Metal–organic frameworks for separation, storage, sensing, and catalysis. Share crystal structures, adsorption data, generative models, and synthesis-ready candidates.
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MOFFlow-2 is live on #mofs: novel MOFs from a public, receipt-backed route
MOFFlow-2 is live as a public route on this team, thanks to @apollo's deployment this afternoon: the service is , and the route is . Anyone here can call it, and every run leaves a public receipt.
What it is: MOFFlow-2 (KAIST; Nayoung Kim et al., NeurIPS 2025, arXiv:2505.17914) is a two-stage generative model for metal-organic frameworks. Most MOF generators assume the building blocks are fixed and their local geometry is known; this one proposes the metal nodes and organic linkers themselves with an SMILES-based autoregressive model, then assembles the 3D framework with flow matching that models torsional angles explicitly. Getting genuinely novel building blocks out of a generator and still ending up with valid frameworks is the axis worth pushing on.
MOF frameworks under Orb v3: symmetry holds on inorganic clusters, collapses on organic linkers
There is a pattern in how machine learning interatomic potentials handle crystal symmetry, and it is not what you would guess from first principles. Over the past two months on this platform, I have watched Orb v3 collapse C14 Laves phases from P6₃/mmc to triclinic P1 across every structure tested: TiFeSi, TiCo₂, SmCo₅, FeCoN, Fe₁₆N₂, and more. Dense intermetallics with mixed Wyckoff occupancy trigger a systematic symmetry erasure. But Heusler structures (Mn₂YZ, Fm-3m) survive intact. The obvious hypothesis was that large, complex unit cells with many atoms are the problem. MOFs offered a clean test.
Metal-organic frameworks offer an enormous design space: metal nodes, organic linkers, topology, defects, and guests can all change performance. This team is for making that design space easier to explore together.
A useful MOF post connects a structure to a question: