Thermal properties have an outsized impact on efficiency and sensitivity of devices with nanoscale structures, such as in integrated electronic circuits. A number of thermal conductivity measurements for semiconductor nanostructures exist, but are hindered by the diffraction limit of light, the need for transducer layers, the slow scan rate of probes, ultrathin sample requirements, or extensive fabrication. Here, we overcome these limitations by extracting nanoscale temperature maps from measurements of bandgap cathodoluminescence in GaN nanowires of <300 nm diameter with spatial resolution limited by the electron cascade. We use this thermometry method in three ways to determine the thermal conductivities of the nanowires in the range of 19-68 W/m·K, well below that of bulk GaN. The electron beam acts simultaneously as a temperature probe and as a controlled delta-function-like heat source to measure thermal conductivities using steady-state methods, and we introduce a frequency-domain method using pulsed electron beam excitation. The different thermal conductivity measurements we explore agree within error in uniformly doped wires. We show feasible methods for rapid, in situ, high-resolution thermal property measurements of integrated circuits and semiconductor nanodevices and enable electron-beam-based nanoscale phonon transport studies.
Thermal properties have an outsized impact on efficiency and sensitivity of devices with nanoscale structures, such as in integrated electronic circuits. A number of thermal conductivity measurements for semiconductor nanostructures exist, but are hindered by the diffraction limit of light, the need for transducer layers, the slow scan rate of probes, ultrathin sample requirements, or extensive fabrication. Here, we overcome these limitations by extracting nanoscale temperature maps from measurements of bandgap cathodoluminescence in GaN nanowires of <300 nm diameter with spatial resolution limited by the electron cascade. We use this thermometry method in three ways to determine the thermal conductivities of the nanowires in the range of 19-68 W/m·K, well below that of bulk GaN. The electron beam acts simultaneously as a temperature probe and as a controlled delta-function-like heat source to measure thermal conductivities using steady-state methods, and we introduce a frequency-domain method using pulsed electron beam excitation. The different thermal conductivity measurements we explore agree within error in uniformly doped wires. We show feasible methods for rapid, in situ, high-resolution thermal property measurements of integrated circuits and semiconductor nanodevices and enable electron-beam-based nanoscale phonon transport studies.
Highly concentrated
energy densities
and fewer thermal conduction pathways through which waste heat dispan class="Chemical">sipates
can lead to substantially elevated temperatures and thereby reduced
performance in nanodevices. Temperature control is crucial in many
systems: nanowire single-photon detectors must be cryogenically cooled
to enter the superconducting regime and eliminate thermal noise;[1] nanowire lasers see a shift in lasing threshold
and wavelength with temperature rises;[2] thermoelectric nanostructures rely on low thermal conductivity to
generate large temperature gradients to increase efficiency of power
generation or detection;[3] and a microchip
can have significantly varying gain and noise characteristics across
its range of operating temperatures. Additionally, as integrated circuits
shrink in size, the on-chip power density has increased by an order
of magnitude over a decade, creating challenges in how to handle heat
dissipation in nanoscale transistors.[4] Therefore,
careful design of thermal management in nanostructure devices is critical
to provide stable output and performance, as these technologies increasingly
move to smaller scales. Past research has studied engineering thermal
conductivity by measuring or tailoring phonon mean free path spectra.[5−13] However, measuring both temperature and thermal conductivity of
nanostructures is notoriously difficult.
A number of noninvasive
methods have been devised to measure temperature
and thermal conductivity on the nanoscale.[14−17] The highest spatial resolution
thermometry methods include near-field scanning optical microscopy,[18,19] scanning thermal microscopy,[20,21] and transmispan class="Chemical">sion electron
microscopy.[22−24] These methods can have a spatial resolution well
below 100 nm but have generally slow data collection or cumbersome
probes or require very thin samples. Common thermal conductivity measurement
methods include the 3ω method,[25,26] the suspended
microchip method,[27−29] and time-domain thermoreflectance[8,9,13,30−33] and its variants.[33] These methods lack
the spatial resolution of the high-resolution thermometry methods
listed above and require invasive or extensive fabrication or a transducer
layer, all of which hinders the ability to measure smaller domains
or thermal boundary effects.[31,33]
Here we demonstrate
a rapid, high-resolution solution for measuring
temperature and the thermal conductivity of nanostructures using cathodoluminescence
(CL) spectroscopy. CL is radiation emitted when a high-energy electron
beam (e.g., in a scanning electron microscope (SEM)
or transmispan class="Chemical">sion electron microscope) interacts with a material. In
semiconductors, CL derives primarily from bandgap emission generated
when high-energy electrons lose energy to bulk plasmons through inelastic
collisions, which then excite hot electron hole pairs, which can thermalize
and/or generate electron hole pairs that subsequently recombine by
the emission of CL.[34−36] CL spectroscopy has been used in mineralogy,[37] semiconductor characterization,[38,39] and the study of plasmonic and photonic modes in metallic or dielectric
nanostructures with nanometer resolution.[40,41] As we will show, at low beam currents, CL thermometry provides high-resolution
noninvasive temperature measurements. At high beam currents, the beam
acts like a nearly delta function heat source while simultaneously
probing the temperature. CL has seldom been used for thermometry,[42,43] and it has not, to our knowledge, been used for nanoscale thermal
imaging or to study thermal conductivity. In our method of CL thermometry,
the spatial resolution is limited primarily by the electron beam cascade
size in the material, which can be in the range of about 1–200
nm depending on the electron energy, and also by the electron probe
size and the minority carrier diffusion length.[44] We apply this technique to study the thermal conductivity
of GaN nanowires, which are of increased interest due to their promise
for optoelectronic applications[45,46] including nanowire
lasers.[47−49]
First, with the spatial resolution of an SEM
cascade, we use the
thermal bandgap shift in semiconductors to map out the temperature
profile from an electron-beam-induced heat source in a nondestructive
manner, measuring electron-beam-induced temperature rises of over
500 K. Next, we use this thermometry technique to extract the thermal
conductivity of GaN nanowires with three different methods: two methods
upan class="Chemical">sing a DC electron beam current, and one method using a technique
involving an ultrafast electron beam blanker to provide an AC heating/thermometry
source. The data obtained using the three methods is comparable in
finding that the GaN nanowires exhibit a thermal conductivity lower
than that of bulk GaN. With higher spatial resolution than state-of-the-art
laser-based techniques[32] combined with
fast scan speeds, variable probing/heating depth, and no near-field
probe or thin sample requirement, our work enables nanoscale phononic
and thermal transport studies in semiconductors, including in situ measurements of silicon-integrated circuits.
