Plasma modeling normally requires knowing the electron energy distribution function (EEDF) as well as transport properties like electron mobility and diffusivity. To accurately calculate these quantities with the Boltzmann equation, we must also know the electron density (and possibly the density of all species subject to electron impact reactions). However, the electron (and species densities) are outputs of a plasma model, resulting in a catch-22. Let’s take a look at how to overcome this challenge using an example app.

Developing a device that generates nuclear fusion would provide a nearly limitless amount of clean energy on Earth. But while work on thermonuclear fusion began in the 1950s, engineers are still trying to make this goal a reality. One approach has been to use magnetic confinement devices known as tokamaks. See why a group of engineers at MIT’s Plasma Science Fusion Center (PSFC) turned to simulation to address a key challenge in tokamak design: instability due to plasma disruptions.

If you’ve ever worked with the Terminal boundary condition in COMSOL Multiphysics, you know that this electrical boundary condition can apply a current or voltage, among other options. But did you know that you can also dynamically switch between excitation types during a transient simulation? This is useful if you are trying to model a current- or voltage-limited power supply, for example. Today, we will look at how to implement such a switching behavior.

In a previous blog post, we introduced readers to different kinds of electron energy distribution functions (EEDFs) and their importance in plasma modeling. Today, we focus our attention on the Boltzmann Equation, Two-Term Approximation interface, demonstrating its use with an example from our Model Library.

When modeling plasmas, various options exist for choosing an ion temperature. Your choice, however, may strongly influence your model’s results. Let’s discuss the theoretical reason behind this phenomenon and study an example involving an inductively coupled plasma (ICP) to illustrate the influence the different ion temperature options have on your model’s results.

Due to the complex pumping scheme of high-power CO2 lasers, there are many species and collisions to consider in their analysis. This makes modeling plasma behavior in these devices — a key element in their optimization — a challenging task. Applying a multilevel approach, one researcher used the COMSOL Multiphysics® software to create a full 3D model of planar discharge in a CO2 laser. The results showcase the homogeneity of the discharge while offering further potential for optimizing laser designs.

In recent versions of the COMSOL Multiphysics® software, we’ve added several new multiphysics interfaces that include the constituent interfaces as separate physics interfaces, with the couplings predefined in the model tree’s Multiphysics node. This provides you with the best of both worlds, combining the flexibility of the constituent physics interfaces and the user-friendly nature of the predefined multiphysics couplings. The latest version of COMSOL Multiphysics® — version 5.2a — is no exception with the new Reacting Flow multiphysics interface.

I love my Philips Hue lighting system, which I bought over a year ago. The system allows you to set millions of different colors and thousands of brightness levels for up to 18 bulbs using a smartphone. You can also program the system to automatically turn on as you approach your residence, known as geofencing, or at specific times of the day. But how does the light quality compare to that of other lighting technologies?

Plasmas can exhibit a large variety of properties. There are plasmas with high and low ionization degrees, as well as those with high and low pressures and hot and cold temperatures. Different equations and modeling approaches are necessary for each kind of plasma. This blog post gives an overview of the different plasma types and shows when to use which of the interfaces available in the Plasma Module.

The electron energy distribution function (EEDF) plays an important role in plasma modeling. Various approaches can be used to describe the EEDF, such as Maxwellian, Druyvesteyn, or using a solution of the Boltzmann equation. Today, we will demonstrate the influence the EEDF has on a plasma model’s results. Additionally, we present a way to compute the EEDF with the Boltzmann Equation, Two-Term Approximation interface.