Carrier motion in as-spun and annealed P3HT:PCBM blends revealed by ultrafast optical electric field probing and Monte Carlo simulations

Abstract

Charge transport dynamics in solar cell devices based on as-spun and annealed P3HT:PCBM films are compared using ultrafast time-resolved optical probing of the electric field by means of field-induced second harmonic generation. The results show that charge carriers drift about twice as far during the first 3 ns after photogeneration in a device where the active layer has been thermally annealed. The carrier dynamics were modelled using Monte-Carlo simulations and good agreement between experimental and simulated drift dynamics was obtained using identical model parameters for both cells, but with different average PCBM and polymer domain sizes. The calculations suggest that small domain sizes in as-spun samples limit the carrier separation distance disabling their escape from geminate recombination.

Full text

2686 |Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 This journal is ©the Owner Societies 2014
Cite this: Phys. Chem. Chem. Phys.,
2014, 16,2686
Carrier motion in as-spun and annealed
P3HT:PCBM blends revealed by ultrafast optical
electric field probing and Monte Carlo simulations
Vytautas Abramavic
ˇius,*
ab
Dimali Amarasinghe Vithanage,
c
Andrius Deviz
ˇis,
a
Yingyot Infahsaeng,
c
Annalisa Bruno,
d
Samuel Foster,
d
Panagiotis E. Keivanidis,
e
Darius Abramavic
ˇius,
b
Jenny Nelson,
d
Arkady Yartsev,
c
Villy Sundstro
¨m
c
and
Vidmantas Gulbinas
a
Charge transport dynamics in solar cell devices based on as-spun and annealed P3HT:PCBM films are
compared using ultrafast time-resolved optical probing of the electric field by means of field-induced
second harmonic generation. The results show that charge carriers drift about twice as far during the first
3 ns after photogeneration in a device where the active layer has been thermally annealed. The carrier
dynamics were modelled using Monte-Carlo simulations and good agreement between experimental and
simulated drift dynamics was obtained using identical model parameters for both cells, but with different
average PCBM and polymer domain sizes. The calculations suggest that small domain sizes in as-spun
samples limit the carrier separation distance disabling their escape from geminate recombination.
1. Introduction
Diminishing sources of fossil fuels and the need to meet rising
global demands for carbon-free energy have led to renewable
sources being explored as replacements. Conjugated polymers
have been investigated as alternatives to solar cells based on
inorganic semiconductors
1
due to their light weight, flexibility,
abundance of material, low material usage and manufacturing
costs. The invention of the bulk heterojunction structure (BHJ)
using a donor and acceptor homogeneously mixed to produce the
active material
2
has aided the increase in solar cell efficiency,
which is presently 9.2% for the best reported cells.
3
To improve
device efficiency, the charge dynamics have also been investigated
and three key stages in the charge separation pathway have been
identified – charge generation,
4
transport
5
and recombination.
6
Excitons are generated when light within the absorption
spectrum of the material impinges on the devices. These excitons
very rapidly
6
separate into positive and negative charges forming
Coulombically bound electron–hole pairs (or charge transfer
states (CT)). In order to separate further, the charges have to
overcome the Columbic attraction and form mobile charges
which can move towards the electrodes through a combination
of diffusion and drift.
7
The collection of the separated charges
results in completion of the circuit and current produced by
the solar cell.
Here we study the polymer:fullerene combination poly(3-
hexylthiophene) (P3HT) and [6,6]-phenyl-C61butyric acid
methyl ester (PCBM). The method of processing P3HT:PCBM
devicesisknowntoimpacttheactive layer morphology and, as a
result, the efficiency of devices, and has therefore been extensively
studied. Several factors have been investigated with the aim
of improving device efficiency, such as the effect of solvent,
morphology, film thickness and processing conditions.
8–17
Annealing was shown to have a great impact on the conversion
efficiency of P3HT:PCBM solar cells, quite different from most
other polymer:fullerene blends. The carrier dynamics of
annealed and as-spun P3HT:PCBM films have been studied
using several techniques aiming at investigating differences in
mobility,
5,15
morphology,
14–17
EQE
14
and I–V characteristics.
