Revealing the improved stability of amorphous boron-nitride upon carbon doping.

Onurcan Kaya, Luigi Colombo, Aleandro Antidormi, Mario Lanza, Stephan Roche

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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 sp3/sp2 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.
Original languageEnglish (US)
JournalNanoscale Horizons
StatePublished - Dec 20 2022

Bibliographical note

KAUST Repository Item: Exported on 2023-01-13
Acknowledgements: This project has been supported by Samsung Advanced Institute of Technology and is conducted under the REDI Program, a project that has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 101034328. ICN2 acknowledges the Grant PCI2021-122092-2A funded by MCIN/AEI/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR”. Simulations were performed at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility, supported by the U.S. DOE, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. Additional computational support was received from the King Abdullah University of Science and Technology-KAUST (Supercomputer Shaheen II Cray XC40) and Texas Advanced Computing Center (TACC) at The University of Texas at Austin.


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