Probability theory of electron-molecule, ion-molecule, molecule-molecule, and Coulomb collisions for particle modeling of materials processing plasmas and cases

Nanbu, Kenichi

doi:10.1109/27.887765

Cited by 303 publications

(260 citation statements)

References 46 publications

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“…While the procedure is well known and documented in literature [28], some details are in order. First we derive the expressions for collision kinematics, since we have not found a compact and simple formulas in literature that are valid for particle collision of arbitrary masses and inelastic processes.…”

Section: Some Details Of An MC Simulationmentioning

confidence: 99%

“…The act of collision with a host particle is treated using the conservation laws and also the information from the differential cross sections about possible anisotrophies of the direction of an ion after the collision. More details about the MC technique one could find, for example, in a review paper [28].…”

Section: A Boltzmann Equation and The Distribution Functionmentioning

confidence: 99%

“…The evolution in between collisions is purely classical determined by the external force. The probability density that an ion that starts evolution at moment t = 0 will suffer a collision with a background gas particle after the time t is given by [28] …”

Section: B Flowchart Of Simulationmentioning

confidence: 99%

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A Monte Carlo simulation of ion transport at finite temperatures

Ristivojević

Petrović

2012

Plasma Sources Sci. Technol.

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We have developed a Monte Carlo simulation for ion transport in hot background gases, which is an alternative way of solving the corresponding Boltzmann equation that determines the distribution function of ions. We consider the limit of low ion densities when the distribution function of the background gas remains unchanged due to collision with ions. A special attention has been paid to properly treat the thermal motion of the host gas particles and their influence on ions, which is very important at low electric fields, when the mean ion energy is comparable to the thermal energy of the host gas. We found the conditional probability distribution of gas velocities that correspond to an ion of specific velocity which collides with a gas particle. Also, we have derived exact analytical formulas for piecewise calculation of the collision frequency integrals. We address the cases when the background gas is monocomponent and when it is a mixture of different gases. The developed techniques described here are required for Monte Carlo simulations of ion transport and for hybrid models of non-equilibrium plasmas. The range of energies where it is necessary to apply the technique has been defined. The results we obtained are in excellent agreement with the existing ones obtained by complementary methods. Having verified our algorithm, we were able to produce calculations for Ar + ions in Ar and propose them as a new benchmark for thermal effects. The developed method is widely applicable for solving the Boltzmann equation that appears in many different contexts in physics.

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Section: Some Details Of An MC Simulationmentioning

confidence: 99%

Section: A Boltzmann Equation and The Distribution Functionmentioning

confidence: 99%

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A Monte Carlo simulation of ion transport at finite temperatures

Ristivojević

Petrović

2012

Plasma Sources Sci. Technol.

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“…This introduces very different weight to be used for each species in the DSMC method. The collision algorithm for such a gas mixture is reported [6][7][8] and it is possible to increase the computation accuracy using different weight for each species.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is not appropriate to adopt the continuum (fluid) model for gas molecules. We simulate the gas flow using "DSMC-Neutrals (Particle-PLUS neutral module)", 4 which is a commercial software employing Direct Simulation Monte Carlo (DSMC) method [5][6][7][8] to solve kinetic Boltzmann equation.…”

Section: Introductionmentioning

confidence: 99%

The effect of carrier gas flow rate and source cell temperature on low pressure organic vapor phase deposition simulation by direct simulation Monte Carlo method

Wada¹,

Ueda²

2013

Journal of Applied Physics

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The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N 2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature. V C 2013 American Institute of Physics. [http://dx

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The Particle‐In‐Cell Method

Tskhakaya

Matyash

Schneider

et al. 2007

Contrib. Plasma Phys.

244

163

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This paper is the first in a series of three papers to summarize the recent work of an European-wide collaboration which is ongoing since about one decade using Particle-in-Cell (PIC) methods in low temperature plasma physics. In the present first paper the main aspects of this computational technique will be presented. In the second paper, an overview of applications in low-temperature plasma modelling will be given, whereas the third part will put emphasis on the specific results of modelling ion thrusters.

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Probability theory of electron-molecule, ion-molecule, molecule-molecule, and Coulomb collisions for particle modeling of materials processing plasmas and cases

Cited by 303 publications

References 46 publications

A Monte Carlo simulation of ion transport at finite temperatures

A Monte Carlo simulation of ion transport at finite temperatures

The effect of carrier gas flow rate and source cell temperature on low pressure organic vapor phase deposition simulation by direct simulation Monte Carlo method

The Particle‐In‐Cell Method

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