About AI4Hydrogel
Learn more about our hydrogel research toolkit and knowledge hub
Our Mission
AI4Hydrogel is a digital toolkit and knowledge hub for hydrogel research. Our mission is to help researchers develop next-generation hydrogels for energy storage, biomedical devices, and smart materials by combining curated literature data, predictive models, and interactive knowledge exploration.
Platform Features
- Curated hydrogel and polymer electrolyte property data from the literature
- Searchable datasets for glass transition temperature and ionic conductivity
- Predictive tools for property estimation and materials screening
- Interactive molecular visualization and structure inspection tools
- Knowledge graph resources for exploring hydrogel structure-property relationships
- Reproducible data organization for benchmarking, meta-analysis, and model development
AI4Hydrogel Consortium
AI4Hydrogel is developed by a multi-institutional research team spanning hydrogel materials, artificial intelligence, knowledge engineering, and statistical modeling. The platform is designed to make our curated datasets, predictive models, and knowledge graph resources easier for the community to inspect, reuse, and extend.
Tsinghua University
Hydrogel science and application context
Shanghai Jiao Tong University
Platform leadership and research guidance
Tongji University
Statistics, data analysis, benchmarking, and model evaluation
Beijing University of Posts and Telecommunications
Materials modeling and polymer electrolyte research
Contributors
- Advisor: Professor Menghao Yang — Project guidance.
- Data & Website: Jiezhou — Data curation, website development, and partial algorithm implementation.
- Algorithm Design: Wenzhu Bi and Tianyu Huang — Algorithm design and development.
This work was completed under the guidance of Professor Menghao Yang.
How to Cite
If you use AI4Hydrogel data, tools, or knowledge graph resources in your research, please cite the platform:
AI4Hydrogel: Artificial Intelligence for Hydrogel. A digital toolkit and knowledge hub for next-generation hydrogel research. Available at: https://ai4hydrogel.comContact Us
For questions, suggestions, or data contributions, please contact us at:
Email: menghaoyang@sjtu.edu.cn