The goal of the project is to study, by means of deterministic (ab initio molecular dynamics) and stochastic (kinetic Monte-Carlo), simulations the initial stages of thin metal film growth on weakly-interacting 2D substrates.
Atoms deposited from the vapor phase on weakly-interacting substrates self-assemble in dispersed three-dimensional (3D) nanoscale islands (i.e., nanostructures). A notable example is the deposition of metal films on two-dimensional (2D) crystals (e.g., graphene and MoS2) for which the tendency toward the formation of 3D agglomerates imposes technological obstacles for the use of 2D materials in a wide range of catalytic, sensing, and switching devices. Thus, understanding the currently unknown atomistic mechanisms that govern 3D island formation and shape evolution is a key step toward controlling film morphology and, by extension, the functionality of devices based on weakly-interacting film/substrate materials systems.
Over the past few years, we have carried out theoretical studies on the growth of thin metal films on weakly-interacting oxide substrates using an in-house kinetic Monte-Carlo (kMC) code. Our results reveal possible pathways and mechanisms for 3D island formation. Similar mechanisms may be operative during growth evolution of metals on 2D substrates.
The goal of this project is to model initial stages of noble-metal (e.g., Ag, Au, and Pd) film formation on model graphene and MoS2 surfaces. Our previously developed kMC code will be used as starting point and it will refined and augmented as detailed below:
(1) We will use DFT calculations to determine surface adsorption energies and diffusion barriers of metal adatoms on graphene and MoS2.
(2) We will also employ DFT-MD simulations, using to investigate atomistic processes during the initial stages of film island nucleation and growth and improve the accuracy of KMC simulations. The focus will be to identify concomitant atomistic reaction pathways, e.g., exchange diffusion events, concerted atomic processes, and near-surface diffusion processes and determine their rates at finite temperatures. This will allow further development of the KMC model by: (i) introducing additional diffusion pathways based on the determined processes, (ii) accounting for the effect of temperature on reaction rates, and (iii) verifying key atomic-scale processes discovered in KMC simulations.
Publications from our group where use of SNIC resources is acknowledged:
1. Edström et al., Acta. Mat. 144, 376 (2018)
2. Sanviovanni et al., Phys. Rev. B. 97, 035406 (2018)
3. Sanvgiovanni, Acta. Mat. 151, 11 (2018)
4. Sangiovanni, Appl. Surf. Sci. 450, 180 (2018)
5. Sangiovanni et al., Phys. Chem. Chem. Phys. 20, 17751 (2018)
6. Mosyagin et al., Phys. Rev. B. 98, 174103 (2018)
7. Lü et al., Phys. Rev. Mat. 2, 063401 (2018)
8. Elofsson et al., J. Appl. Phys. 123, 165301 (2018)
9. Almyras et al., Materials 12, 215 (2019)
10. Jamnig et al., Sci. Rep., under review (2019)
11. Gervilla et al., Phys. Mat., under review (2019)