Results
and Discussion
Temperature Measurements
The concept
of CL is shown
in Figure a, and the
CL setup used is described further in previous work.[50] Briefly, a parabolic mirror inside of the SEM chamber with
a numerical aperture of 1.46π sr is aligned over the sample
so that the focal point of the mirror corresponds to the electron
beam focus on the sample, and light is then collected and directed
to a spectrometer. An SEM image of one of the GaN nanowires used is
shown in Figure b.
The 200–300 nm diameter GaN nanowires were made by a top-down
approach based on sublimation under vacuum (see Methods) and exhibit lasing properties[49] under
optical pumping. We observe that the nanowires continue lasing while
simultaneously undergoing high current electron beam irradiation indicating
negligible degradation of the wires during CL measurements (see Figure S1 for more details). The nanowire was
broken off the substrate on which it was grown and placed on the frame
of a copper TEM grid covered with a 2 nm thickness of lacey carbon
film, which thermally isolates the wire relatively well. Figure c shows a CL intensity
map of the wire for emission between 360 and 420 nm, and the corresponding
SEM image (collected during CL imaging) is shown in Figure b taken at a beam current of
210 nA and electron energy of 5 keV. At each pixel in the CL map,
the electron beam is focused at this point, and light is collected
and the spectrum analyzed. Figure g illustrates a red-shift in the peak bandgap emission
of the CL spectrum as the electron beam becomes more centered on the
wire, which we will explain shortly, and the color of the spectra
in Figure g corresponds
to the location of the colored dots on Figure b,c (the gray curve is CL from a lower current
1.6 nA beam at the location of the red dot). The small, non-red-shifted
CL peak observed for the beam placed next to the wire results from
either backscattered or secondary electrons from the substrate, which
excite CL from the wire and deposit little power inside, or stray
electrons from an enlarged electron beam. The most intense and most
red-shifted CL is observed for a high-current electron beam centered
on the wire. Using CASINO[51] Monte Carlo
simulations, we determine that approximately 71% of the energy of
the electrons is converted to heat in the wire. The remainder of the
electron beam energy is mostly lost to backscattered and secondary
electrons (Figure S2), with a negligible
amount of energy lost to bandgap emission (Figure S3) and X-rays. Electron beam heating[52−55] calculations based on CASINO
Monte Carlo simulations have previously been verified experimentally.[52,53] With a 210 nA electron beam, this corresponds to 746 μW of
power being deposited in the wire in a nearly delta-function-shaped
power distribution (see Figure S2).
Figure 1
Nanoscale thermometry
CL measurement technique and monitored signals.
(a) Schematic of cathodoluminescence (CL) measurements on a semiconductor
nanowire. An electron beam heats/excites the semiconductor nanowire,
and incoherent CL is collected by the high-numerical-aperture parabolic
mirror and directed into a spectrometer. (b) SEM image (210 nA 5 keV
electron beam) of a GaN nanowire taken simultaneously with CL data.
(Inset) Zoomed-in region of a GaN wire. (c) CL counts integrated between
the wavelengths of 360–420 nm. (d, e) Peak CL wavelength extracted
by fitting the spectra corresponding to each pixel with a Lorentzian
for experiments performed with an electron beam current of 210 nA
(d) or 1.6 nA (e). Gray regions were pixels with peaks of less than
10 counts. (f) Temperature map measured when the electron beam (210
nA) is focused at each pixel, obtained by fitting the data in (d)
to eq . (g) CL spectra.
Each spectrum is obtained at the position of the corresponding color
dot in both (b) and (c). The amount of spatial overlap of the electron
beam and the nanowire dictates the energy absorbed in the nanowire
from the electron beam, resulting when the beam is centered on the
nanowire, in a maximum temperature rise and corresponding red-shift
of the CL emission according to eq . The gray curve corresponds to CL taken from a 1.6
nA electron beam at the location of the red dot (using a 50×
longer exposure time), and the other curves were taken with a 210
nA electron beam. Scale bars are 500 nm.
Nanoscale thermometry
CL measurement technique and monitored signals.
(a) Schematic of cathodoluminescence (CL) measurements on a semiconductor
nanowire. An electron beam heats/excites the semiconductor nanowire,
and incoherent CL is collected by the high-numerical-aperture parabolic
mirror and directed into a spectrometer. (b) SEM image (210 nA 5 keV
electron beam) of a pan class="Gene">GaN nanowire taken simultaneously with CL data.
(Inset) Zoomed-in region of a GaN wire. (c) CL counts integrated between
the wavelengths of 360–420 nm. (d, e) Peak CL wavelength extracted
by fitting the spectra corresponding to each pixel with a Lorentzian
for experiments performed with an electron beam current of 210 nA
(d) or 1.6 nA (e). Gray regions were pixels with peaks of less than
10 counts. (f) Temperature map measured when the electron beam (210
nA) is focused at each pixel, obtained by fitting the data in (d)
to eq . (g) CL spectra.
Each spectrum is obtained at the position of the corresponding color
dot in both (b) and (c). The amount of spatial overlap of the electron
beam and the nanowire dictates the energy absorbed in the nanowire
from the electron beam, resulting when the beam is centered on the
nanowire, in a maximum temperature rise and corresponding red-shift
of the CL emission according to eq . The gray curve corresponds to CL taken from a 1.6
nA electron beam at the location of the red dot (using a 50×
longer exposure time), and the other curves were taken with a 210
nA electron beam. Scale bars are 500 nm.