5
Annealing to a high temperature changes the morphology
and enhances the hole mobility,
5,9
resulting in it being only an order
of magnitude below the electron mobility.
5
A similar effect was
achieved with slow solvent evaporation.
18
Using microsecond time
scale techniques, a large spread in mobilities and their differences
in as-spun and annealed samples have been reported.
5,15,19
The
measurements show that the two different processing methods
drastically affect the mobility and charge separation time scales.
Morphological studies have shown that high temperature
a
Center for Physical Sciences and Technology, Savanoriu 231, LT-02300 Vilnius,
Lithuania
b
Department of Theoretical Physics, Vilnius University, Sauletekio 9-III,
LT-10222 Vilnius, Lithuania. E-mail: Vytautas.Abramavicius@ff.vu.lt
c
Chemical Physics, Lund University, Box 124, 221 00 Lund, Sweden
d
Imperial College London, South Kensington Campus, London SW7 2AZ, UK
e
Center for Nano Science and Technology@PoliMi, Istituto Italiano di Tecnologia,
Via Giovanni Pascoli, 70/3, 20133 Milano, Italy
Received 31st October 2013,
Accepted 5th December 2013
DOI: 10.1039/c3cp54605e
www.rsc.org/pccp
PCCP
PAPER
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online
View Journal
| View Issue

This journal is ©the Owner Societies 2014 Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 | 2687
results in phase separation due to crystallization of the
polymer
5,15,16,20
and formation of large PCBM clusters.
12,14–17
There is a consensus that thermal annealing results in improved
device efficiency due to enhanced phase segregation, which
consequently leads to increased charge separation efficiency,
21,22
improved hole conductivity and formation of optimized charge
transport pathways
9,15
and consequently reduced bimolecular
recombination.
23
The mechanism through which the thermal annealing
process enables higher charge carrier mobilities is now fairly
well understood. Annealing induced crystallisation of the polymer
results in larger domains (thicker lamellae) of the pure polymer
and at the same time expels fullerene molecules out of the
crystallising polymer, thereby making more fullerene available
to build a robust electron transport network.
20,24–26
It is clear from
such studies that the improvement in charge collection (reflected
through photocurrent quantum efficiency) is associated with the
growth in pure polymer and fullerene domains and resulting
improvement in charge carrier mobility relative to the recombina-
tion coefficient.
5,9
In this paper, we aim at unveiling how morphology affects
charge transport by investigating charge mobility and charge
separation at earlier timescales using electric field-induced
second harmonic generation (TREFISH)
7,27,28
and MC simula-
tions. We find the morphology to influence the mobility and
carrier separation on the ps to ns time scale. MC simulations
show that the different carrier drift kinetics in as-spun and
annealed blends may be explained by more extensive material
segregation, leading to larger P3HT and PCBM domains in
annealed material, enabling fast separation of carriers at larger
distances and preventing their geminate recombination.
2. Experiment
The experimental setup and theory have been previously
described,
7,27,28
so only a brief account is given here. TREF ISH
is a pump–probe technique, employing a femtosecond laser pulse
to excite the sample devices and generate charges, and a probe
pulse that generates the SHG signal probing the dynamics of
the charges. An applied electric field breaks the symmetry of the
material, allowing to generate the second harmonic signal of
the probe pulse. The intensity and time dependence of the
second harmonic signal monitors the electric field dynamics in
the sample. The excitation pulse (400 nm, 36 nJ per pulse) was
obtained by frequency doubling the fundamental of the Ti:Sa
laser at 800 nm; a photon density of B10
12
photons per cm
2
per
pulse for the sample was used, which is below the onset of strong
second order (non-geminate) recombination. The probing wave-
length was obtained using an optical parametric amplifier
(TOPAS) at 1200 nm, the second harmonic of which was within
the sensitivity of the photomultiplier detector. The sample device
was made using a PEDOT:PSS/ITO anode and an aluminium (Al)
cathode. The PEDOT:PSS was spun to form a 40–60 nm film and
the total device had an overall thickness of B115 nm. The sample
cells were all prepared in a clean room environment.
