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Synthesizable Two-Dimensional Haeckelites with Auxetic Behavior and Multifunctional Properties: A Computational Study Integrating Machine Learning Interatomic Potentials

Ehsan AlibagheriDepartment of Physics, University of Tehran, North Kargar Ave., Tehran 14395-547, IranMohammad KhazaeiDepartment of Physics, University of Tehran, North Kargar Ave., Tehran 14395-547, IranBassam RabihaviDepartment of Physics, University of Tehran, North Kargar Ave., Tehran 14395-547, IranAhmad RanjbarDynamics of Condensed Matter and Center for Sustainable Systems Design, Theoretical Chemistry, University of Paderborn, Warburger Str. 100, D-33098 Paderborn, GermanyThomas D. KühneCenter for Advanced Systems Understanding (CASUS) and Helmholtz-Zentrum Dresden-RossendorfS. Mehdi Vaez AllaeiDepartment of Chemical and Materials Engineering, New Uzbekistan University, Movarounnahr Street 1, Tashkent 100000, Uzbekistan
ACS Materials Lettersjournal2025en
ABI

Abstract

No abstract available.

Topics

Machine Learning in Materials ScienceNanocluster Synthesis and Applications2D Materials and Applications

Identifiers

DOI
10.1021/acsmaterialslett.5c00809

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Cited by 094 references
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