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M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution
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DOI：10.1016/j.commatsci.2026.114901.png)
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Abstract
En 中文
The rapid advancement of artificial intelligence in materials science requires data standards and data management practices that can capture the complexity of atomistic structures, including surfaces, interfaces, defects, and dimensionality reduction. We present M-CODE - Materials Categorization via Ontology, Dimensionality and Evolution - an open-source codebase and framework for categorizing atomistic materials structures and recording their construction provenance. It links materials-science terminology to reusable software concepts, JSON schemas, examples, and provenance-aware transformations. M-CODE classifies structures by dimensionality, structural complexity (from pristine to compound pristine, defective, and processed), and variants that capture common structure creation and evolution approaches. The reference implementation provides schema-validated configurations, representative examples, and Python and TypeScript types/interfaces to support reproducible dataset generation, validation, exchange, and community contributions.
Keywords:
Categorization
Provenance
JSON schemas
Interoperability
FAIR data practices
Atomistic structures
Materials science
Data science
Journal
IF:
3.3
Papers:
1.4W
Citations:
3.6W
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