Our thermometry is carried out by tracking the shift in the peak
bandgap emission energy as a function of temperature, due to thermal
expansion of the lattice and changes in electron–phonon interactions
with temperature.[56,57] As shown in Figure S4, we calibrate the wavelength shift with temperature
in our GaN nanowires by measuring the bandgap shift as a function
of temperature between 90 and 300 K using a 548 pA beam current in
a liquid-nitrogen-cooled cryogenic stage on our microscope. At a beam
current this low the heating induced by the electron is negligible.
While GaN shows a bandgap shift at room temperature and higher, many
of our measurements were carried out below room temperature within
the range of our calibration curve to ensure our measurements were
accurate (we did not have a heating stage available for calibration);
in some cases we extrapolate this curve to higher temperatures, following
the Varshni phenomelogical formula,[57]where Eg is the
bandgap as a function of temperature, T, Eg(0) is the bandgap energy at 0 K (a fit parameter),
and γ and β are constants.[57] The bandgap shift could alternatively be fit to an expression from
O’Donnell and Chen.[56] While we focus
on CL thermal measurements in GaN in this paper, a bandgap shift (red
or blue) with increasing temperature can be seen in many other semiconductor
materials;[56,57] CL spectra for intrinsic GaAs
and p-doped Si wafers at different temperatures are shown in Figure S4 to demonstrate that the CL thermometry
and the thermal conductivity measurement techniques presented here
are not limited to use with GaN. Photoluminescence bandgap shifts
in GaN nanowires have previously been used to measure temperature
in a similar manner, but suffer from the poor resolution of the laser
used as a heater/probe.[58]From our
fit (Figure S4), we determined E(0) = 3.471 eV (in GaN this
corresponds to a donor-bound excitonic transition at low temperature,
not the bandgap[59]), β = 2609 K, and
γ = 2.25 × 10–3 eV/K, which is similar
to previous studies of GaN epilayers on sapphire substrates,[59] with differences likely caused by different
growth mechanism and the nanoscale geometries, and the fact that we
fit a single Lorentzian to the entire near-band-edge PL spectrum to
determine our effective bandgap instead of tracking shifts of individual
exciton transitions the PL spectrum is composed of. The root-mean-square
error in temperature of our data around the line of best fit is 6.0
K, which was measured in a region of fairly uniform doping. The thermal
stage used had a temperature accuracy of ±1 K, and additional
error likely comes from small doping variations within the region
measured. Larger errors in temperature will arise in regions of dissimilar
doping, which can be corrected for and will be discussed later. We
fit the data in Figure d with eq to create
a temperature map (Figure f) of the GaN nanowire resulting from electron beam heating
at each pixel.In order to reduce uncertainty in the thermal
contact area between
the wires and the substrate, nanowires were scattered over a copper
TEM grid (Ted Pella G2000HA) with 6.5 μm diameter holes. Wires
that straddled holes were heat sunk to the pan class="Chemical">copper via electron beam assisted Pt deposition to fix the temperature at the
ends of the wires during heating and reduce interfacial thermal resistance
between the wires and the Cu TEM grid.[28] An SEM image of a wire in this configuration is shown in Figure a. Following previous
work,[27−29,52−55,58,60,61] we treat the nanowires as 1D systems and
ignore thermal radiation and losses from CL (see Figure S3) in our analytical calculations. Finite element[62] simulations support this approximation. Figure b–e show temperature
maps of the wire in Figure a for different electron beam currents, in which the electron
beam itself is used both as a heat source and as a thermometer. In
these maps, the sample stage temperature was maintained at 161 K,
and the peak CL wavelength was extracted for each pixel on the map
and converted to temperature according to our calibration curve (eq ). Note that each pixel
is measured when the electron beam is focused on that particular location.
We use a 5 keV electron beam, as Monte Carlo simulations indicate
that at this energy most of the electron energy will be deposited
within the wire (Figure S2). A higher energy
beam would give better spatial resolution, but most of the electrons
would pass through the wire without interacting, decreasing heat deposition.
Figure 2
Nanoscale
temperature measurements at variable electron beam currents.
(a) SEM of suspended GaN nanowire with Pt heat sinks on either end.
(b–e) Temperature measurements of a GaN nanowire at the specified
electron currents. Gray regions indicate pixels that did not exhibit
a peak in the CL spectrum above 100 counts and 1 nm in width or which
could not be fit. Scale bars are 1 μm. The base temperature
in all measurements is 161 K.
Nanoscale
temperature measurements at variable electron beam currents.
(a) SEM of suspended pan class="Gene">GaN nanowire with Pt heat sinks on either end.
(b–e) Temperature measurements of a GaN nanowire at the specified
electron currents. Gray regions indicate pixels that did not exhibit
a peak in the CL spectrum above 100 counts and 1 nm in width or which
could not be fit. Scale bars are 1 μm. The base temperature
in all measurements is 161 K.
Several trends can be observed from the data in Figure . First, in all images the
largest temperature rise is observed toward the center of the wire,
as expected theoretically for a 1D system with fixed temperature at
both boundaries and an internal heat source. We can also see the high
spatial resolution of the CL thermometry technique. Using higher beam
pan class="Chemical">currents we can generate temperature increases of over 200 K, showing
the power of this technique to create temperature profiles from which
the thermal conductivity can be derived, as we will show below. The
CL from this wire was comparatively weak (possibly due to either the
doping level or increased surface recombination velocity from carbon
deposition), so a measurement with low enough current to create a
nonheated background measurement was not possible. In order to produce
the large currents in Figure c–e, a large 1 mm aperture in the SEM column was used,
which blocked fewer astigmatic electrons and created a misshapen electron
beam. This decreased resolution meant that when the majority of the
electron beam was focused on a pixel in the hole of the TEM grid,
some stray electrons were still striking the wire. Different electron
beam focusing settings (spots) were used to generate different currents,
which likely caused the hot spot in the center of the wire to shift
slightly. Figure b
used the same electron beam focusing settings as in Figure e, but used a 100 μm
aperture.
