Proceedings of the 16th Annual Meeting of Particle Accelerator Society of Japan
July 31 - August 3, 2019, Kyoto, Japan

PASJ2019 THPH015

SECONDARY ELECTRON YIELDS FROM THERMAL-SPRAYED METALSURFACES AND MONTE CARLO SIMULATION OF SEY FROM ROUGHSURFACES
M. L. Yao†, SOKENDAI, Tsukuba, Ibaraki, Japan
Y. Suetsugu , K. Shibata1, H. Hisamatsu, T. Ishibashi1, S. Terui, KEK, Tsukuba, Ibaraki, Japan1
also at SOKENDAI, Tsukuba, Ibaraki, Japan
T. Nishidono, H. Chiba, Komiyama Electron Corp., Minamitsuru, Yamanashi, Japan
T. Sawahata, K. Ishii, MTC, Mito, Ibaraki, Japan
1

Abstract
We coated the copper substrates with copper by thermal
spraying, and investigated the relations between theirsecondary electron yield (SEY or δ), roughness and surface
composition. After enough conditioning, all the values ofmaximum SEY (δmax) were lower, and the energies of the
primary electrons that gives δmax (Emax) were higher than
the flat surfaces. For the copper samples, it was found thatthe δmax and Sa divided by the developed interfacial area
ratio (Sdr), Sa/Sdr, were in inverse proportion. Besides, weused Monte Carlo method to simulate the SEY of roughcopper surface. In the simulation, the relationship between
δmax and Sa/Sdr was inconsistent with the experimental
results. Furthermore, we applied the thermal spray togrooves and measured the SEYs from them. A lower dmax
was obtained even in a blunt groove. Even more interestingin this case, the measured and simulated δmax werequalitatively in agreement.

INTRODUCTION
It has been well known that the electron cloud effect(ECE) in a positron or proton ring seriously deteriorate theperformance of the collider, i.e., luminosity [1, 2]. The secondary electron yield (SEY or δ) is a primary parameter forcontrolling the ECE. One of the applicable solutions would
be preparing a material with a low SEY on the inner surface
of beam pipes.
A rough surface generally has a lower SEY than asmooth surface, and the roughening methods include machining, chemical reaction, laser abrasion, etc. The emitted
secondary electrons are likely to be captured on the roughsurface, and then the effective SEY should be reduced.
In this study, we investigated the SEY properties fromthe thermal-sprayed copper surfaces [3]. Thermal spraying
is an easy method to practice and has been widely used inindustries, here this technology is used for the first time to
reduce the SEY. The relations between the SEY properties
and the roughness parameters were investigated. Furthermore, we tried to explain the results by the numerical simulations using several SEY models. Finally, we applied thethermal spray method to grooved surface, and measured
SEY from them. The experimental and simulation results
were compared again.

EXPERIMENTAL
Sample Preparation
In this study, copper substrates were coated with copper
powder by plasma formed by argon and hydrogen. The
substrate is a disk with a diameter of approximately 15 mm
and a thickness of 3 mm. Copper is a relatively stable material compared to aluminum, and it is easier to process
than stainless steel. Therefore, we mainly used copper as
the research object.
Twelve different thermal-sprayed samples listed in Table
1 were prepared [3]. Two different sizes of copper powder
were used for thermal spraying. The diameter of the bigger
one is 125 - 170 μm (the samples are referred by “B” in thetable) and the smaller one is 45 - 50 μm (the samples arereferred by “S” in the table).
As for the substrate pre-treatment, except for the normal
machined surface (Ra = 1.14 μm), glass beads blast (GBB,
Ra = 8.14 μm) was used to enhance the coating adhesion.
The samples that had been treated with GBB were marked
as “GBB”. In sample B_LT, B_GBB_LT, S_LT and
S_GBB_LT, we simply used argon without mixing hydrogen as the plasma source to lower the plasma temperature,and these samples were marked as “LT”.
Furthermore, in order to increase the roughness of thesurface, we made two special patterns of the coating. The
first one is a trench. The samples B_GBBpre_trench and
S_GBBpre_trench were coated with a “trench” in the middle of the sample surface, of which depth is 50 μm and thewidth is 2 mm. First, we applied a coating on the surfaces
evenly (which was called “pre-spray” after GBB in this report and marked as “GBBpre”), then used a metal sheet asa baffle to perform the thermal spraying, leaving a trenchin the middle of the samples.
The second pattern is a mesh. In samples B_GBB_mesh,
B_GBBpre_mesh, S_GBB_mesh and S_GBBpre_mesh,
we used a metal mesh as a baffle to do the thermal spraying.
The aperture and wire diameter of the mesh are 0.597 and0.25 mm respectively. Samples B_GBBpre_mesh and
S_GBBpre_mesh had a uniform coating before the meshedspraying, and B_GBB_mesh and S_GBB_mesh were directly performed the mesh spraying after the GBB.

