commentary | focus
Harnessing plasmonics for
solar cells
Martin A. Green and Supriya Pillai
Plasmons are free-electron oscillations in a conductor that allow light to be manipulated at the
nanoscale. The ability of plasmons to guide and confine light on subwavelength scales is opening up new
design possibilities for solar cells.
O
ver the past two years, photovoltaics —
the conversion of sunlight into
electricity using solar cells — has
progressed more rapidly than even the most
optimistic forecasts. In 2012, the industry
is poised to attain costs and production
volumes that the International Energy
Agency, even in its 2009 roadmap, did
not anticipate would be reached before
2020. Performance at the large scale has
been impressive. In May 2011 hundreds
of thousands of mainly small, private
photovoltaic systems combined to supply
over 20% of the Germany’s monthly peak
electricity demand, as well as 8% of its
monthly electricity usage1. This example
is a mere glimpse at a future in which
photovoltaics plays a key role in supplying
sustainable energy.
Most commercial photovoltaic cells are
based on silicon wafers, which are reducing in
thickness every year. Wafers measuring just
100 μm thick are expected to be in production
by 20202, although a trade-off must inevitably
be made between minimizing material
usage and achieving adequate strength
for processing and packaging. Interest
continues unabated in even thinner ‘thin-film’
technologies, where the photovoltaic layers
are deposited onto supporting substrates
or superstrates. A key advantage of such
a device is the small amount of material
required, which reduces consumable costs
and increases throughput because of the
reduced deposition time. However, reduced
thickness (and therefore cost) must not come
at the expense of performance. Low cell
efficiencies cause a price penalty that results
from the extra costs associated with installing
larger areas of solar panels. Successful thinfilm technologies must ultimately reach
energy-conversion efficiencies that are at least
roughly similar to mainstream silicon devices.
The average efficiencies of commercial silicon
modules are likely to reach 17–18% by the end
of the decade2.
130
a
b
Nanoparticle
Effective medium
Semiconductor
Scattered light
Semiconductor
Figure 1 | Plasmonic metal nanoparticles as scatterers. a, Incoming light excites confined plasmons in the
particles and is then scattered into the guided modes of the substrate. b, An effective-medium theory
model that captures the key features of the optical processes.
The most fundamental penalty incurred
by reducing wafer thickness is poorer solar
absorption — a disadvantage that can
be mitigated through an approach called
‘light trapping’. In this technique, cells are
designed such that the optical pathlength
through them is much larger than their
thickness. A wavelength-dependent
pathlength enhancement factor is defined
as the ratio of absorption in the material
with light trapping to that for a single pass
of light through the equivalent material
without light trapping. For weakly absorbed
light of unit intensity, the absorption for
a single pass of light is just the volume of
the material multiplied by its absorption
coefficient. For macroscopic devices, the
pathlength enhancement can be as large as
4n2, where n is the refractive index of the cell
material3. For silicon, this corresponds to an
amazing 50-fold enhancement.
In conventional silicon cells, surface
texturing not only reduces reflection but
also increases cell absorption due to light
trapping. Silicon’s high refractive index
means that the escape cone for internal light
is small3, and light scattered internally from
the cone is effectively trapped. Pathlength
enhancements are estimated to be 5–10 for
commercial devices and over 25 for the best
laboratory devices4, but are limited in both
cases by absorption in the rear metal layer.
Although texturing indeed increases the
overall efficiency of a device, it also usually
negatively impacts electronic performance.
Texturing increases not only the surface
area of a device, which improves surface
recombination, but also the total volume
of its junction depletion regions. Texturing
may be infeasible for very thin cells or
incompatible with some thin-film deposition
approaches, including ‘line of sight’ physical
vapour deposition.
Recent reviews5–7 document a surge
of interest in the use of plasmons — freeelectron oscillations in a conductor — to
boost the performance of thin-film cells.
Initial interest arose because plasmons allow
light scattering without the use of texturing 8,9.
Small metal nanoparticles on top of planar
substrates, as shown in Fig. 1a, interact with
incoming light to produce localized surface
plasmons, which scatter the light into the
guided modes of the substrate. The number of
substrate modes decreases with thickness in
a thin sample, leading researchers to question
nature photonics | VOL 6 | MARCH 2012 | www.nature.com/naturephotonics
© 2012 Macmillan Publishers Limited. All rights reserved.
Focus | commentary
whether the same light-trapping limits would
apply as to macroscopic specimens. Initial
results were not encouraging: researchers
predicted that reducing the substrate
thickness would progressively lower the light
trapping efficacy.
