Christensen, Justin

Dennison, JR

Shen, T. -C.

Wilson, Gregory

Wood, Brian

English

Shen, T C

DigitalCommons@USU

Utah State University DigitalCommons@USU Posters Materials Physics 2018 SECONDARY ELECTRON YIELD MEASUREMENTS OF CARBON NANOTUBE FORESTS: DEPENDENCE ON MORPHOLOGY AND SUBSTRATE Brian Wood Utah State University Justin Christensen Utah State University Gregory Wilson Utah State University T C. Shen Utah State University JR Dennison Utah State Univesity Follow this and additional works at: https://digitalcommons.usu.edu/mp_post  Part of the Condensed Matter Physics Commons Recommended Citation Wood, Brian; Christensen, Justin; Wilson, Gregory; Shen, T C.; and Dennison, JR, "SECONDARY ELECTRON YIELD MEASUREMENTS OF CARBON NANOTUBE FORESTS: DEPENDENCE ON MORPHOLOGY AND SUBSTRATE" (2018). Posters. Paper 88. https://digitalcommons.usu.edu/mp_post/88 This Poster is brought to you for free and open access by the Materials Physics at DigitalCommons@USU. It has been accepted for inclusion in Posters by an authorized administrator of DigitalCommons@USU. For more information, please contact digitalcommons@usu.edu. Brian Wood, Justin Christensen, Greg Wilson, T.C. Shen, and JR Dennison USU Materials Physics Group, Utah State UniversityLogan, UT 84321-4415brian.wood314@gmail.comSECONDARY ELECTRON YIELD MEASUREMENTS OF CARBON NANOTUBE FORESTS: DEPENDENCE ON MORPHOLOGY AND SUBSTRATEAbstractTotal, secondary and backscatter electron yield data were taken with beam energies between 15 eV and 30 keV to determine the extent of suppression of substrate yields caused by carbon nanotube (CNT) forest coatings onsubstrates. CNT forests are low density graphitic carbon structures of vertically oriented CNT’s. Chemical vapor deposition (CVD) was used to grow multi-walled CNT forests between 20-50 μm tall on a thick silicon substratecapped with a 3 nm diffusion barrier of evaporated aluminum. CNT forests can potentially lower substrate yield due both to its low-Z (atomic number) carbon composition, along with its bundled, high aspect ratio architecture. Ingeneral, low-Z (atomic number) and low mass density conductors such as carbon have a lower density of bulk electrons for the incident electrons to interact with, thereby reducing the yields. Rough surfaces, and in particularsurfaces with deep high-aspect-ratio voids, can also suppress yields as electrons emitted from lower lying surfaces are recaptured by surface protrusions rather than escaping the near-surface region. Modification of yields fromcoatings can be modeled essentially serially, as layered materials with different yield curves contribute more at certain incident energies. However, it is shown that suppression of the yields due to forest morphology is moresignificant than simple proportional contributions of components, and is related to the angular distribution of backscattered and secondary electrons as a function of energy. These two effects are expected to be most pronouncedat low energies, where the incident electrons interact preferentially with the carbon at the surface.This study measured yields from three CNT forests of varied height and density, along with yields of an annealed substrate and constituent bulk materials. At incident electron energies above ~1200 eV the substrate yieldsdominated those of the CNT forests, as incident electrons penetrated through the low-density low-Z CNT forests and backscattered from the higher-Z substrate. At lower energies <1200 eV, the CNT forests substantially reducedthe overall yields of the substrate, and for <500 eV CNT forest yields were <1 and well below the already low yields of bulk graphite. The yield’s dependence on the height and density of the CNT forest is also discussed. Byunderstanding these effects on electron yield, CNT growth can be catered for specific environments to mitigate spacecraft charging.I. IntroductionThere is significant interest in reducing secondary electron emission frommaterials used for a variety of applications. This can be done by:• Coating surfaces with intrinsically low-yield materials. Low-Z (atomicnumber) and low mass density conductors such as carbon have a lower density ofbulk electrons for the incident electrons to interact with, thereby reducing theyields. Use of colloidal carbon coatings such as AquadagTM to cover surfaces ofelectron optics elements and accelerator beam pipes is an example.