Superior AI Modeling of Large Atomic Systems
Overview
A deep-learning scheme based on atomic graph attention networks for fast, highly accurate modeling of long-term molecular dynamics in large multi-atomic systems, to aid in drug, material and battery design.
Research completion
2023
Commercialisation opportunities
Technology licensing agreement
Problem addressed
The interatomic potentials in MD are usually obtained by fitting to the physical and chemical properties from limited experimental or theoretical data. Consequently, the accuracy of interatomic potential in predicting energy and force is rather limited. An accurate interatomic potential thus can greatly improve the efficiency of large-scale simulations, guiding for searching new materials and designing new functionalities of current materials.
Innovation
- The AGAT model is trained to represent the energy and atomic forces from accurate DFT simulations, and then the well-trained model is deployed to simulate larger systems with a much longer duration at the DFT accuracy.
- Compared to conventional machine-learning interatomic potentials, the current AGAT model provides an end-to-end solution for accurate and efficient training and predicting the energy, force, and stress of large atomic systems.
- N/A
Key impact
- AGAT shows a high accuracy.
- AGAT is extendable.
- AGAT provides an end-to-end solution to obtain energies and forces of any given systems.
Award
- 48th International Exhibition of Inventions Geneva (IEIG) - Silver Medal
Application
- Large-scale molecular simulations
- Efficient electrocatalyst design
- Accurate prediction of mechanical properties
- Optimization of crystal structural models efficiently
Patent
- Patent number: 202211432380.7 (CN) IDF 1249
City University of Hong Kong (CityU)
As one of the fastest growing universities in the world over the past decade, City University of Hong Kong (CityU) is recognised as a hub for innovation in research and professional education. CityU identifies solutions to critical global challenges by extending the frontiers of knowledge both within and beyond existing research paradigms.
The University’s highly qualified academics are drawn from all over the world, not only bringing a wealth of research and professional experience to the teaching programmes, but also contributing to the knowledge and technology advancement.
Enquiry