3. Monte-Carlo simulation model
The simulation model has been described in ref. 7. Briefly, charge
carriermotionintheP3HT:PCBMblendwasmodelledbyassuming
a cubic lattice, characterized by a lattice constant ain all three
dimensions. The lattice is divided into the donor part, where only
the hole is allowed to reside and the acceptor part for the electron.
The acceptor sites are defined by filling the lattice volume with
ellipsoids of acceptor material (see Fig. 2) with typical average
volume, which is later on used as a fitting parameter. The ellipsoids
have arbitrary proportions and they are placed in arbitrary positions
in the lattice and they overlap each other, thus mimicking the
distribution of PCBM in the actual blend. Next, the remaining space
in the lattice is filled with donor sites, which are used to create
arbitrarily oriented and folded chains representing the polymer. The
length of a chain is chosen randomly from the interval [L3, L+3],
where Lis the average length of chains. It should be noted, that
such a blend model apparently cannot reproduce the real blend
morphology, particularly of the annealed blend where a lamellar
structure is suggested to be formed. The results of the calculation
should rather be seen as a qualitative representation of morphology
to rationalize the observed carrier dynamics.
The electron and hole dynamics are controlled by site energy
properties. In the presence of an external electric field the energy of
an electron (hole) in the lattice consists of three parts: (1) the internal
site self-energy E
r
, which is assumed to be a random Gaussian value;
(2) the energy due to the constant external electric field F, and
(3) the energy due to the Coulomb interaction between charges
of opposite sign E
C
. The electron (hole) energy thus equals to:
E
f
(r)=E
r
8(Fr)+E
C
. (1)
The site self-energy is distributed according to a modified
Gaussian distribution, which is defined as a weighted sum of a
normal Gaussian distribution with addition of longer exponential
tails. The energy of the external electric field was accounted
for by projecting the site position to the electric field direction.
The electrostatic interaction energy is given by the shifted
Coulomb potential
EC¼ q
4pee0
1
reh þba (2)
Here qis the electron charge, r
eh
is the distance between the
electron and the hole, eis the mean permittivity of the material, a
is the lattice constant and bis a positive dimensionless parameter,
which accounts for deviation of the Coulomb potential from the
point charge approximation at short distances and sets the
appropriate initial electron–hole interaction energy.
Both types of charges perform hopping in their respective
domains of the lattice. The hopping is simulated using the
Monte-Carlo algorithm as follows. As the initial configuration
the hole and electron are placed on neighbouring sites in the
interfacial region of the donor and acceptor domains. Only the
nearest neighbour sites are taken into account for the hopping
event. A charge can hop into one of six surrounding sites when
it is far from the interface while hopping possibilities are fewer
in the interfacial region. The hopping rates n
mn
for both the
Paper PCCP
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online

2688 |Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 This journal is ©the Owner Societies 201 4
electron and the hole are calculated using the Miller–Abrahams
formula:
29
nmn ¼n0exp 2grmn
ðÞ
exp EnEm
kT

;En4Em
1;EnEm
8
<
:
;(3)
where gis a parameter which characterizes the inverse localiza-
tion length of a charge density, r
mn
is the distance between the
origin site mand the target site n,E
m
and E
n
are their energies
respectively. In the acceptor domain the hopping rate n
0
n
A
is
constant, while in the donor part we assume the value n
0
n
D1
for hopping to a target site located in a straight part of the same
polymer chain as the origin site, n
0
n
D2
for hopping to a target
site located on a folding point (the point where the orientation
of the polymer chain changes) of the same polymer as the
origin site and n
0
n
D3
for hopping to a target site located on a
different polymer chain.
It is assumed that a hole is less likely to hop to a site located
on another polymer chain, thus the corresponding hopping
rate prefactor n
D3
is smaller than both n
D1
and n
D2
. We also
assume that a hole avoids folding points where holes move
slower than in straight sections of the polymer chain, thus
n
D2
on
D1
. It should be noted that a simple isotropic medium
model was unable to reproduce the carrier drift kinetics during
initial tens of ps therefore this more complex model, previously
suggested to simulate carrier motion in the pure polymer,
28
was used.
