# M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution

arXiv: https://arxiv.org/abs/2602.14384 · HTML: https://mlsanity.com/paper/2602.14384/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2026.

## Built on by (most cited first, 1 of 1)

- [AI-ready design of realistic 2D materials and interfaces with Mat3ra-2D](https://mlsanity.com/paper/2603.27886/) (2026)

## Abstract (arXiv)

The rapid advancement of artificial intelligence in materials science requires data standards and data management practices that can capture the complexity of real-world structures, including surfaces, interfaces, defects, and dimensionality reduction. We present M-CODE - Materials Categorization via Ontology, Dimensionality and Evolution - a compact categorization system that links materials-science-specific terminology to a set of reusable concepts as building blocks 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. A practical implementation of the categorization is provided in an open-source codebase that includes JSON schemas, examples, and Python and TypeScript types/interfaces, designed to support reproducible dataset generation, validation, and community contributions.