___________________________________________† yaomulee@post.kek.jp- 627 -

Proceedings of the 16th Annual Meeting of Particle Accelerator Society of Japan
July 31 - August 3, 2019, Kyoto, Japan

PASJ2019 THPH015

Table 1: Copper Samples

B_STD
B_LT
B_GBB_LT
B_GBBpre_trench
B_GBB_mesh
B_GBBpre_mesh
S_STD
S_LT
S_GBB_LT
S_GBBpre_trench
S_GBB_mesh
S_GBBpre_mesh
Cu flatSubstrate
Cu
Cu
Cu
Cu
Cu
Cu
Cu
Cu
Cu
Cu
Cu
Cu

Substrate
pre-treatment
Machined
Machined
GBB
GBB+pre-spray
GBB
GBB+pre-spray
Machined
Machined
GBB
GBB+pre-spray
GBB
GBB+pre-spray

Powdersize (μm)
Big(diameter
125-170)

Small(diameter
45-50)

Experiment
Here we list all the items of the experiments we havedone. For detailed settings, please refer to our previous report [3].
Roughness parameters measurement The measured
parameters include Sa (arithmetical mean height), Sq (rootmean square height), Sz (maximum height), Sdr (developed interfacial area ratio), etc [4].
SEM image measurement The typical magnifications we used were 100 [3].
Surface composition analysis The surface compositions of the copper samples B_GBB_LT, B_GBBpre_trench, S_GBB_LT and S_GBBpre_trench were investigated after the SEY measurement by using XPS at Komiyama Electron Corp. The results showed that there wasno significant difference in the surface composition inthese four copper samples. The main component of the surface was cuprous oxide (Cu2O), and some amorphous carbon and graphite produced by conditioning were detected.
From this, it could be inferred that the difference in SEYof these copper samples after the conditioning are mainly
caused by the surface topography.
SEY measurement The measurement started after abaking at 160 for 24 hours and the typical working pressure is at the level of 10-7 Pa. The SEY of each sample wasmeasured within 150 - 2000 eV of primary electron energy(Ep) after the conditioning time of 2, 7, 24 and 48 hours.
The Ep during the conditioning was 350 eV. After 48 hours
conditioning, the total electron dose reached to ≈ 6×10-2
C/mm2 [3].

MONTE CARLO SIMULATION OF SEY
FROM ROUGH SURFACES
Composition of Secondary Electrons

Plasmaforming gas
Ar + H2
Ar
Ar
Ar + H2
Ar + H2
Ar + H2
Ar + H2
Ar
Ar
Ar + H2
Ar + H2
Ar + H2

Specialpattern

Sa
(μm)
25.96
3.77
12.32
14.94
28.57
22.42
5.44
8.43
10.55
6.12
25.40
26.20
3.28

TrenchMesh
Mesh

Trench
Mesh
Mesh

Sdr
0.28
0.07
0.22
0.23
0.19
0.17
0.11
0.17
0.20
0.11
0.12
0.11
0.23

inside the material and are reflected back out. These are theso-called ‘‘re-diffused’’ electrons, and we call the corresponding current Ir. The rest of the electrons interact in amore complicated way with the material and yield the socalled ‘‘true-secondary electrons,’’ the current of which werefer as Its. The yields for each type of electron are definedby δe = Ie/I0, δr = Ir/I0, and δts = Its/I0, so that the total SEY(δ) is:
=

+

+

=

+

+

(1)

