Molecular dynamics simulation of diffusion behavior of N atoms on the growth surface in GaN solution growth

Kawamura, Takahiro; Kangawa, Yoshihiro; Kakimoto, Koichi; Suzuki, Yasuyuki

doi:10.1016/j.jcrysgro.2012.04.022

Cited by 5 publications

(3 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, to better understand the effect of N adatoms (adsorbed on the sidewalls) on the diffusion behavior of Ga adatoms, we analyzed the diffusion coefficient, which was previously studied in GaAs and GaN systems. [20][21][22] We used new systems that contain various numbers of N adatoms (0, 20, and 40) adsorbed on the ð10 10Þ sidewall, and a fixed number of Ga adatoms (10) near the sidewall. N adatoms were constrained in their position and prevented from desorption in the MD simulations, enabling us to investigate the dependence of Ga adatom diffusion on the number of N adatoms on the sidewalls.…”

Section: Resultsmentioning

confidence: 99%

Atomic-scale behavior of adatoms in axial and radial growth of GaN nanowires: Molecular dynamics simulations

Gong

Dogan

Zhang

et al. 2014

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

The effect of the flux ratio of N atoms to Ga atoms on the radial/axial growth of GaN nanowires during molecular-beam epitaxy has been investigated by molecular dynamics simulations. By studying adatoms on a surface during the growth of GaN nanowires, we explore the underlying mechanisms and find that both a preferable adsorption surface for N and Ga adatoms and the desorption of N adatoms play a key role for such axial/radial growth. These observations on the atomic scale are crucial for understanding the self-induced growth of GaN nanowires in general as well as for achieving their desired morphology under different growth conditions.

show abstract

Section: Resultsmentioning

confidence: 99%

Atomic-scale behavior of adatoms in axial and radial growth of GaN nanowires: Molecular dynamics simulations

Gong

Dogan

Zhang

et al. 2014

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

show abstract

“…In summary, the application of the present method to simple, generally used measurements, such as the PDF and ADF, helped greatly to elucidate the mechanism of crystallization from a melt. We expect that the method will contribute to elucidating the crystallization mechanisms not only for a simple single-component system, but also for complicated multicomponent systems, such as for the crystallization of minerals 16 , 34 – 38 , clathrate hydrates 39 – 41 , and materials for devices 1 , 42 – 44 .…”

Section: Discussionmentioning

confidence: 99%

Melt crystallization mechanism analyzed with dimensional reduction of high-dimensional data representing distribution function geometries

Nada

2020

Sci Rep

View full text Add to dashboard Cite

Melt crystallization is essential to many industrial processes, including semiconductor, ice, and food manufacturing. Nevertheless, our understanding of the melt crystallization mechanism remains poor. This is because the molecular-scale structures of melts are difficult to clarify experimentally. Computer simulations, such as molecular dynamics (MD), are often used to investigate melt structures. However, the time evolution of the structural order in a melt during crystallization must be analyzed properly. In this study, dimensional reduction (DR), which is an unsupervised machine learning technique, is used to evaluate the time evolution of structural order. The DR is performed for high-dimensional data representing an atom–atom pair distribution function and the distribution function of the angle formed by three nearest neighboring atoms at each period during crystallization, which are obtained by an MD simulation of a supercooled Lennard–Jones melt. The results indicate that crystallization occurs via the following activation processes: nucleation of a crystal with a distorted structure and reconstruction of the crystal to a more stable structure. The time evolution of the local structures during crystallization is also evaluated with this method. The present method can be applied to studies of the mechanism of crystallization from a disordered system for real materials, even for complicated multicomponent materials.

show abstract

“…17) Therefore, the parameters can be used for GaN growth simulation. The parameters have been successfully employed for vapor deposition 18,19) and melt growth 20,21) of GaN so far.…”

Section: Potential Functionmentioning

confidence: 99%

Molecular beam epitaxy growth of GaN under Ga-rich conditions investigated by molecular dynamics simulation

Kawamura

Hayashi

Miki

et al. 2014

Jpn. J. Appl. Phys.

Self Cite

View full text Add to dashboard Cite

Molecular beam epitaxial growth of GaN under Ga-rich conditions was simulated using a classical molecular dynamics method. We investigated nitrogen incorporation into the growth surface and the initial growth process using two kinds of simulation models: the Ga adlayer model and Ga droplet model. The simulation of the Ga adlayer model showed that the injected N atom diffused through the Ga adlayer and nucleation occurred in the solid/liquid interface. The simulation of the Ga droplet model showed that the injected N atom diffused on the bare GaN crystal surface and nucleation occurred at the edge of the Ga droplet. In the both simulations, scattering of injected N atoms on the surface of the Ga layer was often observed. Because Ga atoms in the Ga layer were intensively moving compared with that in the GaN crystal, injected N atoms were probably scattered by collisions with the Ga atoms in the Ga layer.

show abstract

Molecular dynamics simulation of diffusion behavior of N atoms on the growth surface in GaN solution growth

Cited by 5 publications

References 25 publications

Atomic-scale behavior of adatoms in axial and radial growth of GaN nanowires: Molecular dynamics simulations

Atomic-scale behavior of adatoms in axial and radial growth of GaN nanowires: Molecular dynamics simulations

Melt crystallization mechanism analyzed with dimensional reduction of high-dimensional data representing distribution function geometries

Molecular beam epitaxy growth of GaN under Ga-rich conditions investigated by molecular dynamics simulation

Contact Info

Product

Resources

About