Large gyro-orbit model of ion velocity distribution in plasma near a wall in a grazing-angle magnetic field
Abstract: A model is presented for the ion distribution function in a plasma at a solid target with a magnetic field $\vec{B}$ inclined at a small angle, $ \alpha \ll 1$ (in radians), to the target. Adiabatic electrons are assumed, requiring $\alpha\gg\sqrt{Zm_{\rm e}/m_{\rm i}} $ where $m_{\rm e}$ and $m_{\rm i}$ are the electron and ion mass respectively, and $Z$ is the charge state of the ion. An electric field $\vec{E}$ is present to repel electrons, and so the characteristic size of the electrostatic potential $\phi$ is set by the electron temperature $T_{\rm e}$, $e\phi \sim T_{\rm e}$, where $e$ is the proton charge. An asymptotic scale separation between the Debye length, $\lambda_{\rm D}=\sqrt{\epsilon_0 T_{\text{e}}/e2 n_{\text{e}}}$, the ion sound gyroradius $\rho_{\rm s}=\sqrt{ m_{\rm i}(ZT_{\rm e}+T_{\rm i})}/(ZeB)$, and the size of the collisional region $d_{\rm c} = \alpha \lambda_{\rm mfp}$ is assumed, $\lambda_{\rm D} \ll \rho_{\rm s} \ll d_{\rm c}$. Here $\epsilon_0$ is the permittivity of free space, $n_{\rm e}$ is the electron density, $T_{\rm i}$ is the ion temperature, $B= |\vec{B}|$ and $\lambda_{\rm mfp}$ is the collisional mean free path of an ion. The form of the ion distribution function is assumed at distances $x$ from the wall such that $\rho_{\rm s} \ll x \ll d_{\rm c}$. A self-consistent solution of $\phi (x)$ is required to solve for the ion trajectories and for the ion distribution function at the target. The model presented here allows to bypass the numerical solution of $\phi (x)$ and results in an analytical expression for the ion distribution function at the target. It assumes that $\tau=T_{\rm i}/(ZT_{\rm e})\gg 1$, and ignores the electric force on the ion trajectory until close to the target. For $\tau \gtrsim 1$, the model provides a fast approximation to energy-angle distributions of ions at the target. These can be used to make sputtering predictions.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.