Usually, the δr is much smaller than δts (Ep > ~ 40 eV) orδe (Ep < ~40 eV), so here we neglected this portion in thesimulation. We consider the δ for two cases depending on
the incident electron energy Ep as follows:
,

≈
,

≈

,

for
for

> ~40
< ~40

(2)
(3)

The δe can be modeled as follows:
=

−

+

+

+

(4)

with two fit parameters E0 and R0. The R0 is the reflectivity
at zero impinging energy, which is typically 0.8. The valueof E0 should be determined from the measured data, but
typically 150 eV. We neglected the angle dependence of δebecause it is weak.
For the δts, after referring to several SEY models, theSEY model derived by Furman [5] was chosen to describethe δts in our simulation, which is based on a broad phenomenological fit to data for the secondary-emission yield.
The δts value is given by:

The conventional picture of secondary emission can besummarized as follows [5]: when a steady electron current
I0 impinges on a surface, a certain portion Ie is backscattered elastically while the rest penetrates into the material.
Some of these electrons are scattered by one or more atoms- 628 -

=

(5)
−1+

Proceedings of the 16th Annual Meeting of Particle Accelerator Society of Japan
July 31 - August 3, 2019, Kyoto, Japan

PASJ2019 THPH015

here s is an adjustable parameter that must be > 1. For offnormal incidence of the primary electrons, the δ dependence of the δmax and Emax are:( )=(0) 1 + 0.7(1 − cos )

(6)

( )=

(0)exp(7)(1 − cos )Here γ is a constant and is typically 1/2.

SEY Simulation from Rough Surfaces Using VBA
We developed a three-dimensional Monte Carlo simulation code to calculate “effective δ” from the rough surface
using the formulae described in the previous section. The
code was written in Excel Visual Basic for Application(Excel VBA). Total number of escaped secondary electrons is the “effective δ” from the surface in question.
In the simulation, a primary electron is injected vertically onto the surface (y = 0 plane) at first. The emission of
secondary electrons is calculated following the formula described in the previous subsection. A secondary electron istraced until it is adsorbed on the surface or it run away fromthe surface (y > 0.1 mm). The ratio of the number of runaway electrons and that of incident electrons are calculated
as the δ. Main parameters and assumptions used in the calculation are as follows:
1. Sample size is 8 mm × 8 mm (square).
2. Beam size of the primary electron is 4 mm × 4 mm
(square) at the center of the sample. The incident point
is randomly chosen over the ranges of the beam size.
3. Ep ranges from 50 to 2,000 eV with a step of 50 eV.
4. Typical number of primary electrons for each Ep is
8,000 and the electrons are randomly incident in therange of the beam size.
5. Range of incident angle θ is 0 ≤ θ < 90°, where θ = 0°means the normal incidence.
6. Range of the energy of the secondary electrons is 5 ~15 eV. The energy distribution is uniform within thisrange.
7. The emission direction of the secondary electrons
obeys the cosine distribution.
8. Calculated roughness parameters are Sa, Sq, Sz, Sdr.

Trapezoidal protrusions
The SEM observation of the sample surface indicatedthat the thermal-sprayed surfaces do not have sharp protrusions [3]. The shape of the peak and valley of the protrusions were not sharp, and the sides were not normal to thesurface. From these considerations, trapezoidal protrusion
surfaces were constructed to roughly imitate the real thermal-sprayed surfaces.
Figure 1 shows the pattern of how we change the parameters of the trapezoidal protrusion models. The Sz varies
from 50 to 300 μm with a step of 50 μm, and the θ varies
in 30°, 45°, 60° and 80°. The width of the peak and valley
is Sz divided by tanψ, where ψ = 30°, 45°, 60° and 80°.
Therefore 96 different trapezoidal protrusions were constructed. Figure 2 shows an example of the model of the
trapezoidal protrusions.

Figure 1: Parameters of the trapezoidal protrusions.

Figure 2: Model of the trapezoidal protrusions.

