Secondary electron yield (SEY) curves in the 0-1000 eV range were measured on polycrystalline Ag, Au and Cu samples. The metals were examined as introduced in the ultra-high vacuum chamber and after having been cleaned by Ar+ ion sputtering. The comparison between the curves measured on the clean samples and in the presence of contaminants, due to the permanence in atmosphere, confirmed that the SEY behavior is strongly influenced by the chemical state of the metal surface. We show that when using very slow primary electrons the sample work function can be determined with high accuracy from the SEY curves. Moreover we prove that SEY is highly sensitive to the presence of adsorbates even at submonolayer coverage. Results showing the effect of small quantities of CO adsorbed on copper are presented. Our findings demonstrate that SEY, besides being an indispensable mean to qualify technical materials in many technological fields, can be also used as a flexible and advantageous diagnostics to probe surfaces a...

/pdf/the-secondary-electron-yield-of-noble-metal-surfaces-5hwqzsiq4j.pdf

The secondary electron yield of noble metal surfaces

The detailed study of the low energy Secondary Electron Yield (LE-SEY) of technical Cu for very low electron landing energies (from 0 to 30 eV) is very important for electron cloud build up in high intensity accelerators and in many other fields of research. However, LE-SEY has been rarely addressed due to the intrinsic experimental complexity to control very low energy electrons. Furthermore, several results published in the past have been recently questioned for allegedly suering from experimental systematics. Here, we critically review the experimental method used to study LE - SEY and define more precise energy regions, in which the experimental data can be considered valid. E-cloud simulations are than performed to address the impact of such results on electron cloud predictions in the LHC.

/pdf/detailed-investigation-of-the-low-energy-secondary-electron-wzj0yh9f5d.pdf

Detailed investigation of the low energy secondary electron yield of technical Cu and its relevance for the LHC

Secondary electron emission of graphene-coated copper

Evolution of the secondary electron emission during the graphitization of thin C films

The influence of microgeometries on the Secondary Electron Yield (SEY) of surfaces is investigated. Laser written structures of different aspect ratio (height to width) on a copper surface tuned the SEY of the surface and reduced its value to less than unity. The aspect ratio of microstructures was methodically controlled by varying the laser parameters. The results obtained corroborate a recent theoretical model of SEY reduction as a function of the aspect ratio of microstructures. Nanostructures - which are formed inside the microstructures during the interaction with the laser beam - provided further reduction in SEY comparable to that obtained in the simulation of structures which were coated with an absorptive layer suppressing secondary electron emission.

/pdf/role-of-surface-microgeometries-on-electron-escape-145xp1h0k4.pdf

Role of surface microgeometries on electron escape probability and secondary electron yield of metal surfaces

Low energy electrons in accelerators are known to interact with the circulating beam, giving rise to the formation of a so-called e- cloud. Such e- cloud may induce detrimental effects on the accelerated beam quality and stability. Those effects have been observed in most accelerators of positively charged particles. A longstanding effort has been so far devoted to understand in detail the physical origin of such e- cloud, its build-up and its interaction with the circulating beam. We will first describe the origin and the basic features causing e- cloud formation in accelerators, then we review some of the theoretical work produced to simulate and analyze such phenomenon. In selected cases, theoretical expectations and experimental observations will be compared, to address the importance of benchmarking codes versus observations to reach the required predictive capability. To this scope, codes need realistic input parameters which correctly describe material and surface properties at the basis of such e- cloud formation and build-up. The experimental efforts, performed worldwide in many surface and material science laboratories, to measure such essential parameters will then be presented and critically reviewed. Finally, we will describe some of the e- cloud mitigation strategies adopted so far and draw some conclusions.

Electron cloud in accelerators

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Electron cloud in accelerators