A chemical language model for reticular materials design

• URL: http://arxiv.org/abs/2603.20389v1
• Date: Fri, 20 Mar 2026 18:05:44 GMT
• Title: A chemical language model for reticular materials design
• Abstract summary: We introduce Nexerra-R1, a building-block chemical language model that enables inverse design in reticular chemistry.<n>Rather than generating complete frameworks directly, Nexerra-R1 operates at the level of molecular building blocks.<n>We propose the experimental synthesis of a previously unreported framework, CU-525, generated entirely in silico.
• Score: 5.537334577890515
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 blocks, preserving the modular logic that underpins reticular synthesis. The model supports both unconstrained generation of low-connectivity linkers and scaffold-constrained design of symmetric multidentate motifs compatible with predefined nodes and topologies. We further combine linker generation with flow-guided distributional targeting to steer the generative process toward application-relevant objectives while maintaining chemical validity and assembly feasibility. The generated linkers are subsequently assembled into three-dimensional frameworks and are structurally optimized to produce candidate materials compatible with experimental synthesis. Using Nexerra-R1, we validate this strategy by rediscovering known MOFs and by proposing the experimental synthesis of a previously unreported framework, CU-525, generated entirely in silico. Together, these results establish a general inverse-design paradigm for reticular materials in which controllable chemical language modelling enables the direct translation from computational design to synthesizable frameworks.

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