Definition of a scoring parameter to identify low-dimensional materials components
Peter Mahler Larsen, Mohnish Pandey, Mikkel Strange, and Karsten Wedel, Jacobsen

TL;DR
This paper introduces a geometric scoring parameter to identify and classify low-dimensional materials, effectively distinguishing between 1D, 2D, and mixed-dimensional structures in large databases.
Contribution
A novel geometric analysis method and scoring parameter for identifying low-dimensional materials and their degree of dimensionality in extensive crystal structure databases.
Findings
Successfully separates 2D from non-2D materials
Identifies approximately 3000 1D and 9000 mixed-dimensional materials
Correlates scoring parameter with bonding strength and charge states
Abstract
The last decade has seen intense research in materials with reduced dimensionality. The low dimensionality leads to interesting electronic behavior due to electronic confinement and reduced screening. The investigations have to a large extent focused on 2D materials both in their bulk form, as individual layers a few atoms thick, and through stacking of 2D layers into heterostructures. The identification of low-dimensional compounds is therefore of key interest. Here, we perform a geometric analysis of material structures, demonstrating a strong clustering of materials depending on their dimensionalities. Based on the geometric analysis, we propose a simple scoring parameter to identify materials of a particular dimension or of mixed dimensionality. The method identifies spatially connected components of the materials and gives a measure of the degree of "1D-ness," "2D-ness," etc., for…
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Taxonomy
TopicsMachine Learning in Materials Science · X-ray Diffraction in Crystallography · Graphene research and applications
