PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design
PolyFusionAgent is a new multimodal foundation model designed to enhance polymer property prediction and inverse design. It integrates a polymer foundation model with an interactive design agent to improve the discovery process in polymer science. This framework aims to bridge the gap between AI models and experimental reality, facilitating actionable design decisions.
- ▪PolyFusionAgent combines a multimodal polymer foundation model with a tool-augmented design agent.
- ▪The framework improves thermophysical property prediction and enables the generation of novel polymers.
- ▪It links prediction and inverse design with evidence retrieval from existing polymer literature.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.26543 |
| Publication time | Wed, 27 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-27T04:07:56.398Z |
| Last seen | 2026-05-27T04:07:56.398Z |
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| Summary source text | contentText |
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| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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Computer Science > Artificial Intelligence arXiv:2605.26543 (cs) [Submitted on 26 May 2026] Title:PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design Authors:Manpreet Kaur, Xingying Zhang, Qian Liu View a PDF of the paper titled PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design, by Manpreet Kaur and 2 other authors View PDF HTML (experimental) Abstract:Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space and fragmented representations of structure, properties, and prior knowledge.
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