When all rates of possible hopping events (including holes
and electrons) have been evaluated, the rates are being translated
into hopping probabilities according to:
pmn ¼nmn
P
k
nk
;(4)
where the summation is performed over all calculated rates of
both the hole and the electron. These probabilities are then
used to determine the destination site nfor either the hole or
the electron, chosen by a linearly distributed random number.
The charge configuration is then switched to the one that has
been determined and the rates of the next hopping events
are recalculated.
For the simulation a 100 400 400 lattice was used. This
lattice simulates the actual structure of the blend, motivating
that no cyclic boundary conditions are introduced. Initially,
charges were created at a random location at the interface
between the donor and the acceptor regions and due to the
external electric field they drifted apart in opposite directions.
While charges moved through the lattice, the distance between
them projected in the direction of the external electric field F,
d
k
(t) was recorded and the result was averaged over 5000
realizations.
Only one electron–hole pair was present in the lattice at a
time, thus the model did not account for the nongeminate
charge carrier recombination. The geminate recombination
was also not accounted for assuming it to be much slower than
the examined time domain.
4. Experimental results
Fig. 1 shows the carrier drift dynamics in as-spun and annealed
samples for various applied voltages, calculated by the proce-
dure described in ref. 19 from the experimentally measured
TREFISH kinetics (not shown). Briefly, the electric field kinetics
was reconstructed from the EFISH kinetics by using steady state
EFISH dependence on the electric field strength. Next we
assume that the electric field drop is proportional to the carrier
drift distance and obtain the drift distance kinetics by normal-
izing the time-resolved field drop to the total field drop at long
delay time when all carriers are extracted and, thus, their
average drift distance equals to the half of the film thickness.
The drift distances presented in Fig. 1 are averaged over
electrons and holes and rapidly increase on the tens of ps time
scale in both samples. At long times (>200 ps) the increase
rate gradually slows down to reach a separation distance of
15–30 nm (depending on film treatment) at 2.5 ns. The drift
distances are approximately proportional to the internal
electric field, suggesting that the initial carrier mobility is
independent of the electric field strength. Qualitatively, similar
drift dynamics has been observed for neat polymers
28
and
Fig. 1 (a) Experimental (symbols) and simulated (lines) charge drift
dynamics in the as-spun (a) and annealed (b) samples at various electric
fields strengths.
PCCP Paper
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online

This journal is ©the Owner Societies 2014 Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 | 2689
attributed to carrier relaxation within a distributed density of
states. The drift distances in the as-spun sample are about half
of those in the annealed sample at the same applied voltages.
The electron and the hole drift in opposite directions by
about 2.5 nm during the initial 10 ps at 6.7 10
5
Vcm
1
electric field in the annealed sample. Thus, the electron–hole
separation distance along the electric field is about 5 nm. This
separation distance is around half as large in the as spun
sample as in the annealed sample and is approximately propor-
tional to the applied field.
5. MC calculation results
Monte Carlo simulations by the procedure described above
have been performed to model the carrier drift dynamics and
to gain insight into the microscopic properties responsible for
the observed differences in drift dynamics of annealed and
as-spun material. The modelling of the hole motion dynamics
accounts for the hole relaxation within the density of states
(DOS), different hole hopping rates within a conjugated segment
(n
D1
), between segments (n
D2
) and between polymer chains (n
D3
).
The electron motion is simpler – the model accounts for the
electron relaxation within the DOS and electron motion inside
PCBM domains is characterised by a single electron hopping rate
prefactor, n
A
. Both electron and hole motions are also affected
by the domain structure of the blend; reaching the domain
boundaries carriers are forced to search for alternative pathways
to continue their motions – this process results in a domain-size
dependence of carrier mobility. The drift kinetics at different
voltages were simulated with the same model parameters, only
varying the internal field strength.
Carrier drift kinetics in as-spun and annealed samples have
been modelled by using exactly the same motion parameters
except for polymer and PCBM domain sizes. The best agree-
ment was obtained with an average acceptor domain diameter
of 7.5 nm for the as-spun sample and 33 nm for the annealed
sample. As a result of fullerene aggregation the polymer domain
dimensions were accordingly larger for annealed samples as
well, but because of nonregular shapes their quantitative char-
acterization, is more difficult. Fig. 2 illustrates the corresponding
material morphologies and Fig. 1 shows the simulated carrier
drift dynamics. The quite good agreement with experimental
results obtained for all curves with only one free variable, the
domain size, validates the simulation results. The obtained
domain dimensions of the annealed samples are somewhat
larger than the B10 nm domains estimated in similar samples
from experimental results.
