Sign inGet started
Paper · arXiv

A chemical language model for reticular materials design

Reticular chemistry has enabled the synthesis of tens of thousands of metal-organic frameworks (MOFs), yet the discovery of new materials still relies largely on intuition-driven linker design and iterative experimentation. As a result, researchers explore only a small fraction of the vast chemical space accessible to reticular materials, limiting the systematic discovery of frameworks with targeted properties. Here, we introduce Nexerra-R1, a building-block chemical language model that enables inverse design in reticular chemistry through the targeted generation of organic linkers. Rather than generating complete frameworks directly, Nexerra-R1 operates at the level of molecular building...

AuthorsDhruv Menon, Vivek Singh, Xu Chen et al.
Primary categorycond-mat.mtrl-sci
Published20 March 2026
Last updated at source20 March 2026
cond-mat.mtrl-scics.LGphysics.chem-ph
Embed this entry
<iframe src="https://silytics.si/embed/item/d28bd8ad-7462-4c66-8611-2075f0f221b7" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.