Comparison and discussion of candidate SEE materials

1. m Muons, Inc. Comparison and discussion of candidate SEE materials Z. Insepov (ANL), V. Ivanov (Muons Inc.)

2. Outline • Motivation • Semi-empirical theories • Monte Carlo simulations • Empirical models • Comparison with experiment • Summary

3. Motivation • Gain and TTS can drastically be improved by increasing SEE at first strike • Higher QE PC can be obtained by using Al2O3, MgO, and ZnO. • Multilayer structures can improve SEE • Surface roughness can affect the SEE • We need a tool to be able to predict SEE based on materials properties

4. Empirical Models • Space charge effect, charging effect of the emitting surface and reflection of incident electrons are not considered. • Number of emitted secondary electrons is determined by Poisson distribution having average value from equation below. • Secondary electrons have Maxwellian energy distribution and Cosine angular distribution. • Ito (1984) • Yakobson (1966) • Guest (1971) b – adjustable parameter • Agarwal (1958)

5. Comparison SEE models

6. SEE for models vs experiment

7. Comparison between theory and experiment

8. SEE of a rough surface The effect of surface roughness on the SEE from Be at E < 1 keV electron bombardment was studied by Monte Carlo simulation. With increasing aspect ratio H/W of the bowl structure, the SEE Yield increases, whereas for large H/W the yield is smaller. Kawata at al, JNM (1995) Krasnov, Vacuum (2004)

9. Semi-empirical theories e- l Al2O3 - Young (1956) Joy (1987) primary secondary • “Universal law of SE yield”

10. Low-Energy Monte Carlo codes   • Algorithm of SEE calculations Screening factor

11. Simulation results: 5 nm Al2O3 • Comparison of various models of SEE

12. Simulation results 5 nm Al2O3 • SEE vs primary electron angle and energy This parameterized set of SEE yield is used as an input to a macroscopic gain code for MCP simulation

13. Comparison with experiment None of them are from experiment except for J which is unimportant at low energies • SE yields of an Al2O3 were measured by a pulsed technique where surface was replenished by electron shower between the two pulses [21]. • Materials data used • in MC simulations: • Zav = 10 • Aav = 20.4 • r= 3.9 g/cm3 • e = 20 eV, • l = 60 Å • J = 145 eV

14. Summary • None of the existing Monte Carlo codes can simulate low-energy SEE from new, engineering materials, and with charge effects. • We need to build a MC code that will be able to treat mixtures, rough, multilayer surfaces, low energy, with charge accumulation. • Our current approach combines simple MC simulation, empirical models, and comparison to experiment. • Al2O3 SE yields were parameterized for two variables: EPE and incident angle and submitted as an input to macroscopic gain code. • We obtained a close agreement with experiment for Al2O3. • We plan to extend this approach to MgO, ZnO, and Al2O3+ZnO mixtures where experiment is sparse.

15. Acknowledgments • David C Joy ORNL • Pierre Hovington McGill University • Raynald Gauvin McGill University