Sökning: (L773:2041 1723) lar1:(ltu) >
Dynamics of growing...
Dynamics of growing carbon nanotube interfaces probed by machine learning-enabled molecular simulations
-
- Hedman, Daniel (författare)
- Center for Multidimensional Carbon Materials (CMCM), Institute for Basic Science (IBS), 44919, Ulsan, Republic of Korea
-
- McLean, Ben (författare)
- Center for Multidimensional Carbon Materials (CMCM), Institute for Basic Science (IBS), 44919, Ulsan, Republic of Korea; School of Engineering, RMIT University, 3001, Victoria, Australia
-
- Bichara, Christophe (författare)
- Aix-Marseille Univ, CNRS, CINaM, UMR7325, 13288, Marseille, France
-
visa fler...
-
- Maruyama, Shigeo (författare)
- Department of Mechanical Engineering, The University of Tokyo, 113-8656, Tokyo, Japan
-
- Larsson, J. Andreas (författare)
- Luleå tekniska universitet,Materialvetenskap
-
- Ding, Feng (författare)
- Center for Multidimensional Carbon Materials (CMCM), Institute for Basic Science (IBS), 44919, Ulsan, Republic of Korea; Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), 44919, Ulsan, Republic of Korea; Faculty of Materials Science and Engineering, Institute of Technology for Carbon Neutrality, Shenzhen Institute of Advanced Technology Chinese Academy of Sciences, 518055, Shenzhen, China
-
visa färre...
-
(creator_code:org_t)
- Springer Nature, 2024
- 2024
- Engelska.
-
Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 15
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://ltu.diva-por... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- Carbon nanotubes (CNTs), hollow cylinders of carbon, hold great promise for advanced technologies, provided their structure remains uniform throughout their length. Their growth takes place at high temperatures across a tube-catalyst interface. Structural defects formed during growth alter CNT properties. These defects are believed to form and heal at the tube-catalyst interface but an understanding of these mechanisms at the atomic-level is lacking. Here we present DeepCNT-22, a machine learning force field (MLFF) to drive molecular dynamics simulations through which we unveil the mechanisms of CNT formation, from nucleation to growth including defect formation and healing. We find the tube-catalyst interface to be highly dynamic, with large fluctuations in the chiral structure of the CNT-edge. This does not support continuous spiral growth as a general mechanism, instead, at these growth conditions, the growing tube edge exhibits significant configurational entropy. We demonstrate that defects form stochastically at the tube-catalyst interface, but under low growth rates and high temperatures, these heal before becoming incorporated in the tube wall, allowing CNTs to grow defect-free to seemingly unlimited lengths. These insights, not readily available through experiments, demonstrate the remarkable power of MLFF-driven simulations and fill long-standing gaps in our understanding of CNT growth mechanisms.
Ämnesord
- NATURVETENSKAP -- Kemi -- Fysikalisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Physical Chemistry (hsv//eng)
Nyckelord
- Applied Physics
- Tillämpad fysik
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas