Physics-based AI model for predicting polymer–surfactant complexation
A physics-based AI model that integrates molecular dynamics (MD) simulations with AI algorithms to predict polymer–surfactant complexation. The approach supports high-throughput screening prior to laboratory testing and aims to improve understanding of molecular mechanisms to inform formulation strategies. MD outputs such as viscosity and complexation energy are used to build predictive models, with initial experimental validation and planned follow-on validation over six months.
Overview
This solution offers a physics-based AI model designed to predict the complexation of polymers and surfactants. By integrating molecular dynamics (MD) simulations with AI algorithms, the model enables high-throughput screening of polymer–surfactant interactions before laboratory experiments. This approach is intended to reduce time and resource use while improving mechanistic understanding of molecular interactions, supporting better formulation strategies.
Technical specifications
Key features:
- Combines MD simulations with AI to enhance predictive accuracy
- Uses the Generalized Amber Force Field (GAFF) for all-atom MD simulations
- Employs GROMACS 2021 for executing simulations
- Develops AI models based on MD outputs such as viscosity and complexation energy
- Validated using experimental data to ensure reliability
Technology readiness level
This technology is currently at TRL 3, indicating an experimental proof-of-concept stage. Further validation with experimental data is planned over a six-month period to advance development.
About University of Macau
UM is a comprehensive research-oriented public university in Macao with more than 16,800 students and an international character. Its Hengqin campus, operating under Macao SAR jurisdiction, links Macao, Zhuhai, and the Guangdong–Hong Kong–Macao Greater Bay Area. Industry engagement is supported by three state key laboratories, more than 30 joint laboratories, and the Zhuhai UM Science & Technology Research Institute, a platform for industry–education–research collaboration and technology transfer. Research draws on Macao SAR funding and national support from China’s Ministry of Science and Technology and the National Natural Science Foundation of China. Knowledge-transfer, entrepreneurship, and commercialisation units support IP management, incubation, licensing, and consulting.
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