HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design
Paper recorded by Signals 4 on 2026-09-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-02 on arXiv · recorded by Signals 4 on 2026-09-03
Category: cs.AI · 人工智能 · first seen 2026-09-03
Abstract
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 framew
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Cite this page: HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design: the #214 most recent of 300 cs.AI papers we have recorded (as of 2026-09-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/hipoly-a-hierarchical-polymer-native-ai-framework-for-property-prediction-and-ge.html
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