M-CODE：基于本体、维度和演化的材料分类
M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution
AI总结：
M-CODE通过本体、维度和演化方法实现材料分类，提供开源工具支持可重复的数据集生成和社区贡献。
摘要：
人工智能在材料科学中的快速发展要求数据标准和数据管理实践能够捕捉现实世界结构的复杂性，包括表面、界面、缺陷和降维。我们提出了M-CODE——通过本体、维度和演化进行材料分类——一种紧凑的分类系统，将材料科学特定术语链接到一组可重用的概念作为构建块和来源感知的转换。M-CODE通过维度、结构复杂性（从纯净到复合纯净、缺陷和处理）以及捕捉常见结构创建和演进方法的变体对结构进行分类。分类的实用实现包含在开源代码库中，包括JSON架构、示例和Python和TypeScript类型/接口，旨在支持可重复的数据集生成、验证和社区贡献。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