• Modifying the surface morphology. Rough surfaces can also suppress yields,as electrons emitted from lower lying surfaces are recaptured by surface protrusionsrather than escaping the near-surface region. The effect of surface roughness onelectron yield has even extended to materials of high aspect ratio with deep voids;such an example is carbon velvets which tend to reduce the secondary yield ofuntreated planar carbon. CNT forest height, density and presence of defects are themain factors expected to have an influence on their ability to absorb stray electronscoming off the substrate and originating within the forest itself.Carbon nanotube (CNT) forests can potentially lower yield in these ways,exploiting extreme properties of CNT forests. While attempts tomeasure the secondary yield of individual nanotubes have been made,the present study focuses on the CNT forest samples as a whole, todetermine the relative effects on the yield of the material compositionand morphology. Forest density, height, and presence of defects are thefactors of the morphology that are expected to affect the yield reductionof the sample. Forest density relates to the average packing density ofthe nanotubes which, along with CNT forest height, determines thedensity of bulk electrons (C atoms) that the incident electrons to interactand the range that the incident electrons will penetrate into the sample.II. Forest Growth and CharacterizationCNT forests were made in the Utah State University Nanofabrication Labusing a non-plasma enhanced chemical vapor deposition method.Substrates of n-type silicon wafer with a 3 nm layer of evaporatedaluminum deposited to produce the proper in-diffusion rate. The waferwas then diced into 1 cm2 pieces and loaded into a tube furnace at 700⁰C. A chemical precursor of xylene with a smaller molar concentration offerrocene was injected into the furnace, dissociating into hydrocarbonsand byproducts along with iron atoms from the ferrocene. Hydrogen andargon carrier gas flow into the furnace at 50 sccm facilitated evendistribution. Iron atoms coalesced on the substrate to form catalystparticles for free carbons to dissolve into. Duration of growth andprecursor volume tend to determine the height of the forest, while themolar concentration of ferrocene in the precursor influences the densityof the forest, with higher concentration producing denser forests butmore defects.Scanning Electron Microscopy (SEM) is used to determine the height ofthe forest, along with its relative density and the presence of defects.Figures 1(a) and 1(b) visually illustrate the differences in density of thedenser AlSi 129 sample compared to the AlSi 132 sample. Examples ofdefects are shown in Figs. 1(c) and 1(d).Scan code to access the USU Material PhysicsGroup papers and presentations.We gratefully acknowledge contributions from othermembers of the USU Materials Physics Groups.Fig. 1. Bottom side views of AlSi 129 (a) to AlSi 132, comparing the relative densitydifferences due to the difference of ferrocene concentration they were grown with. TypicalExamples of defects, a substrate chip (c) that can get dislodged and pushed to the top of theforest, with CNT’s still growing off of it, and (d) showing a bad portion with the forestscraped off, with inset of smaller typical surface deformations.Table I:  CNT Forest CharacteristicsSample Height FerroceneConcentration (%)Surface CoverageSurface Density(μg/cm3)AlSi 127 24-27 0.5 0.90 ~150AlSi 129 42-51 0.5 0.91 ~190AlSi 132 27-32 0.2 0.82 ~160III. Theory and Experimental SetupElectron yield is an incident energy-dependent measure of theinteractions of incident electrons with a material and characterizes thenumber of electrons emitted per incident electron. The total electronyield (TEY), is defined as the ratio emitted electron flux to the incidentflux,Backscatter electron yield (BSEY) describes electrons emitted from thematerial which originate from the incident beam; operationally BSE aredefined as electrons with emission energies >50 eV.SE yield (SEY) describes emitted electrons which originate within thematerial and are excited through inelastic collisions with the incidentelectrons; operationally SE are defined as electrons with emissionenergies <50 eV.Absolute yield were measured using a fully-enclosed hemispherical gridretarding field analyzer (HGRFA) (Fig. 2), which determines absoluteyield accurately (<5% absolute uncertainty), since the encapsulatingdesign captures almost all of the emitted electrons. Concentrichemispherical grids are used to energetically discriminate the