SmartCIF: A context-aware multi-agent system for automated preprocessing and curation of MOF CIFs
Abstract
adsorption data comprising 321 data points demonstrates that SmartCIF can reconciles geometric accessibility according to the original publications and request, avoiding both pore-blocking and over-opened nonphysical results based on the original publications. These results establish that CIF preprocessing is inherently application-dependent and that treating preprocessing assumptions as explicit, controllable variables is essential for reproducible, interpretable high-throughput screening. This assumption-aware paradigm embodied by SmartCIF generalizes existing computation-ready resources and provides a flexible foundation for large-scale simulations beyond adsorption.
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These papers typically split the workflow into role-specific agents for planning, structure retrieval, simulation execution, analysis, and quality control.
“These papers typically split the workflow into role-specific agents for planning, structure retrieval, simulation execution, analysis, and quality control [18,19,21,25,26,35-38,41,42].”
From From Scientific Copilots to Tool-Grounded Autonomy: AI Agents in Simulation-Driven Materials Discovery (2026) · cites this paper as [37]
The remaining literature was distributed across general materials-workflow papers, atomistic simulation infrastructures, MOF and porous-material screening, and polymer simulation.
“The remaining literature was distributed across general materials-workflow papers, atomistic simulation infrastructures, MOF and porous-material screening, and polymer simulation [17,21,22,24-26,32,35-42].”
From From Scientific Copilots to Tool-Grounded Autonomy: AI Agents in Simulation-Driven Materials Discovery (2026) · cites this paper as [37]
Other papers were more demonstrative, emphasizing workflow feasibility, design navigation, or case-based success rather than tightly standardized metrics.
“Other papers were more demonstrative, emphasizing workflow feasibility, design navigation, or case-based success rather than tightly standardized metrics [17,18,21,22,35,37-39,41].”
From From Scientific Copilots to Tool-Grounded Autonomy: AI Agents in Simulation-Driven Materials Discovery (2026) · cites this paper as [37]
Papers such as SmartCIF, DynaMate, VASPilot, Matty, GENIUS, and ToPolyAgent show that a substantial share of the current advance lies not in replacing scientific judgment with text generation, but in making brittle infrastructural steps programmable and recoverable.
“Papers such as SmartCIF, DynaMate, VASPilot, Matty, GENIUS, and ToPolyAgent show that a substantial share of the current advance lies not in replacing scientific judgment with text generation, but in making these brittle infrastructural steps programmable and recoverable [21,25,37-39,42].”
From From Scientific Copilots to Tool-Grounded Autonomy: AI Agents in Simulation-Driven Materials Discovery (2026) · cites this paper as [37]
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References 32 · Cited by 1
- Authors
- Zhang, Q., Zhang, C., & Wang, L.
- Affiliations
- Shanghai Jiao Tong University (CN)
- Corresponding author
- Wang, Liwei
- Venue
- Physical Chemistry Chemical Physics
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2026
- Volume
- 28
- Issue
- 15
- Pages
- 9566-9575
- ISSN
- 1463-9076 (ISSN-L)
- 1463-9084
- OpenAlex
- W7135233609
- Cited by
- 1
- References
- 32
- Citations by year
- 2026: 1
- FWCI
- 1.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Physical Chemistry Chemical Physics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Key Research and Development Program of China (2024YFE0210000)
- National Natural Science Foundation of China (523B2057)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Chemistry › Inorganic Chemistry › Metal-Organic Frameworks: Synthesis and Applications
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Keywords
- multi-agent systems, context-aware systems, crystallographic information files, automated data preprocessing, pore blocking, high-throughput screening, reproducibility, metal-organic frameworks
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