Enhanced control of the ionization rate in radio-frequency plasmas with structured electrodes via tailored voltage waveforms

International audienceRadio-frequency capacitively coupled plasmas that incorporate structured electrodes enable increases in the electron density within spatially localized regions through the hollow cathode effect (HCE). This enables enhanced control over the spatial profile of the plasma density, which is useful for several applications including materials processing, lighting and spacecraft propulsion. However, asymmetries in the powered and grounded electrode areas inherent to the hollow cathode geometry lead to the formation of a time averaged dc self-bias voltage at the powered electrode. This bias alters the energy and flux of secondary electrons leaving the surface of the cathode and consequentially can moderate the increased localized ionization afforded by the hollow cathode discharge. In this work, two-dimensional fluid-kinetic simulations are used to demonstrate control of the dc self-bias voltage in a dual-frequency driven (13.56, 27.12 MHz), hollow cathode enhanced, capacitively coupled argon plasma over the 66.6--200 Pa (0.5--1.5 Torr) pressure range. By varying the phase offset of the 27.12 MHz voltage waveform, the dc self-bias voltage varies by 10%--15% over an applied peak-to-peak voltage range of 600--1000 V, with lower voltages showing higher modulation. Resulting ionization rates due to secondary electrons within the hollow cathode cavity vary by a factor of 3 at constant voltage amplitude, demonstrating the ability to control plasma properties relevant for maintaining and enhancing the HCE

QDB: A new database of plasma chemistries and reactions

One of the most challenging and recurring problems when modeling plasmas is the lack of data on the key atomic and molecular reactions that drive plasma processes. Even when there are data for some reactions, complete and validated datasets of chemistries are rarely available. This hinders research on plasma processes and curbs development of industrial applications. The QDB project aims to address this problem by providing a platform for provision, exchange, and validation of chemistry datasets. A new data model developed for QDB is presented. QDB collates published data on both electron scattering and heavy-particle reactions. These data are formed into reaction sets, which are then validated against experimental data where possible. This process produces both complete chemistry sets and identifies key reactions that are currently unreported in the literature. Gaps in the datasets can be filled using established theoretical methods. Initial validated chemistry sets for SF 6 /CF 4 /O 2 and SF 6 /CF 4 /N 2 /H 2 are presented as examples