RESULTS AND DISCUSSIONSSEY Measurement

Figure 3: The δmax of Cu samples as a function of electron
dose.
Figure 3 shows the δmax of the copper samples as a function of electron dose after 48 hours conditioning as a function of the electron dose. As a whole, all the δmax of thethermal-sprayed copper surfaces were lower than that of
the flat copper surface, as expected. The energies of the
primary electrons that gives δmax (Emax) were higher than
the flat surfaces. Generally, the δmax was lower for the “S”type samples than for the “B”-type samples. For the caseof samples (B_STD, S_STD) and (B_GBBpre_trench,
S_GBBpre_trench), the δmax were almost the same. The meshed samples (S_GBB_mesh, S_GBBpre_mesh) had thelowest value of δmax.

- 629 -

Proceedings of the 16th Annual Meeting of Particle Accelerator Society of Japan
July 31 - August 3, 2019, Kyoto, Japan

PASJ2019 THPH015(a) δmax vs. Sa(b) δmax vs. Sdr(c) δmax vs. Sa/Sdr
Figure 4: The final δmax of Cu samples as a function of roughness parameters.

(a) δmax vs. Sa(b) δmax vs. Sdr(c) δmax vs. Sa/Sdr
Figure 5: The profiles of simulated δ against the roughness parameters of the copper trapezoidal protrusions.
For the “LT” samples, the coatings of samples (S_LT,
S_GBB_LT), where the smaller powders were used, kept
the bead shape successfully, but the coatings of samples(B_LT, B_GBB_LT), where the bigger powders were used,lost the bead shape and melt on the surface. However, theδmax of (S_LT, S_GBB_LT) were only slightly lower thanthat of (B_LT, B_GBB_LT), and all of them were higher
than that of (B_STD, S_STD). This may be related to theincompleteness of the distribution of the particles that retain the spherical shape.
Another interesting phenomenon was observed in thesamples (B_GBB_LT, S_GBB_LT) and (B_GBBpre_trench, S_GBBpre_trench). The δmax of these four
samples increased with the conditioning time. Now we suspect that these rising SEYs are due to the reduction of Cu2O
to Cu on the thermal-sprayed surfaces. But this cannot explain why only the SEY of these four samples rose with theexposure of electron beam. Further investigation is required.

Roughness parameters and SEY
Many roughness parameters had been compared to theδmax, but only some parameters appeared to be relevant.
Figure 4 shows the relationship between the final δmax andthe roughness parameter of Sa, Sdr and Sa/ Sdr for copper
samples. No obvious dependence of δmax on the Sa or Sdr
was found, but the δmax had evident negative correlation to
Sa/Sdr.
On the other hand, in the results of simulation for thecopper trapezoidal protrusions as shown in Fig. 5, the δmax
changed with the sharpness of the protrusions, i.e. lager θand shorter width, and was independent of the scale of thestructure. It was obvious that the δmax had strong negative

correlation to “Sdr”, but not “Sa/Sdr”, which is different
from the experiment.
We consider the following two possible reasons for thisdifference; (1) Instrument limitations: The different dependence on Sdr should be due to the resolution limit ofour 3D measuring microscope. For Sa, it needs the heightof particles, which is easier to obtain even for low resolution. But Sdr needs the lengths of slopes of the melted
metal particles on the surface, which is difficult to measurewith our resolution. We found that under different magnifications, Sa was almost the same, and the variation of Sdr
was quite large, which proved that our instrument has insufficient resolution for Sdr. (2) Diversity of the surface
pattern: We found that the patterns with different surface
shapes have different slope of δmax against Sdr, for example,
the slope of the trend of the triangular protrusion and thetrapezoidal protrusion was not the same. And due to thedifferent thermal-sprayed conditions, the pattern of the surface shape may vary greatly. From this standpoint, thetrend in Fig. 4(c) should be just a coincidence.

