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  6. Example: Particle-PLUS: GEC-CCP Device Plasma Analysis

Example: Particle-PLUS: GEC-CCP Device Plasma Analysis

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Particle-PLUS

last updated:Jan 20, 2022

ウェーブフロント 本社
ウェーブフロント 本社
  • Official site

Introduction to Particle-PLUS Analysis Case: "Plasma Analysis of GEC-CCP Device" 3D Simulation Case

This is a 3D analysis case related to CCP (Capacitively Coupled Plasma) etching, which is one of the representative dry etching methods. Particle-PLUS specializes in plasma analysis within vacuum chambers and can perform simulations of etching rates and other parameters at high speed. ◇ Features of 'Particle-PLUS' - Excels in low-pressure plasma analysis. - By combining axisymmetric models with mirror-symmetric boundary conditions, it can obtain results quickly without the need for full device simulations. - Specializes in plasma simulations for low-pressure gases, where fluid modeling is challenging. - Supports both 2D and 3D, allowing efficient analysis even for complex models. - As a strength of our in-house developed software, customization to fit customer devices is also possible. ◆ Various calculation results can be output ◆ - Potential distribution - Density distribution/temperature distribution/generation distribution of electrons and ions - Particle flux and energy flux to the walls - Energy spectrum of electrons and ions at the walls - Density distribution/temperature distribution/velocity distribution of neutral gas and more. *Please feel free to contact us for more details.

    Other analytical equipmentScientific Calculation and Simulation SoftwareOther Software
スライド1.JPG

Example: Particle-PLUS: GEC-CCP Device Plasma Analysis

スライド1.JPG
スライド1.JPG
  • Related Link - http://www.wavefront.co.jp/CAE/particle-plus/

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basic information

**Features** - The time scheme uses the implicit method, allowing for stable time evolution calculations over a large time step Δt compared to conventional methods. - The collision reaction model between neutral gas and electrons and ions employs the Monte Carlo Scattering method, enabling accurate and rapid calculations of complex reaction processes. - The neutral gas module determines the initial neutral gas distribution used in the plasma module above, allowing for quick evaluation of gas flow using the DSMC method. - The sputter particle module calculates the behavior of atoms sputtered from the target in plasma and neutral gas environments, such as the flux distribution on opposing substrates, which can be evaluated in a short time. *For other functions and details, please feel free to contact us.*

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Delivery Time

P4

Applications/Examples of results

【Dual Frequency Capacitive Coupled Plasma】 - Optimization of voltage and other parameters to obtain high-density plasma - Damage to chamber walls - Optimization of power using external circuit models - It is possible to apply voltages to the electrode plates that align with real devices - The waveform of the applied voltage can be simulated smoothly and with relatively realistic voltages - Calculations are relatively stable to avoid applying unreasonable voltages 【DC Magnetron Sputtering】 - Uniformity of erosion dependent on magnetic field distribution - Adsorption distribution of sputtered materials on the substrate 【Pulsed Voltage Magnetron Sputtering】 - Optimization of the application time of pulsed voltage to efficiently sputter materials 【Ion Implantation】 - The influence of the substrate on the erosion distribution 【Time Evolution of Applied Voltage on Electrode Plates】 - It is possible to observe physical quantities that are difficult to measure experimentally, such as electron density and ion velocity distribution - By investigating electron density and ion velocity distribution, it is possible to examine the uniformity of the film and the damage to the chamber walls - By changing calculation conditions, optimization of high-density plasma generation at low power is possible

Detailed information

  • スライド2.JPG

    ◇Model Overview Ar Plasma Analysis of 3D (Three-Dimensional) GEC-CCP Device

  • スライド3.JPG

    Potential distribution and self-bias effect

  • スライド4.JPG

    Growth of Plasma Observed through Electron Density Distribution

  • スライド5.JPG

    Particle density distribution (steady state) - Electron density distribution (time-averaged) - Ar+ density distribution (time-averaged) It can be seen that there are more ions than electrons near the surface, indicating the formation of a sheath.

  • スライド6.JPG

    Reaction rate distribution - Ionization rate (period average) - Excitation rate (period average)

  • スライド7.JPG

    Temperature distribution - Electron temperature (periodic average) - Ar+ temperature (periodic average) In a particle model, it is possible to analyze the non-equilibrium temperature distribution of the plasma. (In a fluid model, it is difficult to accurately evaluate the temperature distribution of low-temperature plasma because it requires assuming a velocity distribution function.)

  • スライド8.JPG

    Energy distribution - Electron energy (period average) - Ar+ energy (period average)

  • スライド9.JPG

    - Magnitude of ion velocity (period average) - Joule heat (period average) Ions are strongly attracted by the self-bias of the power supply electrode. Additionally, Joule heat (the dot product of current density and electric field) increases in that area.

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Our company develops and sells a "Maintenance Management System" for managing and operating various plants, factories, and other facilities and assets. Currently, this system is undergoing significant evolution into a system that incorporates IoT technologies, such as sensor information and input from tablet devices, as well as AI technologies like machine learning, featuring functions for failure prediction and automatic scheduling. Additionally, as part of the recent trend of digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to improve operational efficiency. In line with this trend, our company provides a solution aimed at enhancing efficiency in research and development environments, which is the Laboratory Information Management System (LIMS). This software includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.

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