Web of Science: 4 citations, Scopus: 4 citations, Google Scholar: citations,
Revealing the improved stability of amorphous boron-nitride upon carbon doping
Kaya, Onurcan (Institut Català de Nanociència i Nanotecnologia)
Colombo, Luigi (The University of Texas at Dallas. Department of Materials Science and Engineering)
Antidormi, Aleandro (Institut Català de Nanociència i Nanotecnologia)
Lanza, Mario (King Abdullah University of Science and Technology. Department of Material Science and Engineering)
Roche, Stephan (Institut Català de Nanociència i Nanotecnologia)

Date: 2022
Abstract: We report on a large improvement of the thermal stability and mechanical properties of amorphous boron-nitride upon carbon doping. By generating versatile force fields using first-principles and machine learning simulations, we investigate the structural properties of amorphous boron-nitride with varying contents of carbon (from a few percent to 40 at%). We found that for 20 at% of carbon, the sp/sp ratio reaches a maximum with a negligible graphitisation effect, resulting in an improvement of the thermal stability by up to 20% while the bulk Young's modulus increases by about 30%. These results provide a guide to experimentalists and engineers to further tailor the growth conditions of BN-based compounds as non-conductive diffusion barriers and ultralow dielectric coefficient materials for a number of applications including interconnect technology.
Grants: European Commission 101034328
Agencia Estatal de Investigación PCI2021-122092-2A
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió publicada
Subject: Amorphous boron nitride ; Barrier dielectrics ; Carbon doping ; Conductive diffusion barrier ; First principles ; Forcefields ; Growth conditions ; Learning simulation ; Machine-learning ; Young modulus
Published in: Nanoscale horizons, Vol. 8, Issue 3 (March 2022) , p. 361-367, ISSN 2055-6764

DOI: 10.1039/d2nh00520d


7 p, 1.0 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Experimental sciences > Catalan Institute of Nanoscience and Nanotechnology (ICN2)
Articles > Research articles
Articles > Published articles

 Record created 2023-04-12, last modified 2023-04-16



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