Over the past five years, much has been
learned about how to exploit these confined
plasmons effectively. For example, researchers
found that interference between scattered
and incoming light reduces (perhaps counterintuitively) the overall reflection of a device.
Effective-medium theories have proved their
usefulness in the field of metamaterials and
can be used to describe this interference
at least qualitatively 10 (Fig. 1b), although a
number of caveats still apply 11. Introducing
reflective nanoparticles into a dielectric
increases its effective refractive index. Recent
work suggests that aluminium particles
may be more effective than noble metals
for reducing reflection12. This advantage is
attributed to the higher resonant frequency
of aluminium, as particles absorb light at
wavelengths below their resonance frequency.
This led to the suggestion that the rear side
of the cell is the most effective location for
plasmonic scatterers7. Recent work7,13,14 has
clarified the effect of particle shape and
spacer layers for both front and rear locations.
Hemispheres and cylinders are superior to
the spheres shown in Fig. 1a because they
have a larger contact area with the silicon
substrate. Surface plasmon polaritons (SPPs)
have recently been shown to be active in this
contact area13.
SPPs are plasmon modes that propagate
along metal–dielectric interfaces over
distances determined by absorption in
the metal. Using SPPs propagating along
the rear surface of a cell to enhance cell
absorption (Fig. 2a) is also under active
investigation5. These SPPs can be excited at
visible wavelengths, where the magnitude of
the real (negative) component of the metal’s
dielectric constant becomes larger than
the corresponding (positive) value for the
dielectric. In terms of refractive indices, this
corresponds roughly to the imaginary part
of the metal’s index km becoming larger in
magnitude than the real part of the dielectric
(or, in this case, semiconductor) index ns.
Evanescent waves decay in both the
metal and the dielectric, but extend further
into the dielectric by the inverse ratio of
respective dielectric constants, which is
roughly (km/ns)2. At a wavelength of 800 nm,
evanescent fields extend around 17 nm into
silver and 38 nm into crystalline silicon,
where a long decay length is desirable
because it increases absorption there5.
A common concern5,6 has been whether
metal absorption might override the
benefits of semiconductor absorption.
a
b
Evanescent
wave
Substrate
mode
Textured surface
High-index
layers
Low-index layer
SPP
Metal reflector
Metal reflector
Figure 2 | Trapping light using evanescent waves. a, Features on the rear layer of a solar cell can not
only scatter light into substrate modes but also excite SPPs propagating along the rear surface reflector.
b, Evanescent states at the interface of a low-index medium embedded in high-index material can
significantly boost absorption in a thin low-index layer.
This problem can be explored by
examining the reduction of plasmon
propagation distance caused by absorption
in the semiconductor. The fractional
semiconductor absorption found in this way
is given by fs = kskm3/(ns3nm + kskm3), where ns
(nm) and ks (km) are the real and imaginary
parts of the semiconductor (metal) indices.
Only when ks > ns3nm/km3 will half of the
propagating energy be absorbed in the
semiconductor. Metals with a small value
of nm/km3 maximize desirable absorption in
the semiconductor. The fraction of incident
perpendicular light that is reflected from
the surface of a metal in vacuum, R, is given
approximately by 1 − (4nm/km2). R therefore
provides a simple screening parameter
because km is relatively independent of the
metal at visible wavelengths.
The optical constants of metal candidates
are often obtained from data in Palik’s
handbook15, or from earlier data derived by
Johnson and Christy 16. For silver, however,
there are large differences between these
data. Nash and Sambles17 rejected both
data sets because they were derived from
silver samples exposed to air, and instead
tabulated an alternative ‘best set of values’
in the range of 400–900 nm. These give
a silver vacuum reflectivity of 98.9% at
800 nm, whereas values from Palik and
Johnson and Christy give 98.0% and 99.5%,
respectively. Although these values are all
relatively similar, small differences magnify
to give a large difference in the calculated
SPP light-trapping effectiveness. Handbook
R values for gold, copper, aluminium and
molybdenum (used in chalcogenide cells) at
800 nm are 97.4%, 96.3%, 86.8% and 55.6%,
respectively, thus clearly identifying silver as
the material of choice. Nash and Sambles17
measured nm = 0.087 and km = 5.48 at
800 nm, which suggests that SPP light
trapping is effective only for absorption
coefficients of more than 4,000 cm–1
for inorganic semiconductors. Organic
semiconductors have smaller values of ns,
which makes organic cells more promising
candidates than inorganic cells.
