| AVS 64th International Symposium & Exhibition | |
| Plasma Science and Technology Division | Tuesday Sessions |
| Session PS-TuP |
| Session: | Plasma Science and Technology Poster Session |
| Presenter: | Natale Ianno, University of Nebraska-Lincoln |
| Authors: | N.T. Lauer, University of Nebraska-Lincoln N.J. Ianno, University of Nebraska-Lincoln |
| Correspondent: | Click to Email |
Leveraging the advantages of high impulse magnetron sputtering (HiPIMS) requires knowledge of the temporal evolution characteristics and transport properties of the target material from the cathode to the substrate. These are difficult characteristics to measure directly. Determining the desired process parameters required for specific results by experiment, such as pulse voltage, duty cycle, pressure, magnetic field strength and profile, electrode separation, substrate biasing, and target current density, is time consuming and expensive involving multiple experiments combined with months of characterizing depositions. Also, this approach must be repeated for each target material and gas mixture used. This makes the ability to model and predict plasma properties and deposition or etching results due to external driving parameters via computer simulation attractive.
A 1d3v particle-in-cell (PIC) local density adjustment Monte-Carlo-Collision (LDA-MCC) model has been applied to model the specifics of sputtering using HiPIMS. Physics of the plasma-target interaction and diagnostics were incorporated into the model resulting in the ability to better understand the target species evolution at the cathode and subsequent transport to the substrate. The LDA-MCC was used regarding specific collision types to support transient particle volume density gradients and population inversions in the plasma associated with HiPIMS. Temporal evolution of species energy distribution functions (EDFs), volume densities, and populations at various locations within the plasma are characterized. Simulation predictions are compared with a variety of different experimental results in the literature supporting the validity of the model. These results will support future enhancements to the model to explore substrate bias effects on the process of target ion transport, tailoring energy distributions of deposited ions at the anode, investigating the utility of synchronized pulsed substrate biasing, and their effects on deposition characteristics.