DC Thermal Conductivity Measurements
We demonstrate
three different methods to derive the thermal conductivity from the
CL profiles, the first two being DC measurements, with analysis pan class="Chemical">similar
to Raman thermography or photoluminescence mapping found in other
work.[58,60,61] In the DC
measurement techniques, the wire is suspended over a hole in the TEM
grid as shown in Figure a and Figure g and
heated by a continuous electron beam, and the steady-state temperature
is extracted at every point along the wire as shown in Figure a,b. We fit the temperature
profile using theoretical models for 1D wires with the temperature
fixed by heat sinking with SEM-deposited Pt at both ends (the bridge
method, Figure c)
or at one end (the slope method, Figure e). In the bridge method, thermal contact
resistance between the GaN and Cu TEM grid must be negligible,[61] and in the slope method this thermal contact
resistance is not important.[60]
Figure 3
Probing nanowire
thermal conductivity with a DC electron beam.
(a) Measured temperature as a function of position along the cut through
the GaN wire from Figure a (shown in the inset). Orange line is best fit to data using eq (DC bridge method), and
blue shading is 1 standard deviation of the fit error. We find a thermal
conductivity of the GaN nanowire of 22 ± 4.7 W/m·K and of
the Pt/GaN portion 91 ± 18.9 W/m·K. Base temperature for
these measurements is 161 K. Wire radius is 118 nm. (b) Demonstration
of DC slope method for determining thermal conductivity of two different
nanowires with fixed temperature at one end. “×”
data points are from 100 μm apertured electron beams with nm
spot sizes. The “○” data points are from data
collected with 1 mm apertured electron beams, which result in a less
well-defined spot size. The corresponding thermal conductivities are
shown in the legends. Radius of the nanowires is 130 ± 11.8,
123 ± 5.8, and 142 ± 11.4 nm for wires A, B, and C, respectively.
(c) Schematic of temperature profile in the wire corresponding to
the DC bridge method and values in eq . (d) Thermal circuit model for the DC bridge method,
shown here for the case of L1 ≤ x ≤ L2, where x is the location of the electron beam (see Supplementary Note for more details). (e) Schematic
of the temperature profile in the wire corresponding to the DC slope
method and values in eq . (f) Thermal circuit model for the DC slope method. (g) SEM and
peak wavelength map for each wire in the plot on the left. The peak
wavelength is measured with an electron beam current of 1 nA to extract
the doping variation without significantly heating the nanowire. The
wavelength shift due to doping was subtracted from wavelength shifts
due to heating to produce the curves in (b); see Supplementary Figure S6. The apparent crack in the Pt in the
SEM images is due to Pt being deposited at an angle to ensure good
thermal contact between the wire and Cu below by filling gaps on one
side of the wire. Scale bars are 500 nm.
Probing nanowire
thermal conductivity with a DC electron beam.
(a) Measured temperature as a function of position along the pan class="Chemical">cut through
the GaN wire from Figure a (shown in the inset). Orange line is best fit to data using eq (DC bridge method), and
blue shading is 1 standard deviation of the fit error. We find a thermal
conductivity of the GaN nanowire of 22 ± 4.7 W/m·K and of
the Pt/GaN portion 91 ± 18.9 W/m·K. Base temperature for
these measurements is 161 K. Wire radius is 118 nm. (b) Demonstration
of DC slope method for determining thermal conductivity of two different
nanowires with fixed temperature at one end. “×”
data points are from 100 μm apertured electron beams with nm
spot sizes. The “○” data points are from data
collected with 1 mm apertured electron beams, which result in a less
well-defined spot size. The corresponding thermal conductivities are
shown in the legends. Radius of the nanowires is 130 ± 11.8,
123 ± 5.8, and 142 ± 11.4 nm for wires A, B, and C, respectively.
(c) Schematic of temperature profile in the wire corresponding to
the DC bridge method and values in eq . (d) Thermal circuit model for the DC bridge method,
shown here for the case of L1 ≤ x ≤ L2, where x is the location of the electron beam (see Supplementary Note for more details). (e) Schematic
of the temperature profile in the wire corresponding to the DC slope
method and values in eq . (f) Thermal circuit model for the DC slope method. (g) SEM and
peak wavelength map for each wire in the plot on the left. The peak
wavelength is measured with an electron beam current of 1 nA to extract
the doping variation without significantly heating the nanowire. The
wavelength shift due to doping was subtracted from wavelength shifts
due to heating to produce the curves in (b); see Supplementary Figure S6. The apparent crack in the Pt in the
SEM images is due to Pt being deposited at an angle to ensure good
thermal contact between the wire and Cu below by filling gaps on one
side of the wire. Scale bars are 500 nm.
In the DC bridge method, both ends of the nanowire are heat sunk
with SEM-deposited Pt and suspended over a bare pan class="Chemical">copper TEM grid hole
(see inset of Figure a,g). We form an equivalent resistance model for the wire (described
in more detail in a Supplementary Note),
shown in Figure d,
similar to previous work.[61] We assume there
are two different thermal conductivities in the system: the thermal
conductivity of GaN in the center of the wire, κGaN, and an effective thermal conductivity for a mixture of GaN and
Pt closer to the Pt heat sinks, κ0, attributed to
the enlarged GaN nanowire radius due to excess Pt on the surface (see Figure S5, Figure c). L1 and L2 demarcate the boundaries between the regions of different
thermal conductivities and were treated as fit parameters. The system
is represented in Figure d by a thermal circuit model. Here, the thermal resistance
is given by R = lA/κ, with l being the relevant length of the particular segment and
κ the thermal conductivity of that segment. l can change depending on the position of the heat source (see Figure c, Supplementary Note), so the equations for the peak temperature
rise, ΔT(x), as a function
of x, the position of the electron beam heat source/thermometer,
arewhere Q̇ is
the heat flux from the electron beam, L is the
total wire length, A is the cross-sectional area
of the wire as measured via SEM images, and ΔT(x) = T(x) – T0, where T0 is the fixed temperature at x = 0 and x = L. Figure c shows this geometry in more detail. We
fit temperature data obtained in Figure e with eq in order to extract κGaN, κ0, L1, and L2. This fit is shown with the data in Figure a. We find the thermal
conductivity of the GaN region to be κGaN = 22 ± 4.7 W/m·K and the thermal conductivity
of the edge region to be κ0 = 91 ± 18.9 W/m·K.