As explained by Schiff 18, these SPP modes
represent photon-accessible states that are
in addition to those involving propagation
across the substrate. Photon coupling
between both sets of states would potentially
allow macroscopic light-trapping limits
to be exceeded. Schiff calculated that the
limits, neglecting metal absorption, could
be increased to 4n2 + nλ/W, where W is the
device thickness and λ is the wavelength of
light. Rear gratings or rear-surface features
such as those shown in Fig. 2a not only
scatter light into substrate propagation
modes, but also provide the required
coupling. As noted above, metal absorption
largely negates these gains18, although there
may be scope for more optimal trade-offs5.
Another way of describing potential
gains in this geometry is through the
local density of optical states19 ρ(r, ω) as a
function of position, r, and radial frequency,
ω, which can be determined from the
local density of electromagnetic energy
U(r, ω) = ρ(r, ω)hω/(exp(hω/kT) − 1),
where hω and kT are the photon energy
and thermal energy, respectively. In a
dielectric near a metal interface, the local
density of optical states increases due to
the presence of additional evanescent
modes, with ρ(r, ω) peaking at the SPP
resonant frequency 19. Light trapping can
be significantly improved by employing
the geometry shown in Fig. 2b20, as the
evanescent states at the interface between
dielectrics of different refractive indices
can enhance the local density of optical
states. Trapping in a thin low-index (nL)
layer immersed in high-index (nH) material
boosts the macroscopic limit of 4nL2 by
a further factor of (2nH/nL + nH5/nL5)/3,
which equals 12 for nH/nL = 2. Yu et al.
nature photonics | VOL 6 | MARCH 2012 | www.nature.com/naturephotonics
© 2012 Macmillan Publishers Limited. All rights reserved.
131
commentary | focus
a
b
Nanoparticle
ITO (55 nm)
Ag (20 nm)
a-Si (15 nm)
Ag (50 nm)
Semiconductor
junction
Figure 3 | Plasmonic solar cell approaches. a, Metal nanoparticles embedded in the absorber at a cell
junction enhance the electric field — and therefore light absorption — around their periphery. b, Unit
cell of a recently proposed metamaterial–plasmonic cell consisting of, from top to bottom, an indium
tin oxide (ITO) antireflection coating (55 nm), a silver top contact (20 nm) in an ‘over-full’ conducting
chequer-board pattern, a thin layer of amorphous silicon (15 nm) as the active cell material and a rear
silver reflector (50 nm).
subsequently more simply derived this
formula as well as a similar expression
for embedded nanospheres21, showing
smaller boosts in this case. Conversely,
light trapping is suppressed for high-index
media immersed in low-index materials,
which emphasizes the importance of
local environments in determining
optical performance for thin high-index
layers. This effect is well-documented for
photoluminescence22, which is closely
related to absorption through fundamental
reciprocity relationships23.
Performance can also be enhanced by
positioning the metal nanoparticles to
maximize absorption in the most active
cell regions6,24 (Fig. 3a). The downside of
this technique is that metal–semiconductor
interfaces are regions of detrimental
electronic activity. The introduction of
intervening thin insulator layers may
overcome this effect 24, albeit at the expense
of diluting the associated field strength.
Embedded nanoparticles might also be
beneficial for promoting processes such as
upconversion, which rise nonlinearly with
increasing field strength.
Much progress has been made in
understanding the photovoltaic potential of
plasmonics, and further work may uncover
even more substantial gains. Figure 3b
shows the structure of a recently proposed
metamaterial–plasmonic solar cell25 that is
simulated to give good performance with
an extremely thin 15 nm amorphous-silicon
active layer. The design of this cell was
based on effective-medium theory analysis
and then confirmed by full solutions to
Maxwell’s equations. The structure involves
132
a 20-nm-thick top silver metal contact
in an ‘over-full’ chequer-board pattern of
subwavelength dimensions, which obscures
54% of the cell. The underlying 15-nm-thick
amorphous silicon layer has a 50-nm-thick
silver rear reflector. The top surface is
covered in a 55-nm-thick indium tin oxide
antireflection coating, resulting in a total
device thickness of only 140 nm.
The possible plasmonic activity in this
structure is complex. The structure relies on
extraordinary optical transmission through
the top metallization holes26. Periodicity in
the top contact geometry provides phase
matching that allows SPP excitation, which
contributes to both light transmission
and scattering. The top silver layer is
partly transmissive, which enables SPP
stimulation on both of its sides. Although
SPP stimulation on both sides is generally
detrimental to extraordinary optical
transmission, researchers were nevertheless
able to measure26 reasonable transmission
through holes similar to the subwavelength
hole arrays of ref. 25, albeit at lower levels
than in simulations. The amorphous silicon
layer is so thin that coupling also occurs
between the front and rear silver layers,
leading to SPP excitation in the rear silver
layer. Simulations suggest that this structure
would absorb sufficient photons from the
standard solar spectrum to give a current
output of 19.7 mA cm–2, compared with
16.8 mA cm–2 from today’s highest-efficiency
amorphous-silicon cell27. However, this
simulation used Johnson and Christy
optical parameters, and therefore possibly
underestimates silver’s absorption losses by
up to a factor of four.