30
On the other hand, quite similar
domain sizes of 10 to 30 nm were estimated by MC modelling of
carrier recombination in a P3HT:PCBM blend.
23
The MC simula-
tions do not perfectly reproduce the carrier drift kinetics in annealed
samples at high applied electric fields (6.7 10
5
Vcm
1
)attimes
longer than 1 ns. This is not very surprising taking into account the
relatively simple blend structure used in calculations.
We proceed to infer effective charge carrier mobilities from
the data for separation as a function of time. Note that these are
not mobilities as usually defined, describing drift of relaxed
populations of charges in the steady state, but instantaneous
mobilities describing the instantaneous separation velocity of
unrelaxed charge carrier populations. Since the experimental
data gives us information on the sum of electron and hole drift
distances, the actual electron and hole mobilities remain
undisclosed, the ratio between electron and hole hopping rates
being a free parameter. We have chosen the electron hopping
rate on the basis of additional available information on the
ultrafast time-resolved electron mobility and on the basis of the
best agreement between experimental and calculated carrier
drift kinetics. By means of time-resolved microwave conductivity,
Savenije et al.
31
obtained the electron mobility inside PCBM
nanocrystals of 8 10
2
cm
2
V
1
s
1
and a similar mobility of
about 0.1 cm
2
V
1
s
1
was also obtained on a subpicosecond-
several ps time-scale in PCBM film by dynamic Stark effect
measurements.
32
Thus, we have chosen an electron hopping
rate prefactor n
A
to give an electron mobility of 0.1 cm
2
V
1
s
1
at 0.3 ps, while its subsequent evolution was obtained from the
best fitting with experimental data. Similar information on the
initial hole mobility in P3HT is not available and therefore it
was obtained from the modelling of the carrier drift kinetics.
The best agreement was obtained with about ten times lower
hole mobility than that of electrons. The simulation parameters
used to obtain the best agreement between calculated and
measured drift kinetics (see Fig. 1) are presented in Table 1.
A lower initial hole mobility in comparison with the electron
mobility was also concluded for a polyfluorene/fullerene blend.
33
On the other hand, mobilities obtained from time resolved THz
measurements on another polyfluorene low-bandgap polymer/
fullerene blend (APFO3/PCBM) show that picosecond time scale
hole mobility is higher than the electron mobility by approxi-
mately a factor of five.
34
The reason for this difference in the
relative mobility of holes and electrons is probably a result of
different sensitivity to intra- and inter-chain hole transport of
the experimental methods. Fitting of the simulation and
experimental results allows significant freedom of correlated
variation of hopping rates of electrons and holes in different
directions, thus the distinction of electron and hole mobilities
is not reliable. Therefore we present, in Fig. 3, the carrier
mobility averaged over electrons and holes, obtained directly
from the experimental data. The short time carrier mobility is
almost two times larger for the annealed sample. Carrier mobilities
Fig. 2 Cross section of typical simulated structures of as-spun (left) and
annealed (right) samples. Dark areas denote acceptor regions (PCBM) and
white areas denote donor regions (P3HT). The red line represents the
length of 50 nm.
Paper PCCP
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online

2690 |Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 This journal is ©the Owner Societies 2 01 4
in both samples drop down several tens of times during 1 ns.
The TREFISH mobilities at t> 1 ns approach literature data for
steady state mobility,
5,18,19
indicating that carrier populations have
almost relaxed into trap states during this time. Qualitatively
similar mobility dynamics was observed in pure polymer films,
27,28
showing that both inherent polymer and PCBM properties,
as well as nanostructured blend morphology, are responsible
for the mobility dynamics.
