ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2026
Unsupervised Classification of Local Clathrate Hydrate Structures.
Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- The quasi-liquid layer thickness controls clathrate hydrates' growth rate.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
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3 authors.
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Abstract
Quantifying and differentiating the structural characteristics of clathrate hydrates at the molecular level is crucial for understanding the properties that underpin hydrate-based technologies. While useful, current approaches lack sufficient resolution to discern, e.g., interfacial and dynamical structures. In this study, we present an algorithm based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) that accurately identifies different water states coexisting within clathrate hydrates. A key novel component is an effective cavity-finder algorithm, which provides input to the clustering framework. The new algorithm detects hydrate cavities by analyzing the number and type of constituent molecular rings around voids. Integrating the new algorithm with widely used order parameters (e.g.,
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