Full solutions to Maxwell’s equations will
be crucial in unravelling the performance
of increasingly complex geometries such
as the one described above, and effectivemedium theory approximations may have
a role in identifying structures that warrant
detailed assessment. Localized plasmons
have already demonstrated their potential
to boost the performance of solar cells
for cases when traditional texturing may
not be viable. For propagating plasmons,
parasitic optical absorption in the metallic
structure and strong optical absorption near
high-recombination metal–semiconductor
interfaces both remain significant challenges.
Nonetheless, plasmonics is opening up a
new optical world at the subwavelength
scale that is largely unexplored. High-index,
non-absorbing dielectrics and the emerging
field of metamaterial plasmonics may
both offer new photovoltaic possibilities.
The low cell thickness that is possible with
plasmonics may not only deliver anticipated
material savings but also ultimately allow
the successful implementation of advanced
high-performance concepts, such as hotcarrier cells28.
❒
Martin A. Green and Supriya Pillai are at the ARC
Photovoltaics Centre of Excellence, University of New
South Wales, Sydney, New South Wales
2052, Australia.
e-mail: m.green@unsw.edu.au
References
1.www.transparency.eex.com/en/
2.www.itrpv.net/doc/roadmap_itrpv_2011_brochure_web.pdf
3. Yablonovitch, E. J. Opt. Soc. Am. 72, 899–907 (1982).
4. Green, M. A. Prog. Photovoltaics 17, 183–189 (2009).
5. Atwater, H. & Polman, A. Nature Mater. 9, 205–213 (2010).
6. Mallick, S. B., Sergeant, N. P., Agrawal, M., Lee, J.‑Y. &
Peumans, P. MRS Bull. 36, 453–460 (2011).
7. Catchpole, K. R. et al. MRS Bull. 36, 461–467 (2011).
8. Stuart, H. R. & Hall, D. G. Appl. Phys. Lett. 69, 2327–2329 (1996).
9. Pillai, S. et al. J. Appl. Phys. 101, 093105 (2007).
10.Akimov, Y. A., Ostrikov, K. & Li, E. P. Plasmonics 4,
107–113 (2009).
11.Simovski, C. R. J. Opt. 13, 013001 (2011).
12.Akimov, Y. A. & Koh, W. S. Nanotechnology 21, 235201 (2010).
13.Beck, F. J., Mokkapati, S. & Catchpole, K. R. Opt. Express 19,
25230–25241 (2011).
14.Pillai, S., Beck, F. J., Catchpole, K. R., Ouyang, Z. & Green, M. A.
J. Appl. Phys. 109, 073105 (2011).
15.Palik, E. D. (ed.) Handbook of Optical Constants of Solids
(Academic, 1985).
16.Johnson, P. B. & Christy, R. W. Phys. Rev. B 6, 4370–4379 (1972).
17.Nash, D. J. & Sambles, J. R. J. Mod. Opt. 43, 81–91 (1996).
18.Schiff, E. A. J. Appl. Phys. 110, 104501 (2011).
19.Joulain, K., Carminati, R., Mulet, J.‑P. & Greffet, J.‑J. Phys. Rev. B
68, 245405 (2003).
20.Green, M. A. Prog. Photovoltaics 19, 473–477 (2011).
21.Yu, Z., Raman, A. & Fan, S. Proc. Natl Acad. Sci. USA 107,
17491–17496 (2010).
22.Yablonovitch, E., Gmitter, T. J. & Bhat, R. Phys. Rev. Lett. 61,
2546–2549 (1988).
23.Rau, U. Phys. Rev. B 76, 085303 (2007).
24.Lee, J.‑Y. & Peumans, P. Opt. Express 18, 10078–10087 (2010).
25.Wang, Y. et al. Nano Lett. 12, 440–445 (2012).
26.Braun, J., Gompf, B., Weiss, T., Giessen, H. & Dressel, M.
Phys. Rev. B 84, 155419 (2011).
27.Green, M. A., Emery, K., Hishikawa, Y., Warta, W. &
Dunlop, E. D. Prog. Photovoltaics 20, 12–20 (2012).
28.Aliberti, P. et al. J. Appl. Phys. 108, 094507 (2010).
nature photonics | VOL 6 | MARCH 2012 | www.nature.com/naturephotonics
© 2012 Macmillan Publishers Limited. All rights reserved.