Molecular dynamics simulation of silicon nanostructures
Introduction
A nanowire consists of a rod which can have a length of thousands of atoms while its width can be less than ten atoms. The atoms that build up the nanowire follow a crystallographic pattern and the axial direction can be parallel to any direction in principle. In the case of a silicon nanowire the atoms present the same structure as bulk silicon, e.g., the diamond structure. Such systems have recently been studied both experimentally and theoretically [3], [4].
Due to the small dimensions involved, silicon nanowires seem very promising on the engineering of very small gears that could be used, for example, in the production of nanomotors. Cui et al. [3] used laser catalyst growth to produce silicon nanowires at controllable sizes and orientations. Doping by implantation with boron or phosphorous could alter the electronic properties and produce a p or n-type semiconductor, respectively. Moreover, in the case of high doping the system exhibits a metallic behavior. These observations open the possibility of producing in the same wire regions having different electronic properties which could give origin to nanodiodes or nanotransistors. The ion implantation, a common technique to introduce dopants into materials seems to be very useful also in nanoscale systems [5], [6].
Wu et al. [4] synthesized via chemical vapor deposition silicon nanowires of several nanometers wide. Gold was used as a catalyst for the sylane vapor. High resolution microscopy helped on the identification of the geometries formed. The preferred orientation depends strongly on the nanowire diameter. For the smaller diameters, up to 10 nm, 95% of the nanowires were found to orient themselves along the 〈1 1 0〉 direction. As the diameter increases the nanowire tend to follow the 〈1 1 2〉 direction reaching the 〈1 1 1〉 direction for diameters between 20 and 30 nm.
Electron microscopy can identify the nanowire orientation as well as its diameter. However, it is not possible to localize the exact position of each particle in such system. The Molecular Dynamics approach can fill this gap left by the experimental technique. Starting from an initial configuration which can be inferred from the experimental evidences one can follow the evolution of the atomic positions of the system. Therefore, this technique can foresee surface reconstruction as well as the system response to irradiation. As it is well known, the computing time depends strongly on the number of particles; the larger the system the more cpu time is required. In order to avoid long simulation runs we decide to start with the smallest kind of silicon nanowires observed by Wu et al. [4] which are those aligned along the 〈1 1 0〉 direction.
The present contribution describes the details of simulation procedure and discusses the pertinence of the use of the usual potentials to simulate Si nanostructures. In Section 2 we briefly explain the details of the simulation technique. Right after we present our results and their implications. The last section presents our conclusions.
Section snippets
Simulation details
The Molecular Dynamics approach consists in solving the coupled equations of motions of all particles. In order to proceed with simulations we used a standard code which contains time saving techniques as a cutoff radius as well as neighbor list. The Verlet integrator and a time step of 1 fs were used. Periodic boundary conditions were used along the main nanowire axis while the other two directions were kept free. Since we have chosen to simulate the 〈1 1 0〉 nanowire, periodicity happens along
Results and discussion
A Molecular Dynamics simulation depends strongly on the choice of potential which rules out the interaction of each particle. There are several potentials which have been developed with the purpose of describing bulk silicon. We decided to compare the two most popular ones: Stillinger–Weber [1] and Tersoff [2]. Both potentials have been extensively studied regarding bulk properties. The main criterion we use in order to decide which potential works better will be the surface behavior. A good
Conclusion
We have performed Molecular Dynamics simulations of silicon nanowires using two different interatomic potentials in order to decide which one is best suited to this kind of system. Tersoff potential have shown more accurate surface reconstruction and phonons behavior when compared to Stillinger–Weber potential. Therefore, we conclude that Tersoff potential is more adequate to the case.
Self-irradiation runs showed that the choice of potential can lead to very different final configurations which
Acknowledgements
The authors would like to acknowledge the Brazilian funding agency CAPES for its financial support.
References (7)
- et al.
Computer simulation of local order in condensed phases of silicon
Phys. Rev. B
(1985) Empirical interatomic potential for silicon with improved elastic properties
Phys. Rev. B
(1988)- et al.
Doping and electrical transport in silicon nanowires
J. Phys. Chem.
(2000)
Cited by (28)
Long-range Tersoff potential for silicon to reproduce 30° partial dislocation migration
2024, Computational Materials ScienceOn the elastic modulus, and ultimate strength of Ge, Ge-Si nanowires
2020, Computational Materials ScienceCitation Excerpt :Mechanical properties of cubic Zinc blende (ZB) Si0.5Ge0.5 alloy nanowires [29], mechanical properties of a Si nanowire under uniaxial tension and compression [30] were studied using Tersoff potential. Tersoff potential was used to reconstruct nanowire surface and it is a very good potential to develop nanowire surface [31]. Tersoff potential was used to predict the covalent bonding of crystalline and amorphous phase of Silicon [32].
Numerical study of three-body diamond abrasive polishing single crystal Si under graphene lubrication by molecular dynamics simulation
2020, Computational Materials ScienceCitation Excerpt :The change in the distance between the atoms is related to the change in the coordination number of silicon from 4 to 6 [38]. Table 3 lists Si-I (brittle), Si-II (Metallic), Si-XII (R8), Si-III, Bct-5, the distance and number of five silicon-phase atoms from neighboring atoms [30,39–41]. In this study, in order to identify the different phases formed by the workpiece atoms, the radius was chosen to be larger than the maximum bond length in the surrounding environment, and the cutoff radius is 2.6 Å.
Phase transformation of monocrystalline silicon by nanoindentation – Effect of processing temperature
2019, Materials Science in Semiconductor ProcessingCitation Excerpt :Tersoff potential is used in this study to describe the interaction between the silicon atoms in the work material. It has been widely adopted to study the properties and deformation behaviors of silicon in MD simulation [7,38–40]. Tersoff parameters for silicon atoms are shown in Table 1.
Comparison of subsurface damages on mono-crystalline silicon between traditional nanoscale machining and laser-assisted nanoscale machining via molecular dynamics simulation
2018, Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and AtomsCitation Excerpt :Which are the interaction between silicon atoms (Si-Si) in the workpiece, interaction between carbon atoms (CC) in the tool, and interaction between workpiece and tool atoms (SiC). According to many previous works [31–41], Tersoff potential is adopted to describe the interaction between workpiece atoms in our simulation (SiSi). However, Tersoff potential are short ranged and yield ductile instead of brittle behavior for covalent materials such as diamond or silicon.
Comparison of tool-chip stress distributions in nano-machining of monocrystalline silicon and copper
2013, International Journal of Mechanical Sciences