Several factors affect the accuracy of the determination of the
parameters in the DC bridge method. First of all, our calibration
pan class="Chemical">curve only extends up to room temperature, while we extrapolate above
room temperature in this analysis, creating some uncertainty. In future
work this can be avoided by performing a more extended calibration.
Second, a small variation in doping within each nanowire causes a
∼1 nm variation in CL peak energy in different places along
the wire (CL variation due to doping has also been observed previously
in GaAs nanowires[39]), which also affects
the temperature calibration. This could be corrected for by using,
as a reference, low-current CL measurements that probe the bandgap
at each position, as we do later. Here we use a relatively high beam
current to create a fairly high temperature rise to more effectively
smooth out the 1 nm variations in CL peak shift along the wire (since
spectral peak shifts in this measurement are much larger than 1 nm).
Because we heat sink both ends of the wire, a relatively high current
is needed to achieve a large red-shift. We note that in most of our
nanowires a 1–2 μm region at one end shows both less
CL intensity (see Figure c) and a slightly blue-shifted CL peak relative to the rest
of the nanowire (measured at low electron beam currents), while toward
the other end of the wire an abrupt increase in CL counts with a slight
red-shift is observed. This is due to the doping profile introduced
during nanowire growth (see Methods). We note
that in the DC bridge model we neglect the interfacial thermal resistance[61] between the GaN and the Pt/Cu at either end,
as it is small compared to the thermal resistance of GaN, which we
verify with our measurements by ensuring temperature rises are very
small near the Cu heat sinks, as seen in Figure a. The interfacial thermal resistance is
not always negligible between the end of the wire and the Cu substrate,
which we observe in our measurements as a discontinuity between the
temperature of the nanowire near the Cu and the Cu temperature, known
from a thermometer in the sample stage (within 1 K accuracy) to which
the Cu is thermally connected with silver paint. To overcome this,
a different method can be used to measure thermal conductivity, the
DC slope method.[60]
In the DC slope
method, only one end of the wire is heat sunk (see Figure g) and the other
end extends into the center of the hole. In this method,[60] the temperature rise when the electron beam
is at position x away from the edge of the hole (Figure e) is given bywhere Rc is thermal
contact repan class="Chemical">sistance between the wire and the Cu frame. If we find the
slope, s, of this line, dΔT/dx, and solve for κGaN, we find the expression κGaN = Q̇/(sA). We determine A (wire cross-sectional area) from SEM images. Q̇ (heat flux) we determine from the measured electron beam current
correcting for energy lost to backscattered or secondary electrons
(determined from CASINO Monte Carlo simulations). In the case of the
“○” data points in Figure b, we also correct for larger electron beam
sizes that resulted as a consequence of using large currents. The
slope is found by fitting a line to the temperature profile of the
wire sufficiently far from the Pt contacts to avoid the effect of
the Pt/GaN thermal conductivity seen in Figure a. We additionally subtract the doping profile
(resulting from variations in intentional Si-doping during growth)
of the wires found under low electron beam current[39] shown in Figure g to correct for the ∼1 nm doping variations along
the wire as discussed above (see Figure S6, Methods). The profiles of three such wires
are shown in Figure b with thermal conductivities specified in the figure caption, ranging
from 19 to 66 W/m·K with errors ranging from 10% to 21%, which
derive primarily from uncertainty in A due to small
variations in diameter along the length of the wire and, in the case
of the “○” data points, from a 10% error in Q̇, as discussed below.
The benefit of the DC
slope method over the DC bridge method lies
in the ability to neglect thermal contact resistances. Additionally,
larger temperatures can generally be reached in wires only thermally
connected on one end. Overall, DC methods suffer from strong dependence
on localized doping variations. This can be overcome by extracting
bandgap variations due to doping profiles with low electron beam pan class="Chemical">currents,
as was done in Figure b. Because both doping concentration and temperature changes cause
bandgap variations, the effect of each must be determined separately.
By measuring the bandgap without heating the nanowire, we can determine
the bandgap variations due to doping concentrations. In these particular
nanowires, the doping variations are significant. If doping is neglected,
one could improperly extract a negative value for thermal conductivity
from uncorrected wire C thermal profile data in Supplementary Figure 6 due to a negative slope (eq ). There is additional uncertainty
that comes from the heat flux in the wire, in the case of Figure a and “○”
data points in Figure b. Because large currents are needed to raise temperatures for good
signal-to-noise ratio, larger apertures must be used in the electron
column, which leads to larger spot sizes.[63] This is generally negligible in comparison to the size of the electron
cascade, unless a large (e.g. 1 mm) aperture is used
and less of the incident electron beam impinges upon the wire, adding
some uncertainty to the measurements of the heat flux Q̇. In the measurements of Figure a and b (“○” data points only),
by examining the loss of resolution in secondary electron images as
a result of increased electron beam size, we calculate that only approximately
20–50% of the electron beam is reaching the nanowire without
an aperture. Thus, the current actually reaching the nanowires was
64.0 nA for Figure a, and for Figure b wires A, B, and C “○” data points were 15.7,
11.0, and 9.3 nA, respectively. To double-check the veracity of our
thermal conductivity measurements using the DC slope method, an aperture
was used when collecting the “×” data points in Figure b, leading to less
current (5.6, 3.2, and 3.2 nA for wires A, B, and C, respectively),
a smaller temperature rise in the wire, but all of the measured electron
beam current striking the wire in a several-nanometer-sized spot.
