Sputter yields of monoatomic solids by Ar and Ne ions near the threshold: A Bayesian analysis of the Yamamura Model

Abstract

Semi-empirical formulae like the Yamamura model provide a quick reference of sputter yields for applications such as sputter depth profiling and secondary ion mass spectrometry. Fit parameters in such models are prone to errors which can propagate into the prediction of sputter yields. We compare experimental sputter yields to predictions of the Yamamura model using a Bayesian Markov Chain Monte Carlo (MCMC) algorithm. The model parameters Q (linear scaling) and s (power-law scaling) are explored. The results from MCMC are then compared to propositions of Seah (Surface and Interface Analysis, 2005) and extended to a collection of target materials by fitting simulated yields for argon and neon using TRIDYN. Q was found to be proportional to the threshold energy and a simple relation is proposed. The simplicity notwithstanding, Q is speculated to be dependent on a multitude of parameters such as density, energy transfer and orbital filling.