TY - JOUR
T1 - Sputter yields of monoatomic solids by Ar and Ne ions near the threshold
T2 - A Bayesian analysis of the Yamamura Model
AU - Phadke, Parikshit
AU - Zameshin, Andrey A.
AU - Sturm, Jacobus M.
AU - van de Kruijs, Robbert W.E.
AU - Bijkerk, Fred
N1 - Funding Information:
The authors would like to thank (an) anonymous referee(s) for their useful/insightful comments. This work was funded by TNO , the “Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek”, and carried out in the Industrial Focus Group XUV Optics at the MESA+ Institute for Nanotechnology at the University of Twente. We acknowledge the additional support by the industrial partners ASML , Carl Zeiss SMT , Malvern Panalytical , as well as the Province of Overijssel and the Netherlands Organization for Scientific Research (NWO) .
Funding Information:
The authors would like to thank (an) anonymous referee(s) for their useful/insightful comments. This work was funded by TNO, the ?Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek?, and carried out in the Industrial Focus Group XUV Optics at the MESA+ Institute for Nanotechnology at the University of Twente. We acknowledge the additional support by the industrial partners ASML, Carl Zeiss SMT, Malvern Panalytical, as well as the Province of Overijssel and the Netherlands Organization for Scientific Research (NWO).
Publisher Copyright:
© 2022 The Authors
PY - 2022/6/1
Y1 - 2022/6/1
N2 - 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.
AB - 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.
KW - Bayesian statistics
KW - Inert ions
KW - Monoatomic solid targets
KW - Sputter yields
KW - UT-Hybrid-D
UR - http://www.scopus.com/inward/record.url?scp=85128149340&partnerID=8YFLogxK
U2 - 10.1016/j.nimb.2022.03.016
DO - 10.1016/j.nimb.2022.03.016
M3 - Article
AN - SCOPUS:85128149340
SN - 0168-583X
VL - 520
SP - 29
EP - 39
JO - Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms
JF - Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms
ER -