APPLICATION TO GROOVED SURFACES
We applied the thermal-sprayed coating to groove surfaces. Prepared samples are:
1. Sharp groove
2. Blunt groove
3. Blunt groove + Thermal spray
4. Blunt groove + Thermal spray + TiN coating
The schematic cross sections of structures 1 and 2 areshown in Fig. 6. It is reported that a groove with a sharperpeak/valley and a narrower angle generally has a lower δmax.
However, from a practical point of view, the manufacturing- 630 -

Proceedings of the 16th Annual Meeting of Particle Accelerator Society of Japan
July 31 - August 3, 2019, Kyoto, Japan

PASJ2019 THPH015

of a sharp groove is more difficult than that of a blunt
groove.
Figure 7 shows the δmax of the four samples after 48
hours conditioning as a function of the electron dose. As
shown in the figure, the δmax of the blunt groove with thethermal-sprayed coating is almost the same to the sharp
groove. It is a big merit of the thermal spray. By applying
TiN coating further on the thermal-sprayed surface, theδmax lowered further even in the blunt groove.

(a) Sharp groove(b) Blunt groove
Figure 6: Cross sections of (a) sharp groove and (b) blunt
groove.

Figure 7: The final δmax of the four groove samples as afunction of electron dose.
The SEYs for these four grooved structures were simulated using the surfaces with following parameters, where
the arcs at the bottoms and tops of the grooves were replaced by polygons, i.e., trapezoids, for simplicity;
1. δmax = 1.217, Emax = 450 eV and s = 1.5
2. δmax = 1.217, Emax = 450 eV and s = 1.5
3. δmax = 0.9636, Emax = 650 eV and s = 1.45, which wereobtained by fitting the experimental result of S_STD.
4. δmax = 0.6016, Emax = 700 eV and s = 1.2, which wereobtained by fitting the experimental result.

Figure 8 presents the correlations between measured δmax
and the simulated ones for these four samples. As shown inthis figure, a good correlation was obtained, although theδmax of the simulation were always lower than those ofmeasurements. This indicated that the present simulation
can qualitatively evaluate the SEY from the global roughsurfaces, such as groove structure.

CONCLUSION
For the SEY measurement, all the δmax of the thermalsprayed copper surfaces were lower than that of the flat
surface, and generally the δmax was lower for the “S”-typesamples than for the “B”-type samples. The Emax became
higher and the δ profiles were broader for the thermalsprayed surfaces compared to the case of flat surface. In
the copper samples, the meshed samples had the lowest
δmax and can reduce the δmax from ≈1.2 to ≈0.8. For theroughness measurement of copper samples, the δmax had
evident negative correlation to Sa/Sdr.
In the simulation, it was found that if the boundary of thesurface protrusion is more well-defined and sharper, alower SEY is obtained. In the results of simulation, the δmax
had strong negative correlation to “Sdr”, but not “Sa/Sdr”,
which was not consistent to the experimental results. We
infer that is caused by the insufficient resolution of the 3D
measuring microscope and the diversity of the surface pattern of the thermal-sprayed surfaces, since the patterns withdifferent surface patterns should have different slopes ofδmax against Sdr.
The thermal-sprayed groove shows a low SEY even a
blunt groove. This can be a big merit in manufacturing
grooves in a practical long beam pipes, where making a
sharp groove is hardly possible. Furthermore, a good correlation was obtained between the measured and simulated
δmax. These results indicate that the present simulation isable to make a qualitative prediction of SEY for the simple
periodic rough surface. Further investigation will be required to understand these discrepancies between the simulation and the experiments.

REFERENCES[1] Zimmermann, H. Fukuma, and K. Ohmi, “More electron
cloud studies for KEKB: Long-term evolution, solenoid patterns, and fast blowup”, CERN Report No. CERN-SL-Note2000-061 AP, Dec. 2000.
[2] H. Fukuma et al., “Observation of vertical beam blow-up in
KEKB low energy ring”, in Proc. EPAC2000, Vienna, Austria, Jun. 2000, pp. 1122-1124.
[3] M. Yao et al., “Secondary electron yields from thermal
sprayed metal surfaces”, in Proc. PASJ2018, Nagaoka, Japan,
Aug. 7-10, 2018, paper WEP113, pp. 649-653.
[4] Keyence, https://www.keyence.com/ss/products/microscope/roughness/surface/parameters.jsp[5] M. A. Furman and M. T. F. Pivi, “Probabilistic model for thesimulation of secondary electron emission,” Phys. Rev. ST
Accel. Beams, vol. 5, p.124404, Dec. 2002.

Figure 8: Correlation between the simulated and measured

δmax for the four grooved samples.
- 631 -