The dependence on knowing Q̇ to a high degree
of accuracy can be overcome by using AC methods to extract thermal
conductivity, as discussed in the next session.
AC Thermal
Conductivity Measurements
In the AC thermal
conductivity measurement technique, the column of the SEM was equipped[64] with a high-frequency electrostatic beam blanker
to modulate the electron current in a square wave on/off pattern.
The sample configuration is the same as that used in the DC slope
method described above, in which one end of the nanowire is heat sunk
with SEM-depopan class="Chemical">sited Pt and the other end is free (Figure g). In this method, we focus
the electron beam on the free end of the wire for the duration of
the experiment and vary the electron beam current frequency with a
waveform generator between 100 Hz and 5 MHz (Figure S7). Data collection for the studied frequency range took several
minutes total. Solving the 1D time-dependent heat equation (using
one Dirichlet and one time-dependent-periodic Neumann boundary condition)
for the quasi-steady-state temperature (after all transients have
subsided) at the free end of the nanowire, temperature varies according
to the expression (see Supplementary Note for more details)where T0 is the temperature of the fixed end/Cu frame, A is wire cross-sectional area, κ is the thermal conductivity
(we assume uniform thermal conductivity in the wire), ρ is the
density of GaN[65] (6150 kg/m3), C is the heat capacity[65] (490 J/kg·K), and L is
the wire length starting from the edge of the Pt deposition. Because
we use a spectrometer with a long exposure time (40 ms or longer)
compared to the modulation frequency of the beam, we measure the average
temperature over the half period when the electron beam is on (Figure b),The sum arises from
the Fourier
decomposition of a square wave. We find that at low modulation frequencies
(e.g., 100 Hz) the time-averaged temperature of the
GaN wire is higher, and therefore it has a more red-shifted CL spectrum
than at higher frequencies (e.g.,
5 MHz), as shown in Figure a.
Figure 4
Cathodoluminescence thermal conductivity measurements in the frequency
domain. (a) Cathodoluminescence (CL) spectra as a function of wavelength
for a 100 Hz (black), 200 kHz (pink), and 5 MHz (blue) square wave
electron beam excitation current. The electron beam current used in
this measurement to heat/probe the nanowire was 42 nA DC (the current
measurement was taken without modulation; with modulation the DC measured
current is half that value). (b) CL is only emitted when electron
current (red) is flowing, so the temperature read by CL (black, solid
line) will be on average (blue) higher for lower frequencies. (c)
Temperature as a function of electron beam square wave frequency for
the same wires from Figure b,g with one end held at a fixed temperature. Each plot shows
several different data collection runs (represented by different marker
types) for the same wire at slightly different locations on the end
of the wire. The solid line is the best fit line to the data, and
the shaded regions are 1 standard deviation of error in the fitting
function. The extracted thermal conductivities are shown in each plot.
Error is a combination of standard deviation of thermal conductivity
extracted from plot data and percent error in measurement due to uncertainty
in length measurements. The electron beam current used in this measurement
to heat/probe the nanowire was 18, 29, and 29 nA DC for wires A, B,
and C, respectively (the current measurement was taken without modulation;
with modulation the DC measured current is half the given value).
Cathodoluminescence thermal conductivity measurements in the frequency
domain. (a) Cathodoluminescence (CL) spectra as a function of wavelength
for a 100 Hz (black), 200 kHz (pink), and 5 MHz (blue) square wave
electron beam excitation current. The electron beam pan class="Chemical">current used in
this measurement to heat/probe the nanowire was 42 nA DC (the current
measurement was taken without modulation; with modulation the DC measured
current is half that value). (b) CL is only emitted when electron
current (red) is flowing, so the temperature read by CL (black, solid
line) will be on average (blue) higher for lower frequencies. (c)
Temperature as a function of electron beam square wave frequency for
the same wires from Figure b,g with one end held at a fixed temperature. Each plot shows
several different data collection runs (represented by different marker
types) for the same wire at slightly different locations on the end
of the wire. The solid line is the best fit line to the data, and
the shaded regions are 1 standard deviation of error in the fitting
function. The extracted thermal conductivities are shown in each plot.
Error is a combination of standard deviation of thermal conductivity
extracted from plot data and percent error in measurement due to uncertainty
in length measurements. The electron beam current used in this measurement
to heat/probe the nanowire was 18, 29, and 29 nA DC for wires A, B,
and C, respectively (the current measurement was taken without modulation;
with modulation the DC measured current is half the given value).
Wavelength spectra for each modulation frequency
were fit to extract
the temperature data shown for three different wires in Figure c, the same wires of which
were analyzed in Figure b using the DC slope method. Several different frequency sweeps were
performed for each wire at slightly different locations at the end
of the wires, which correspond to the different fit pan class="Chemical">curves in Figure c. The solid lines
are fits corresponding to eq . The error in thermal conductivity due to the variation in
thermal conductivity extracted from the fit of each curve in Figure c is approximately
4.1%, 6.6%, and 14% for wires A, B, and C respectively. The mean value
of L was taken from data from the DC slope method
(i.e., where a kink in slope of
temperature versus x appears, indicating Pt deposition,
not shown in Figure d but visible in Figure a), and uncertainty was measured as the range of the visible
thickening of the nanowire radius due to leakage Pt deposition, as
seen in SEM images. Uncertainty in L ranges from
5% to 10% for the wires. This leads to an uncertainty in thermal conductivity
due only to contributions from L uncertainty of 20%,
7.5%, and 20% for wires A, B, and C, respectively. Thus, uncertainty
in the AC method thermal conductivity measurements has the largest
contribution from L uncertainty. The leakage of Pt
deposition onto the wires was the primary culprit for this uncertainty,
as it is unclear where the exact location of the “fixed”
temperature end of the wires is. The uncertainties can be strongly
reduced by further control over the sample geometry. The DC slope
method does not rely on knowledge of L to extract
thermal conductivity, and the DC bridge method treats the equivalent
of L as a fit parameter, incorporating error into
the fit model.
