. His research focuses on developing physics-informed artificial intelligence methods combined with neural network potential-based simulations to uncover universal scaling laws and evolutionary principles across systems—from electrons to atoms to composite materials. He aims to establish multiscale mathematical models to guide the rational design, synthesis, and performance optimization of advanced catalytic materials. Notably, he discovered a volcano-type relationship between interfacial strain and the activity of single-atom electrocatalysts for oxygen evolution in fuel cells, revealed scaling laws governing nanoparticle catalyst sintering and deactivation, and established a new theory for designing ultra-stable nanocatalysts driven by physics-informed machine learning. This provides a theoretical foundation for screening long-life, high-temperature-resistant energy catalysts. He has published multiple papers in Science, Nat. Catal., Nat. Commun., J. Phys. Chem. C, ChemCatChem, and other journals.

2.Manyi Yang：Impact of Catalyst Surface Dynamics on Ammonia Decomposition

Tenure-track Associate Professor at Nanjing University, Jiangsu Provincial Distinguished Professor, PhD Supervisor, and recipient of national youth talent programs. Graduated with a B.Sc. from the School of Chemistry and Chemical Engineering at Central South University in 2013. Earned his Ph.D. (direct Ph.D. program) under Professor Shuhua Li at Nanjing University. After completing his Ph.D. in 2019, he joined the research group of Prof. Michele Parrinello, conducting postdoctoral research at ETH Zurich (July 2019 – December 2020) and the Italian Institute of Technology (January 2021 – February 2024). His expertise lies in automated reaction pathway search methods, enhanced sampling molecular dynamics simulations, and mechanistic studies of complex rare events such as chemical reactions, phase transitions, and industrial catalysis. He has published in Nat. Catal., Phys. Rev. Lett., Chem. Sci., J. Chem. Theory Comput., ACS Catal., and other journals. His current research focuses on: (1) developing automated reaction pathway search methods and their applications in mechanistic studies and reaction design; and (2) developing machine learning-assisted enhanced sampling MD methods for applications in phase transitions and industrial catalysis.

3.Menglei Jia：Practicing Machine Learning-Accelerated Molecular Dynamics in Dynamic Catalysis Research

Postdoctoral Researcher at Tan Kah Kee Innovation Laboratory.

Received her B.Sc. in Chemical Engineering from East China University of Science and Technology in 2018, and completed her Ph.D. in Chemistry and Molecular Engineering at the same institution in 2023 under the supervision of Professors Peijun Hu and Haifeng Wang. Joined Professor Jun Cheng’s group at the College of Chemistry and Chemical Engineering, Xiamen University, and the IKKEM AI4EC Lab in August 2023. Her research focuses on microkinetic analysis of catalytic reaction networks and intelligent design of nanocatalysts. She has published in ACS Nano, ACS Catal., J. Chem. Phys., and other journals.。

4.Yueyuan Cui： Dynamic Coordination of Ni on BOx Promotes Propane Oxidative Dehydrogenation

Ph.D. candidate at the College of Chemistry and Chemical Engineering, Xiamen University. Completed her undergraduate studies at the School of Physical Science and Technology, Inner Mongolia University, under the supervision of Professor Gang Fu. Her research interests include self-assembly of boron-based materials, design of 3D topological materials, selective C–H bond activation using boron-based catalysts, and machine learning-accelerated screening and design of battery materials.

Section 2: Hands-on Practice (Afternoon, April 12)

1. Chengxuan Wang：Active Learning Applications of ai²-kit in Catalytic Reaction Processes

Ph.D. candidate at the College of Chemistry and Chemical Engineering, Xiamen University. B.Sc. from Xiamen University, supervised by Professor Jun Cheng. His current research focuses on the dynamic behavior in metal cluster catalysis, construction of general-purpose potential functions for dynamic catalysis, and free energy calculation methods.

2. Yun Yang：Applications of ai²-kit in Proton-Coupled Electron Transfer at Electrochemical Interfaces

Ph.D. candidate at the College of Chemistry and Chemical Engineering, Xiamen University. B.Sc. from Yunnan University, supervised by Professor Gang Fu. His research focuses on using machine learning-based potential functions to study nonadiabatic free energy surfaces in electron transfer and proton-coupled electron transfer processes at metal/aqueous solution interfaces.

Registration

• Interested students and faculty are invited to register by scanning the QR code below before April 3, 2025.

• Participation is limited to 30 attendees. Registration is confirmed upon receiving a notification from the organizing committee.
• Prospective participants are encouraged to scan the QR code to join the workshop WeChat group, where presentation slides and post-event materials will be shared.

• No registration fee. Lunch will be provided on April 12. Travel and accommodation expenses are at participants’ own cost.

Contact

Email：ai4ec@xmu.edu.cn