Dongguan Key Laboratory of Artificial Intelligence Design for Advanced Materials
News
2025.02.14
Assistant Investigators
Chen Jifeng
2025.01.20
Chemistry
Cai You
2024.12.13
Postdocs
Keqin Wu
2024.12.13
Mathematics
Qingsheng Zhang
2024.10.30
Research Achievements
2024.10.15
Physics
Pak Hang Chris Lau
Introduction

Dongguan Key Laboratory of Artificial Intelligence Design for Advanced Materials was established in 2023 upon the approval of Dongguan Science and Technology Bureau. Based at GBU and in collaboration with Songshan Lake Materials Laboratory and Sun Yat-sen University, the Laboratory conducts scientific research, talent development, and industry-university-research cooperation. The primary focus of the Laboratory is on large-scale numerical calculations and AI-based design of advanced materials. Digging into core challenges in material numerical simulation and design of advanced quantum materials and catalytic materials, we are devoted to advancing the research and development of advanced materials through new computational tools and methodologies, and applying these research-derived methods to relevant industrial fields. The Laboratory’s specific research directions include:

1. Computational simulation of quantum materials: We conduct large-scale numerical calculations and integrate machine learning techniques to study advanced quantum materials such as quantum magnetic materials, quantum topological materials, and quantum correlated materials. These materials have the potential to revolutionize energy-related technologies and data storage and processing, generating substantial economic benefits. While relying on its own numerical calculations and theoretical mechanism studies, the Laboratory plans to collaborate with Songshan Lake Materials Laboratory, the spallation neutron source, and ultrafast physics platforms to advance quantum materials research in the GBA, especially in Dongguan.


2. Theoretical simulation of catalytic materials and catalyst design: Beyond traditional experiments and characterization, the development of modern catalysts increasingly relies on quantum chemical calculations and intelligent design. This theoretical simulation clarifies the essence of chemical reaction processes at the atomic and molecular levels, enabling rational catalyst design to reduce experimental trial-and-error costs and overall R&D costs significantly. The Laboratory explores and develops high-throughput rational design of catalysts for specific catalytic reactions, providing upstream R&D support to Dongguan’s catalytic production industry.


3. Machine learning-based materials computational simulation software development: Focused on the AI design of advanced materials, the Laboratory plans to gradually advance in related algorithms and computational technologies. We aim to develop computational platforms and technologies into simulation software for a broader customer base and establish simulation platforms for industrial use.

Currently, the Laboratory is carrying out the first-phase construction with a focus on quantum correlated materials and advanced catalyst design.