Product:Molecular Flow Module
Product:Molecular Flow Module
Model Low-Pressure Gas Flow in Vacuum Systems with the Molecular Flow Module
Understanding and Predicting Free Molecular Flows
Vacuum engineers and scientists use the Molecular Flow Module to design vacuum systems and to understand and predict low-pressure gas flows. The use of simulation tools in the design cycle has become more widespread as these tools improve understanding, reduce prototyping costs, and speed up development. Vacuum systems are usually expensive to prototype. Therefore, an increased use of simulation in the design process can result in substantial cost savings. The gas flows that occur inside vacuum systems are described by different physics than conventional fluid flow problems. At low pressures, the mean free path of the gas molecules becomes comparable to the size of the system and gas rarefaction becomes important. Flow regimes are categorized quantitatively via the Knudsen number (Kn), which represents the ratio of the molecular mean free path to the flow geometry size for gases:
|Flow Type||Knudsen Number|
|Continuum flow||Kn < 0.01|
|Slip flow||0.01 < Kn < 0.1|
|Transitional flow||0.1 < Kn < 10|
|Free molecular flow||Kn > 10|
While the Microfluidics Module is used for modeling slip and continuum flows, the Molecular Flow Module is designed for accurately simulating flows in the free molecular flow regime. Historically, flows in this regime have been modeled by the direct simulation Monte Carlo (DSMC) method. This computes the trajectories of large numbers of randomized particles through the system, but introduces statistical noise into the modeling process. For low-velocity flows, such as those encountered in vacuum systems, the noise introduced by DSMC renders the simulations unfeasible.
Accurate Modeling of Low-Pressure, Low-Velocity Gas Flows
The Molecular Flow Module is designed to offer previously unavailable simulation capabilities for the accurate modeling of low-pressure gas flows in complex geometries. It is ideal for the simulation of vacuum systems, including those used in semiconductor processing, particle accelerators, and mass spectrometers. Small channel applications (e.g., shale gas exploration and flow in nanoporous materials) may also be addressed. The Molecular Flow Module uses the angular coefficient method to simulate steady-state free molecular flows, allowing the molecular flux, pressure, number density, and heat flux to be computed on surfaces. The number density can be reconstructed on domains, surfaces, edges, and points from the molecular flux on the surrounding surfaces. You can model isothermal and nonisothermal molecular flows and calculate the heat flux contribution from the gas molecules.
Molecular Flow Module
- Isothermal and nonisothermal flows using the angular coefficient method
- Reconstruction of number densities on domains, boundaries, edges, and points
- Multiple species
- Diffuse flux, evaporation, and reservoir conditions for inflow boundaries
- Total vacuum and vacuum pump conditions for outflow boundaries
- Outgassing, thermal desorption, adsorption, and deposition conditions for walls
- Additional temperature boundary conditions for nonisothermal flows
- Mesh either the entire geometry or only the surfaces
- Vacuum systems
- Semiconductor processing equipment
- Materials processing equipment
- Ultra-high vacuum chemical vapor deposition (UHV/CVD)
- Ion implantation
- Charge exchange cells
- Thermal evaporation
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Adsorption and Desorption of Water in a Load Lock Vacuum System
This model shows how to simulate the time-dependent adsorption and desorption of water in a vacuum system at low pressures. The water is introduced into the system when a gate valve to a load lock is opened and the subsequent migration and pumping of the water is modeled.
Differentially pumped vacuum systems use a small orifice or tube to connect two parts of a vacuum system that are at very different pressures. Such systems are necessary when processes run at higher pressures and are monitored by detectors that require UHV for operation. In this model, gas flow through a narrow tube and into a high vacuum chamber ...
Molecular Flow Through an RF Coupler
This model computes the transmission probability through an RF coupler using both the angular coefficient method available in the Free Molecular Flow interface and a Monte Carlo method using the Mathematical Particle Tracing interface. The computed transmission probability determined by the two methods is in excellent agreement with less than a ...
Molecular Flow in an Ion-Implant Vacuum System
The Ion Implanter Evaluator app considers the design of an ion implantation system. Ion implantation is used extensively in the semiconductor industry to implant dopants into wafers. Within an ion implanter, ions generated within an ion source are accelerated by an electric field to achieve the desired implant energy. Ions of the correct charge ...
Rotating Plate in a Unidirectional Molecular Flow
This model computes the particle flux, number density and pressure on the surface of a plate that rotates in a highly directional molecular flow. The results obtained are compared with those from other, approximate, techniques for computing molecular flows.
Charge Exchange Cell Simulator
A charge exchange cell consists of a region of gas at an elevated pressure within a vacuum chamber. When an ion beam interacts with the higher-density gas, the ions undergo charge exchange reactions with the gas, creating energetic neutral particles. It is likely that only a fraction of the beam ions will undergo charge exchange reactions. ...
Molecular Flow Through a Microcapillary
Computing molecular flows in arbitrary geometries produces complex integral equations that are very difficult to compute analytically. Analytic solutions are, therefore, only available for simple geometries. One of the earliest problems solved was that of gas flow through tubes of arbitrary length, which was first treated correctly by Clausing. ...
This benchmark model computes the pressure in a system of outgassing pipes with a high aspect ratio. The results are compared with a 1D simulation and a Monte-Carlo simulation of the same system from the literature.
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