Repository: Freie Universität Berlin, Math Department

A fuzzy classification framework to identify equivalent atoms in complex materials and molecules

Lai, King Chun and Matera, S. and Scheurer, C. and Reuter, K. (2023) A fuzzy classification framework to identify equivalent atoms in complex materials and molecules. Journal of Chemical Physics, 159 (2). ISSN 0021-9606

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The nature of an atom in a bonded structure—such as in molecules, in nanoparticles, or in solids, at surfaces or interfaces—depends on its local atomic environment. In atomic-scale modeling and simulation, identifying groups of atoms with equivalent environments is a frequent task, to gain an understanding of the material function, to interpret experimental results, or to simply restrict demanding first-principles calculations. However, while routine, this task can often be challenging for complex molecules or non-ideal materials with breaks in symmetries or long-range order. To automatize this task, we here present a general machine-learning framework to identify groups of (nearly) equivalent atoms. The initial classification rests on the representation of the local atomic environment through a high-dimensional smooth overlap of atomic positions (SOAP) vector. Recognizing that not least thermal vibrations may lead to deviations from ideal positions, we then achieve a fuzzy classification by mean-shift clustering within a low-dimensional embedded representation of the SOAP points as obtained through multidimensional scaling. The performance of this classification framework is demonstrated for simple aromatic molecules and crystalline Pd surface examples.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Mathematics > Applied Mathematics
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Geophysical Fluid Dynamics Group
ID Code:3117
Deposited By: Ulrike Eickers
Deposited On:21 Feb 2024 13:23
Last Modified:21 Feb 2024 13:23

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