Multiscale Analysis of Silicon LPCVD Reactor

2005 ◽  
Author(s):  
Yukinori Sakiyama ◽  
Shu Takagi ◽  
Yoichiro Matsumoto
Keyword(s):  
Potential Energy ◽  
Ab Initio ◽  
Multiscale Analysis ◽  
Potential Model ◽  
Research Work ◽  
Pair Potential ◽  
Dynamics Simulation ◽  
Molecular Orbital Calculations ◽  
Ongoing Research ◽  
Trajectory Calculations

We demonstrate the multiscale analysis of the transport phenomena in a low pressure reactor. In this method, the macroscopic phenomena such as the temperature and the density distribution are related to the microscopic electronic structure of atom/molecule. By connecting the different scales with physical models, the macroscopic properties are obtained starting from the first principle calculation without any empirical parameters. Here, we take the silicon epitaxial growth from a gas mixture of silane and hydrogen as an example. As the first step of this method, we calculated the intermolecular potential energy of SiH4/H2 using the ab initio molecular orbital calculations. Then, an analytical pair potential model was constructed to reproduce the potential energy surface obtained from the ab initio calculation. We have confirmed the validation of the potential model by comparing the experimental data of the transport properties with the molecular dynamics simulation using the potential model. Subsequently, the binary molecular collision models were constructed by the classical trajectory calculation using the potential model as the second step of the multiscale analysis. The trajectory calculations were conducted for the various combinations of the initial translational and the rotational energy. Through the statistical analysis of the trajectory calculations, the elastic/inelastic collision cross section and the scattering angle model were constructed. Finally, the direct simulation Monte Carlo simulation of flow field in a low parssure reactor was executed. The thin film thickness distribution was also investigated and discussed. This method was extended to analyze the surface reaction, which is an ongoing research work and only the current progress is reported here.

Empirical Potential-Energy Surfaces Fitting Using Feed forward Neural Networks

2012 ◽  
Author(s):  
Lionel Raff ◽  
Ranga Komanduri ◽  
Martin Hagan ◽  
Satish Bukkapatnam
Keyword(s):  
Potential Energy ◽  
Ab Initio ◽  
Potential Energy Surfaces ◽  
Force Fields ◽  
Pair Potential ◽  
Potential Surfaces ◽  
Empirical Potential ◽  
Functional Forms ◽  
Dynamics Simulations ◽  
Energy Surfaces

When the system of interest becomes too complex to permit the use of ab initio methods to obtain the system potential-energy surfaces (PES), empirical potential surfaces are frequently employed to represent the force fields present in the system under investigation. In most cases, the functional forms present in these potentials are selected on the basis of chemical and physical intuitions. The parameters of the surface are frequently adjusted to fit a very small set of experimental data that comprise bond energies, equilibrium bond distances and angles, fundamental vibrational frequencies, and perhaps measured barrier heights to reactions of interest. Such potentials generally yield only qualitative or semiquantitative descriptions of the system dynamics. Several research groups have significantly improved the accuracy of the values of the experimental properties computed using empirical potential surfaces by fitting the chosen functional form for the potential to the force fields obtained from trajectories using ab initio Car-Parrinello molecular dynamics simulations. The fitting to the force fields is usually done using a least-squares fitting approach. This method has been employed by Izvekov et al. to obtain effective non-polarizable three-site force fields for liquid water. Carré et al. have employed such a procedure to obtain a new pair potential for silica. In their investigation, the vector of potential parameters was fitted using an iterative Levenberg-Marquardt algorithm. Tangney and Scandolo have also developed an interatomic force field for liquid SiO2 in which the parameters were fitted to the forces, stresses, and energies obtained from ab initio calculations. Ercolessi and Adams have used a quasi-Newtonian procedure to fit an empirical potential for aluminum to data obtained from first-principals computations. Empirical potentials can be improved by making the parameters parameterized functions of the coordinates defining the instantaneous positions of the atoms of the system. This approach has been successfully employed by numerous investigators The difficulty with this procedure is that the number of parameters that must be adjusted increases rapidly. Appropriate fitting of these parameters requires a much more extensive database. Finally, the actual fitting process can often be tedious, difficult, and time-consuming.

Sign in / Sign up

Export Citation Format

Share Document