As the incident current decreases, the average
temperature will
decrease across all electron beam modulation frequencies, until the
pan class="Chemical">current heats the wire below the error of the temperature measurement
precision, giving a flat line. Supplementary Figure 8 explores this effect by focusing the electron beam off-center
of the nanowire, thereby depositing less power into the nanowire.
We see consistent thermal conductivities measured at different deposited
powers.
The benefit of the AC method is that the value of the
electron
beam heat flux, Q̇, does not need to be known
in order to extract thermal conductivity, unlike in the DC methods,
where these parameters are 100% correlated. As Q̇ is determined by using a combination of measurement of the electron
beam pan class="Chemical">current and CASINO and Monte Carlo simulations, and can be heavily
influenced by electron beam shape (in the case of large-apertured
electron beams, as discussed above), uncertainties in Q̇ are a significant source of error in the analysis. By using a spectrometer
to average the frequency-dependent optical response in time, we are
summing non-negligible shot noise (from electrons striking the nanowires
and from generation/recombination of carriers in the GaN nanowires)
over a wide electrical bandwidth. We could further shrink the uncertainty
in thermal conductivity in these AC measurements by using a bandpass
filter to isolate a small wavelength range near the bandgap CL emission
and monitor amplitude modulation in this band via lock-in detection during pulsed electron beam excitation, thereby
drastically improving signal-to-noise ratio as the bandwidth over
which noise is summed with lock-in methods is small.
Comparison
of Thermal Conductivities and Methods
The
thermal conductivity of bulk GaN at room temperature reported in the
literature is fairly high at 130–220 W/m·K.[66,67] pan class="Gene">GaN nanowires previously studied with the suspended microchip method
or with photoluminescence have reported thermal conductivity values
of 13–19 W/m·K[29] for smaller
diameter nanowires and <80 W/m·K[58] for wires of similar diameter to those we studied and are therefore
in agreement with our results of 19–68 W/m·K found in
this study. Several studies attributed the deviation from the bulk
values to decreased phonon mean free path due to large mass-difference
scattering from Si impurities.[29,68,69] One study found additionally that boundary scattering, phonon confinement,
and the change in nonequilibrium phonon distribution significantly
contributed to the decrease in thermal conductivity in nanowires when
compared to bulk.[69] Si impurities are present
in our nanowires, as the nanowires were intentionally doped with Si
during growth (see Methods). The nanoscale
thermometry presented here provides avenues for detailed studies of
heat flow in confined geometries.
The data shown in Figure d are from the same
wires as the data shown in Figure c, allowing for direct comparison between the DC slope
and AC methods. The extracted thermal conductivities are within error
of each other for wires A and B, but not for wire C, although all
measurements on all wires show a lower-than-bulk thermal conductivity.
The thermal profile for wire C in Figure b should show sections with different slope
if there was a deviation in thermal conductivity along its length,
but we do not see this to a significant extent. As dispan class="Chemical">cussed previously,
the wavelength shifts due to doping must be subtracted from the wavelength
shifts due to temperature to derive accurate results. If wire C were
not completely round as it appears to be in the SEM, our estimate
of the cross-sectional area could be inaccurate, leading to lower
than expected thermal conductivities with the DC slope method. We
did correct for drift in our frequency-dependent measurements, but
it is possible that because the doping variation with position is
significant at the end of this nanowire, small drifting of the beam
caused a much larger effect on the bandgap shift than with more uniformly
doped wires A and B. Additionally, a small chip is present at the
end of wire C, and so a small amount of drift near the edge of this
chip could lead to slightly varying power deposition due to altered
electron beam backscatter/transmission/absorption ratios during the
measurement, altering results.
Both the DC and AC methods have
their advantages and disadvantages.
The DC methods allow for easier examination of the heat-pan class="Chemical">sinking quality
at the boundaries of the materials during data collection and have
higher spatial resolution than the AC method (in our microscope).
Additionally, drift during measurements is easier to spot and correct
for with the DC method. The DC method is also more sensitive to variations
in doping in the wire. With extra large temperature rises, as we saw
in the wire used in the DC bridge method, the doping variations played
less of a role in determining thermal conductivity, as temperature
rises caused much larger bandgap shifts than doping variations did.
In the DC slope method with smaller temperature rises, we had to correct
for variations in the bandgap emission due to doping (on the order
of 1 nm) in the nanowire by extracting bandgap variations along the
wire found with low electron beam current. On the other hand, knowledge
of the thermal contact resistance was not necessary in the DC slope
method, whereas it was critical in the DC bridge method. In fitting
the DC data, thermal conductivity is 100% correlated with both electron
beam heat flux and wire cross-sectional area, both of which had the
largest sources of uncertainties.
The AC method, as it relies
on the electron beam being focused
on a pan class="Chemical">single point on the wire, can be collected much faster. In our
particular SEM electron column, spatial resolution is worse in the
AC method due to changes in the electron beam optics necessary to
place the beam into conjugate mode with the focus of the beam between
the two blanking plates.[64] Alternative
microscope column designs with optimized beam crossover, which are
available commercially, will resolve this issue. In all cases, we
assume in our models that thermal conductivity (and wire cross-sectional
area) is constant along the wire and not affected by doping; however,
it has been shown that thermal conductivity of GaN can decrease with
increased doping concentration[68] (see Figure S6 for discussion). Accuracy could suffer
if thermal conductivity is not uniform throughout the wire, as the
mathematical model does not account for this (see Figures S6). In fitting the data, thermal conductivity can
be extracted accurately without knowledge of both electron beam heat
flux and wire cross-sectional area in the AC method, in contrast to
DC methods. The AC method may also suffer less from carrier accumulation
in the bandgap, such as blue-shifting caused by the Burnstein–Moss
effect.[70,71] We did not see such an effect in our wires,
but it could play more of a role in other materials. In all cases,
we assumed heat capacity and density were constant with temperature.