collectedelectrons. SEY is calculated as the difference between TEY and BSEY.IV. Results and ConclusionsDue to the multi-component nature of the CNT forest-substratestructure, understanding of the yield is done by looking at contributionsfrom all materials individually. The contribution made by bare Si and Alto the AlSi substrate SEY is shown in Fig. 4(a). The penetration depth ofAl matches the layer thickness of 3 nm at 265 eV, below which the SEYof Al should dominate. After this energy, Si starts to rule thecontribution to the yield, where AlSi SEY lies ~30% above the differenceof yields between bare Si and Al, with the rise attributed to secondaryelectrons still being generated in the thin Al layer.Fig. 3 shows that the penetration depth of graphite set to ~3% of itsnormal density does not reach 30 µm until ~8500 eV, a factor of 7 higherthan the 1200 eV transition energy seen. This suggests that the effect ofthe CNTs at low energies is about an order of magnitude large thansimple density arguments predict, perhaps due to the CNT morphology.More quantitative measurements of mass density are needed toconfirm this. determine how the morphology suppresses substrate yieldbeyond density arguments.Total, secondary and backscatter electron yield data of a CNT forest andbulk graphite is seen in Fig. 4(b), taken with beam energies between 15eV and 30 keV demonstrate that carbon nanotube (CNT) forest coatingson substrates substantially suppress substrate yields. Figure 4(c) atincident electron energies above ~1200 eV shows the substrate yieldsdominated those of the CNT forests, as incident electrons penetratedthrough the low-density low-Z CNT forests and backscattered from thehigher-Z substrate. Above ~1200 eV, the yield of the forests is slightlyhigher than the bare substrate, which may result from lower attenuationof SE produced by BSE directed back out of the material. At lowerenergies <1200 eV, the CNT forests substantially reduced the overallyields of the substrate, and for <500 eV CNT forest yields were <1 andwell below the already low yields of bulk graphite. This suggests thatthe effect of the CNTs at low energies is about an order of magnitudelarge than simple density arguments predict, perhaps due to the CNTmorphology. The yield’s dependence on the height and density of theCNT forest is a relatively small effect, but is consistent with increasedinfluence of carbon scatter as the areal density of C atoms increases.𝜎𝜎 =𝑁𝑁𝑜𝑜𝑜𝑜𝑜𝑜𝑒𝑒−𝑁𝑁𝑖𝑖𝑖𝑖𝑒𝑒−=𝑄𝑄𝑜𝑜𝑜𝑜𝑜𝑜𝑒𝑒−𝑄𝑄𝑖𝑖𝑖𝑖𝑒𝑒−(1)Fig. 3. Log-log graph showing electron range versus incident energy for sample materials Al and Si(indistinguishable on this scale), bulk graphite (density of 2.2 g/cm3), and graphite scaled to 3% ofbulk graphite surface density as a surrogate for a material with graphitic composition but densitysimilar to CNT forests. Inset shows the penetration depth of 3 nm for aluminum occurs at 265 eV.Fig. 2. Schematic of the hemispherical grid retarding field analyzer (a), illustrating the incidentbeam impinging the sample through the drift tube, along with the inner grid to provide someshielding from a charged sample, the bias grid that can be charged to 50 volts to discriminatebackscatter electrons to be captured by the collector. A UV and flood gun may be used to neutralizeinsulating materials in between data collection that can store charge during electron pulsing. (b)shows possible interactions of incident electrons as it passes through the forest, creating secondarywithin the forest, aluminum and silicon, which then, depending on the incident energy, getcollected by the HGRFA.Fig. 4. Secondary electron yield measurements of component sample materials. (a) SEY versusincident energy of bulk Al and uncoated Si substrate, plus a bare coated AlSi substrate. The verticaldashed line indicates the energy of electrons with a 3 nm range. (b) SEY versus incident energy ofbulk HOPG graphite, a bare coated AlSi substrate, and an AlSi 129 substrate with CNT forest. (c)Electron yield versus incident electron energy for AlSi 127, AlSi 129 and AlSi 132 CNT forest samplescompared to a bare AlSi substrate.Values for height, ferrocene concentration and surface coverage are givenin Table I. Ferrocene concentration is a relative comparison of densitybetween forests. Surface coverage is also reported by counting thenumber of pixels above a threshold from top view images of the forest;this is strictly a superficial comparison, as the density varies throughoutthe forest.(a) (b)(a) (b)(c) (d)(a)(b)(c)

