PolyNC
AI Models Apache-2.0 (Free)
About
A unified natural & chemical language model (text-to-text) for predicting polymer properties (multi-task: regression + classification).
Citation
Qiu, H.; Liu, L.; Qiu, X.; Dai, X.; Ji, X.; Sun, Z.-Y. PolyNC: a natural and chemical language model for unified polymer properties prediction. Chemical Science (2024). DOI:10.1039/D3SC05079C
Frequently Asked Questions
What is PolyNC?
PolyNC is a ai models application available in the Paramus App Store. A unified natural & chemical language model (text-to-text) for predicting polymer properties (multi-task: regression + classification).
Is PolyNC free to use?
Yes. PolyNC is distributed under the Apache-2.0 (Free) license and is available at no cost through the Paramus App Store.
How do I install PolyNC?
PolyNC is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select PolyNC for one-click deployment.
What type of application is PolyNC?
PolyNC belongs to the “AI Models” category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.
What platform does PolyNC run on?
PolyNC runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.
Can PolyNC be automated or integrated with AI workflows?
Yes. PolyNC is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.
How should I cite PolyNC in publications?
The recommended citation for PolyNC is: Qiu, H.; Liu, L.; Qiu, X.; Dai, X.; Ji, X.; Sun, Z.-Y. PolyNC: a natural and chemical language model for unified polymer properties prediction. Chemical Science (2024). DOI:10.1039/D3SC05079C