HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design
Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made significant advances in materials discovery, the hierarchical structure of polymers across multiple length scales makes them inherently difficult to represent in a unified and physically meaningful way. Here we introduce HiPoly, a polymer-native AI framework that processes complete polymer descriptions through a three-level hierarchical graph architecture built on the G2RINS representation. HiPoly encodes stochastic inter-monomer connectivity, composition, and molecular weight directly within its architecture, using physically motivated design pr...
| Authors | Ge Sun, Gervasio Zaldivar, Yuan Tian et al. |
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| Primary category | physics.chem-ph |
| Published | 2 September 2026 |
| Last updated at source | 2 September 2026 |
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