SECONDARY ELECTRON YIELD MEASUREMENTS OF CARBON NANOTUBE FORESTS: DEPENDENCE ON MORPHOLOGY AND SUBSTRATE

Secondary Electron Yield Measurements of Carbon Nanotube Forests: Dependence on Morphology and Substrate

Utah State University DigitalCommons@USU Posters Materials Physics 6-25-2018 Secondary Electron Yield Measurements of Carbon Nanotube Forests: Dependence on Morphology and Substrate Brian Wood Utah State University Justin Christensen Utah State University Gregory Wilson Utah State University JR Dennison Utah State Univesity T. -C. Shen Utah State University Follow this and additional works at: https://digitalcommons.usu.edu/mp_post  Part of the Condensed Matter Physics Commons Recommended Citation Wood, Brian; Christensen, Justin; Wilson, Gregory; Dennison, JR; and Shen, T. -C., "Secondary Electron Yield Measurements of Carbon Nanotube Forests: Dependence on Morphology and Substrate" (2018). SCTC. Posters. Paper 90. https://digitalcommons.usu.edu/mp_post/90 This Poster is brought to you for free and open access by the Materials Physics at DigitalCommons@USU. It has been accepted for inclusion in Posters by an authorized administrator of DigitalCommons@USU. For more information, please contact digitalcommons@usu.edu. Brian Wood, Justin Christensen, Greg Wilson, T.C. Shen, and JR Dennison USU Materials Physics Group, Utah State UniversityLogan, UT 84321-4415brian.wood314@gmail.comSECONDARY ELECTRON YIELD MEASUREMENTS OF CARBON NANOTUBE FORESTS: DEPENDENCE ON MORPHOLOGY AND SUBSTRATEAbstractTotal, secondary and backscatter electron yield data were taken with beam energies between 15 eV and 30 keV to determine the extent of suppression of substrate yields caused by carbon nanotube (CNT) forest coatings onsubstrates. CNT forests are low density graphitic carbon structures of vertically oriented CNT’s. Chemical vapor deposition (CVD) was used to grow multi-walled CNT forests between 20-50 μm tall on a thick silicon substratecapped with a 3 nm diffusion barrier of evaporated aluminum. CNT forests can potentially lower substrate yield due both to its low-Z (atomic number) carbon composition, along with its bundled, high aspect ratio architecture. Ingeneral, low-Z (atomic number) and low mass density conductors such as carbon have a lower density of bulk electrons for the incident electrons to interact with, thereby reducing the yields. Rough surfaces, and in particularsurfaces with deep high-aspect-ratio voids, can also suppress yields as electrons emitted from lower lying surfaces are recaptured by surface protrusions rather than escaping the near-surface region. Modification of yields fromcoatings can be modeled essentially serially, as layered materials with different yield curves contribute more at certain incident energies. However, it is shown that suppression of the yields due to forest morphology is moresignificant than simple proportional contributions of components, and is related to the angular distribution of backscattered and secondary electrons as a function of energy. These two effects are expected to be most pronouncedat low energies, where the incident electrons interact preferentially with the carbon at the surface.This study measured yields from three CNT forests of varied height and density, along with yields of an annealed substrate and constituent bulk materials. At incident electron energies above ~1200 eV the substrate yieldsdominated those of the CNT forests, as incident electrons penetrated through the low-density low-Z CNT forests and backscattered from the higher-Z substrate. At lower energies <1200 eV, the CNT forests substantially reducedthe overall yields of the substrate, and for <500 eV CNT forest yields were <1 and well below the already low yields of bulk graphite. The yield’s dependence on the height and density of the CNT forest is also discussed. Byunderstanding these effects on electron yield, CNT growth can be catered for specific environments to mitigate spacecraft charging.I. IntroductionThere is significant interest in reducing secondary electron emission frommaterials used for a variety of applications. This can be done by:• Coating surfaces with intrinsically low-yield materials. Low-Z (atomicnumber) and low mass density conductors such as carbon have a lower density ofbulk electrons for the incident electrons to interact with, thereby reducing theyields. Use of colloidal carbon coatings such as AquadagTM to cover surfaces ofelectron optics elements and accelerator beam pipes is an example.