Our experimental data give information on the carrier drift
distance, while the absolute carrier separation distance is deter-
mined by carrier diffusion as well as drift. These two processes are
interrelated through the Einstein relation D=mk
B
T/q,whereDis the
diffusion coefficient, mis the carrier mobility, k
B
is the Boltzmann
coefficient, Tis the temperature and qis the electron charge. In our
previouspaperwehaveshownthatthediffusiondistanceonaps
time scale significantly exceeds the drift distance at low fields and is
responsible for the weakly field dependent carrier separation yield.
7
MC simulation is a convenient approach to obtain average
absolute carrier separation distances caused by both carrier
drift and diffusion from the carrier drift kinetics. Fig. 4 shows a
comparison of the absolute carrier separation distances in
as-spun and annealed samples at different electric field strengths.
At zero electric field, only the diffusion drives the carrier
motion, thus curves at zero field represent diffusion driven
charge separation dynamics. At 0 and 1.7 10
5
Vcm
1
electric
fields the separation distances on a tens of ps time scale are
almost independent of the sample annealing. The difference
appears on a ns time scale, when electrons approach the
boundaries of small PCBM domains in the as-spun sample,
while in the annealed sample with larger PCBM domains, they
continue an unrestricted motion. At higher electric field, when
the carrier drift contributes more to their motion, charge
Fig. 3 Carrier mobility averaged over electrons and holes for as spun
(closed circles) and annealed (open circles) samples at 4.7 10
5
Vcm
1
field strength.
Table 1 Numerical values of the parameters of the model
Lattice dimension
in the xdirection (nm)
Lattice dimension
in the ydirection (nm)
Lattice dimension
in the zdirection (nm)
Lattice constant
a(nm)
Average size of the
acceptor ellipsoid M(nm)
100 400 400 1 As-spun: 220 annealed: 19 800
Average length of the
donor chain (nm)
Hopping rate prefactor
in the acceptor n
A
(s
1
)
Hopping rate prefactor
in the donor n
D1
(s
1
)
Hopping rate prefactor
in the donor n
D2
(s
1
)
Hopping rate prefactor
in the donor n
D3
(s
1
)
6 2.8 10
16
210
15
110
15
510
14
Parameter g(nm
1
) Disorder in the
acceptor s
A
(meV)
Disorder in the
donor s
D
(meV)
Temperature T(K) Mean dielectric permittivity e
5 70 80 293 3
Correction parameter bof the initial electron–hole interaction energy Fraction of exponential distribution exp(E/s)
in the modified Gaussian distribution
2 0.19
Fig. 4 Calculated absolute charge carrier separation distances in as spun
(dotted lines) and annealed (solid lines) samples at different electric field
strengths obtained by Monte Carlo simulation using a model fitted to the
drift distance data in Fig. 1. The curves at higher electric field strengths are
vertically shifted.
PCCP Paper
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online

This journal is ©the Owner Societies 2014 Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 | 2691
carriers move faster and reach domain boundaries in the as
spun sample already on a ps time scale, thus the difference in
separation distances appears already during tens of ps. Strongly
restricted carrier motion in the as-spun sample with smaller
PCBM and polymer domains prevents carrier escape from the
Coulomb attraction. In devices such restricted carrier motion
leads to enhanced charge carrier recombination, which is
apparently one of the major factors limiting the carrier genera-
tion yield and performance efficiency of non-annealed P3HT/
PCBM solar cells.
23
Our MC simulations have been performed assuming that
only nearest neighbor e–h pairs are created by exciton splitting
at the donor–acceptor interface as was suggested in ref. 7
and 33. However, there are publications
35–37
arguing that charge
carrier separation at much longer distances takes place on a
femtosecond time scale and it helps for final separation of e–h
pairs into free charges. Since this is still an open question,
which could be also related to the blend annealing, we have
also performed additional calculations directed towards evalua-
tion of the role of the initial carrier separation distance in the
charge separation process. Fig. 5 shows the calculated absolute
charge carrier separation distances at zero applied field with
the model parameters obtained from the above described
simulations. Diffusion driven separation at long times is large
with larger initial separation, but the influence of the initial
separation gradually decreases with time and after several ns
the separation distance is almost independent of the initial
ultrafast separation if this separation is significantly smaller
than 8 nm. Thus, initial carrier separation only weakly influences
the final carrier separation process (at several ns when charges
have reached a distance where the electrostatic attraction energy
is similar to kT), unless the initial separation is comparable with
the Coulomb capture radius. On the other hand, as we have
discussed in ref. 7, the large distance carrier separation is hardly
compatible with our experimental carrier drift data showing no
quasi-instantaneous carrier drift component.
