A property-registry contract for retrieve-or-refuse thermal-mechanical lattice search
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Abstract (arXiv)
Early thermal-mechanical lattice requirements are knowledge-intensive and often jointly unsatisfiable: an engineer asks for a cell that is light, stiff, laterally conducting and cheap, and no cell in the library satisfies it. A design system should say so, and say which requirement to loosen and by how much, rather than return the nearest row. A generative model can return a candidate even when the library holds none. This work applies established conflict diagnosis to a catalogue of homogenised properties. Search over 1,397 homogenised unit cells and 19 base materials (26,543 combinations) returns a catalogue row that a second solver can rebuild, or, for an empty feasible set of at most eight constraints, inclusion-minimal unsatisfiable subsets (MUS) and the slack of a repair, not a neighbour. One registry declaration generates the prompt and the evaluator, so undeclared parsed keys cannot reach search. On a frozen suite of 64 typed queries, retrieve-or-refuse matches min-repair on every feasible query (48/48) and refuses every empty one (16/16) with MUS and slack. Constraint-ignoring nearest-neighbour and penalty search violate stated cost or density limits. On 216 empty queries, repairs printed at three significant figures and rounded outward stay feasible in every case (216/216). When density and cost must be kept, a list of minimum-cardinality repairs keeps them on 209 of 211 queries; a protection-first repair keeps them on all 211, the same as full diagnosis. A 308-request parse benchmark is a template-text check, not unconstrained engineer prose.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 72 references that are in the map. First posted on arXiv 13 Sep 2026.
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References · 12
- 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
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- 2025Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformerscited by 5
- 2025MetaGen: A DSL, Database, and Benchmark for VLM-Assisted Metamaterial Generationcited by 3
- 2025Toward a Robust and Generalizable Metamaterial Foundation Modelcited by 1
- 2025Multi-Objective Infeasibility Diagnosis for Routing Problems Using Large Language Modelscited by 1
- 2026Why Not? Solver-Grounded Certificates for Explainable Mission Planningcited by 1
- 2026AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Designcited by 1
- 2026METASYMBO: Multi-Agent Language-Guided Metamaterial Discovery via Symbolic Latent Evolutioncited by 1
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