• Modifying the surface morphology. Rough surfaces can also suppress yields,as electrons emitted from lower lying surfaces are recaptured by surface protrusionsrather than escaping the near-surface region. The effect of surface roughness onelectron yield has even extended to materials of high aspect ratio with deep voids;such an example is carbon velvets which tend to reduce the secondary yield ofuntreated planar carbon. CNT forest height, density and presence of defects are themain factors expected to have an influence on their ability to absorb stray electronscoming off the substrate and originating within the forest itself.Carbon nanotube (CNT) forests can potentially lower yield in these ways,exploiting extreme properties of CNT forests. While attempts tomeasure the secondary yield of individual nanotubes have been made,the present study focuses on the CNT forest samples as a whole, todetermine the relative effects on the yield of the material compositionand morphology. Forest density, height, and presence of defects are thefactors of the morphology that are expected to affect the yield reductionof the sample. Forest density relates to the average packing density ofthe nanotubes which, along with CNT forest height, determines thedensity of bulk electrons (C atoms) that the incident electrons to interactand the range that the incident electrons will penetrate into the sample.II. Forest Growth and CharacterizationCNT forests were made in the Utah State University Nanofabrication Labusing a non-plasma enhanced chemical vapor deposition method.Substrates of n-type silicon wafer with a 3 nm layer of evaporatedaluminum deposited to produce the proper in-diffusion rate. The waferwas then diced into 1 cm2 pieces and loaded into a tube furnace at 700⁰C. A chemical precursor of xylene with a smaller molar concentration offerrocene was injected into the furnace, dissociating into hydrocarbonsand byproducts along with iron atoms from the ferrocene. Hydrogen andargon carrier gas flow into the furnace at 50 sccm facilitated evendistribution. Iron atoms coalesced on the substrate to form catalystparticles for free carbons to dissolve into. Duration of growth andprecursor volume tend to determine the height of the forest, while themolar concentration of ferrocene in the precursor influences the densityof the forest, with higher concentration producing denser forests butmore defects.Scanning Electron Microscopy (SEM) is used to determine the height ofthe forest, along with its relative density and the presence of defects.Figures 1(a) and 1(b) visually illustrate the differences in density of thedenser AlSi 129 sample compared to the AlSi 132 sample. Examples ofdefects are shown in Figs. 1(c) and 1(d).Scan code to access the USU Material PhysicsGroup papers and presentations.We gratefully acknowledge contributions from othermembers of the USU Materials Physics Groups.Fig. 1. Bottom side views of AlSi 129 (a) to AlSi 132, comparing the relative densitydifferences due to the difference of ferrocene concentration they were grown with. TypicalExamples of defects, a substrate chip (c) that can get dislodged and pushed to the top of theforest, with CNT’s still growing off of it, and (d) showing a bad portion with the forestscraped off, with inset of smaller typical surface deformations.Table I:  CNT Forest CharacteristicsSample Height FerroceneConcentration (%)Surface CoverageSurface Density(μg/cm3)AlSi 127 24-27 0.5 0.90 ~150AlSi 129 42-51 0.5 0.91 ~190AlSi 132 27-32 0.2 0.82 ~160III. Theory and Experimental SetupElectron yield is an incident energy-dependent measure of theinteractions of incident electrons with a material and characterizes thenumber of electrons emitted per incident electron. The total electronyield (TEY), is defined as the ratio emitted electron flux to the incidentflux,Backscatter electron yield (BSEY) describes electrons emitted from thematerial which originate from the incident beam; operationally BSE aredefined as electrons with emission energies >50 eV.SE yield (SEY) describes emitted electrons which originate within thematerial and are excited through inelastic collisions with the incidentelectrons; operationally SE are defined as electrons with emissionenergies <50 eV.Absolute yield were measured using a fully-enclosed hemispherical gridretarding field analyzer (HGRFA) (Fig. 2), which determines absoluteyield accurately (<5% absolute uncertainty), since the encapsulatingdesign captures almost all of the emitted electrons. Concentrichemispherical grids are used to energetically discriminate the collectedelectrons. SEY is calculated as the difference between TEY and BSEY.IV. Results and ConclusionsDue to the