Judgment by agents, numbers by code: auditable automated speciation analysis towards a chemistry world model
Year: 2026
Type: preprint
Abstract: Chemical speciation governs the reactivity, solubility, and toxicity of a solution, yet assembling speciation calculations from evaluated thermodynamic data remains a manual expert task whose reasoning is discarded once the figure is drawn. To mirror real-world research, automation belongs within a chemistry world model (CWM) where language agents curate and analyze data. As a first module, our agentic framework converts plain-language questions into deterministic equilibrium calculations grounded in NIST Standard Reference Database 46 (SRD-46). Agents resolve intent, curate records, adjudicate duplicates, design calculations, and estimate values beyond database coverage through induction-deduction-validation loops, while deterministic code validates every agentic commitment before it reaches the solver and compacts diagram topology into text readable without a vision stage. Across four case studies of escalating difficulty, quoted constants, patched records, and boundary coordinates reproduced their sources essentially exactly, whereas the same model without the framework missed phases or failed to build a solver. Residual errors surfaced only as auditable narration flaws, from misread topology to a sign-flipped hydrogen-evolution argument. The framework serves as a human-in-the-loop instrument delivering consensus-grade starting points, turning evaluated databases into active discovery instruments, mapping where language-model chemical reasoning still fails, and providing a general agentic template for finetuning.
Source: ChemRxiv
Institution: Argonne National Laboratory
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7214228694