Dataset for Electronics and Plasmonics in Graphene, Silicene, and Germanene Nanostrips

Talia Tene, Nataly Bonilla García, Miguel Ángel Sáez Paguay, John Vera, Marco Guevara, Cristian Vacacela Gomez () and Stefano Bellucci ()
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Talia Tene: Department of Chemistry, Universidad Técnica Particular de Loja, Loja 110160, Ecuador
Nataly Bonilla García: Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060155, Ecuador
Miguel Ángel Sáez Paguay: Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060155, Ecuador
John Vera: Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060155, Ecuador
Marco Guevara: INFN-Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Cristian Vacacela Gomez: INFN-Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Stefano Bellucci: INFN-Laboratori Nazionali di Frascati, I-00044 Frascati, Italy

Data, 2024, vol. 9, issue 2, 1-18

Abstract: The quest for novel materials with extraordinary electronic and plasmonic properties is an ongoing pursuit in the field of materials science. The dataset provides the results of a computational study that used ab initio and semi-analytical computations to model freestanding nanosystems. We delve into the world of ribbon-like materials, specifically graphene nanoribbons, silicene nanoribbons, and germanene nanoribbons, comparing their electronic and plasmonic characteristics. Our research reveals a myriad of insights, from the tunability of band structures and the influence of an atomic number on electronic properties to the adaptability of nanoribbons for optoelectronic applications. Further, we uncover the promise of these materials for biosensing, demonstrating their plasmon frequency tunability based on charge density and Fermi velocity modification. Our findings not only expand the understanding of these quasi-1D materials but also open new avenues for the development of cutting-edge devices and technologies. This data presentation holds immense potential for future advancements in electronics, optics, and molecular sensing.

Keywords: graphene; silicene; germanene; plasmons; electronics; semi-analytical model; DFT; GW approximation (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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