multi-component nature of the CNT forest-substratestructure, understanding of the yield is done by looking at contributionsfrom all materials individually. The contribution made by bare Si and Alto the AlSi substrate SEY is shown in Fig. 4(a). The penetration depth ofAl matches the layer thickness of 3 nm at 265 eV, below which the SEYof Al should dominate. After this energy, Si starts to rule thecontribution to the yield, where AlSi SEY lies ~30% above the differenceof yields between bare Si and Al, with the rise attributed to secondaryelectrons still being generated in the thin Al layer.Fig. 3 shows that the penetration depth of graphite set to ~3% of itsnormal density does not reach 30 µm until ~8500 eV, a factor of 7 higherthan the 1200 eV transition energy seen. This suggests that the effect ofthe CNTs at low energies is about an order of magnitude large thansimple density arguments predict, perhaps due to the CNT morphology.More quantitative measurements of mass density are needed toconfirm this. determine how the morphology suppresses substrate yieldbeyond density arguments.Total, secondary and backscatter electron yield data of a CNT forest andbulk graphite is seen in Fig. 4(b), taken with beam energies between 15eV and 30 keV demonstrate that carbon nanotube (CNT) forest coatingson substrates substantially suppress substrate yields. Figure 4(c) atincident electron energies above ~1200 eV shows the substrate yieldsdominated those of the CNT forests, as incident electrons penetratedthrough the low-density low-Z CNT forests and backscattered from thehigher-Z substrate. Above ~1200 eV, the yield of the forests is slightlyhigher than the bare substrate, which may result from lower attenuationof SE produced by BSE directed back out of the material. At lowerenergies <1200 eV, the CNT forests substantially reduced the overallyields of the substrate, and for <500 eV CNT forest yields were <1 andwell below the already low yields of bulk graphite. This suggests thatthe effect of the CNTs at low energies is about an order of magnitudelarge than simple density arguments predict, perhaps due to the CNTmorphology. The yield’s dependence on the height and density of theCNT forest is a relatively small effect, but is consistent with increasedinfluence of carbon scatter as the areal density of C atoms increases.𝜎𝜎 = 𝑁𝑁𝑜𝑜𝑜𝑜𝑜𝑜𝑒𝑒−𝑁𝑁𝑖𝑖𝑖𝑖𝑒𝑒− = 𝑄𝑄𝑜𝑜𝑜𝑜𝑜𝑜𝑒𝑒−𝑄𝑄𝑖𝑖𝑖𝑖𝑒𝑒− (1)Fig. 3. Log-log graph showing electron range versus incident energy for sample materials Al and Si(indistinguishable on this scale), bulk graphite (density of 2.2 g/cm3), and graphite scaled to 3% ofbulk graphite surface density as a surrogate for a material with graphitic composition but densitysimilar to CNT forests. Inset shows the penetration depth of 3 nm for aluminum occurs at 265 eV.Fig. 2. Schematic of the hemispherical grid retarding field analyzer (a), illustrating the incidentbeam impinging the sample through the drift tube, along with the inner grid to provide someshielding from a charged sample, the bias grid that can be charged to 50 volts to discriminatebackscatter electrons to be captured by the collector. A UV and flood gun may be used to neutralizeinsulating materials in between data collection that can store charge during electron pulsing. (b)shows possible interactions of incident electrons as it passes through the forest, creating secondarywithin the forest, aluminum and silicon, which then, depending on the incident energy, getcollected by the HGRFA.Fig. 4. Secondary electron yield measurements of component sample materials. (a) SEY versusincident energy of bulk Al and uncoated Si substrate, plus a bare coated AlSi substrate. The verticaldashed line indicates the energy of electrons with a 3 nm range. (b) SEY versus incident energy ofbulk HOPG graphite, a bare coated AlSi substrate, and an AlSi 129 substrate with CNT forest. (c)Electron yield versus incident electron energy for AlSi 127, AlSi 129 and AlSi 132 CNT forest samplescompared to a bare AlSi substrate.Values for height, ferrocene concentration and surface coverage are givenin Table I. Ferrocene concentration is a relative comparison of densitybetween forests. Surface coverage is also reported by counting thenumber of pixels above a threshold from top view images of the forest;this is strictly a superficial comparison, as the density varies throughoutthe forest.(a) (b)(a) (b)(c) (d)(a)(b)(c)

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Secondary Electron Yield Measurements of Carbon Nanotube Forests: Dependence on Morphology and Substrate

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