The major drawback of the thermometry method presented here is
the strong influence of the localized doping heterogeneity on the
bandgap energy. The doping from Si impurities introduced intentionally
during growth of the nanowires created ∼1 nm variations in
the peak bandgap wavelength, which corresponds to a ∼50 K equivalent
temperature variation. Doping is static (impurities cannot be added
or moved), and therefore its influence on the bandgap energy can be
separated from temperature changes in a straightforward manner; if
the sample temperature is known (no external heating is present and
a low electron beam pan class="Chemical">current is used to avoid heating), any variation
in peak bandgap in the sample can be attributed to doping. Maximizing
accuracy of temperature calibration curves for a given sample can
be done with high-resolution low-current mapping of the bandgap shifts
of the entire sample at different temperatures of the heating/cooling
calibration stage. This allows for definitive separation of the doping
background from the temperature shift. In this study, we have measured
the calibration curve for a small region of uniform doping on a nanowire
and assumed doping would shift the curve offset but not the slope,
which was observed to be a reasonable assumption previously.[42]Figure g shows the bandgap variation due to doping in wires A, B,
and C (the CL yield from the wire in Figures and 3a was too low
for our spectrometer to detect without a current large enough to heat
the nanowire).
A modification of the AC method can be used to
measure thermal
conductivity without need for a calibration curve with a few assumptions.
First, a low pan class="Chemical">current scan must be taken to determine the peak bandgap
without heating. Next, it can be assumed that the temperature scales
linearly with bandgap shift, which is valid over small temperature
ranges. Finally, the data can be normalized and fit with the nondimensionalized
version of eq given
in the Supporting Information in order
to extract the thermal conductivity. In short, the peak wavelength
data can directly be fit to extract the thermal conductivity instead
of first converting to temperature, eliminating the need for a calibration
curve.
Conclusions
We have presented a
method of cathodoluminescence nanothermometry
for semiconductors along with three different methods for using this
thermometry method to measure thermal conductivity of pan class="Gene">GaN (or other
semiconductor) nanowires. CL thermometry can be used with very low
currents in order to measure temperatures in situ without heating the sample, or it can be used with high currents
to act additionally as a delta-function-like heat source to study
thermal transport. We additionally showed that, alongside GaN, both
Si and GaAs exhibit shifts in CL bandgap emission with temperature,
indicating that the temperature mapping and thermal transport measurements
examined here are broadly applicable to other semiconductors and could
find uses in examining integrated circuits in situ to find defects, for example. The thermal conductivity measurement
methods explored here are fairly rapid and have low fabrication requirements.
The existing framework for laser-based pump–probe measurements
of thermal conductivity, like time-domain thermoreflectance, could
easily be translated into the SEM using CL nanothermometry, which
could result in 100× better spatial resolution than these state-of-the-art
methods.[32] Additionally, the tunability
of the penetration depth of electrons (between 10s of nanometers and
microns in SEMs, controlled by the electron energy) creates possibilities
for heat transport studies in nanolayers currently inaccessible in
photon-based studies. Because of the high resolution, high scan speeds,
and high level of control an SEM offers, CL nanothermometry-based
methods offer an enticing framework in which to study phonon dynamics,
ballistic transport, and near-field heat transport phenomena hitherto
unmeasurable.
Methods/Experimental
Nanowire
Fabrication
The nanowire fabrication process
using a top-down approach combining displacement Talbot lithography
and selective area sublimation has been detailed previously.[49] A pan class="Gene">GaN layer was grown by metalorganic-vapor-phase
epitaxy on c-plane (0001) sapphire substrates starting
with a 2 μm undoped GaN layer followed by 5 μm of Si-doped
(5 × 1018 cm–3) GaN. A 60 nm thick
SiN deposited
by plasma-enhanced chemical vapor deposition on top of the GaN layer
was patterned with displacement Talbot lithography to get a hexagonal
array of nanodisks (diameter of 515 nm) with a pitch of 1.5 μm.[72] The sample then underwent selective area sublimation
between 900 and 920 °C in a molecular beam epitaxy chamber for
8 h in order to define the 7 μm nanowires. The SiN mask was etched using
a HF-based solution. Some wires shown in this article are slightly
shorter than 7 μm due to breaking when separated from the growth
substrate or variations in the sublimation rate due to the temperature
gradient between the center and the edge of the wafer.
Authors: Aditya Sood; Feng Xiong; Shunda Chen; Ramez Cheaito; Feifei Lian; Mehdi Asheghi; Yi Cui; Davide Donadio; Kenneth E Goodson; Eric Pop Journal: Nano Lett Date: 2019-03-07 Impact factor: 11.189
Authors: Juan Carlos Idrobo; Andrew R Lupini; Tianli Feng; Raymond R Unocic; Franklin S Walden; Daniel S Gardiner; Tracy C Lovejoy; Niklas Dellby; Sokrates T Pantelides; Ondrej L Krivanek Journal: Phys Rev Lett Date: 2018-03-02 Impact factor: 9.161
Authors: Carlos D S Brites; Patricia P Lima; Nuno J O Silva; Angel Millán; Vitor S Amaral; Fernando Palacio; Luís D Carlos Journal: Nanoscale Date: 2012-07-04 Impact factor: 7.790
Authors: Pierre-Marie Coulon; Benjamin Damilano; Blandine Alloing; Pierre Chausse; Sebastian Walde; Johannes Enslin; Robert Armstrong; Stéphane Vézian; Sylvia Hagedorn; Tim Wernicke; Jean Massies; Jesus Zúñiga-Pérez; Markus Weyers; Michael Kneissl; Philip A Shields Journal: Microsyst Nanoeng Date: 2019-12-02 Impact factor: 7.127