6. Conclusions
In conclusion, our experimental investigations of the initial
carrier motion in as-spun and annealed P3HT:PCBM blends
together with Monte Carlo simulations of the carrier drift
dynamics suggest a mechanism for the improved performance
of annealed solar cells. The initial carrier drift rates, on a
subnanosecond–nanosecond time scale are about two times larger
in annealed samples. Monte Carlo simulations of the motion
dynamics suggest that the increase in the carrier separation rate
caused by blend annealing is related to the increased polymer and
PCBM domain sizes enabling longer distance carrier separation on
a ps time scale, which reduces the probability of their geminate
recombination and thus increases the free charge carrier genera-
tion yield in annealed samples. On the other hand, the role of
other material properties such as the presence of energy traps, or
formation of semicrystalline polymer domains, which change as a
result of annealing, cannot be completely ruled out.
Additional MC simulations directed towards evaluation of
theroleoftheinitialcarrierseparation distance showed that the
more efficient carrier separation in annealed samples can be
hardly related to increased initial carrier separation distance.
The initial separation distance only weakly influences the carrier
separation efficiency at times and distances where free charges
are formed if it is shorter than about 8 nm, while longer distance
separation is non-compatible with our experimental data.
Acknowledgements
This research was funded by the European Social Fund under
the Global Grant measure, by the Swedish and European
Research Councils (ERC 226136-VISCHEM), by the Swedish
Energy Agency and the Knut & Alice Wallenberg Foundation
and by Laser Lab Europe (project ID LLC001578, framework of the
Initiative of Infrastructures Programme), by the UK Engineering
and Physical Sciences Research Council via the Supergen
programme and by the Royal Society.
Notes and references
1 J. Nelson, Curr. Opin. Solid State Mater. Sci., 2002, 6, 87–95.
2 G. Yu, J. Gao, J. C. Hummelen, F. Wudl and A. J. Heeger,
Science, 1995, 270, 1789–1791.
3 Z. He, C. Zhong, S. Su, M. Xu, H. Wu and Y. Cao, Nat.
Photonics, 2012, 6, 591–595.
4 J. Guo, H. Ohkita, H. Benten and S. Ito, J. Am. Chem. Soc.,
2010, 132, 6154–6164.
5 V. D. Mihailetchi, H. Xie, B. de Boer, L. Jan Anton Koster and
P. W. M. Blom, Adv. Funct. Mater., 2006, 16, 699–708.
6 S. De, T. Pascher, M. Maiti, K. G. Jespersen, T. Kesti,
F. Zhang, O. Ingana
¨s, A. Yartsev and V. Sundstro
¨m, J. Am.
Chem. Soc., 2007, 129, 8466–8472.
7 D. Amarasinghe Vithanage, A. Devizˇis, V. Abramavic
ˇius,
Y. Infahsaeng, D. Abramavic
ˇius, R. C. I. MacKenzie,
P. E. Keivanidis, A. Yartsev, D. Hertel, J. Nelson,
V. Sundstro
¨m and V. Gulbinas, Nat. Commun., 2013, 4, 2334.
Fig. 5 Calculated time dependence of the absolute carrier separation
distance at zero electric field and at various initial separation distances.
Paper PCCP
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online

2692 |Phys. Chem. Chem. Phys., 2014, 16, 2686--2692 This journal is ©the Owner Societies 2014
8 C. Brabec, V. Dyakonov and U. Scherf, IEEE J. Sel. Top.
Quantum Electron., 2013, 16, 1517.
9 R. A. Marsh, J. M. Hodgkiss, S. Albert-Seifried and
R. H. Friend, Nano Lett., 2010, 10, 923–930.
10 F. Zhang, K. G. Jespersen, C. Bjo
¨rstro
¨m, M. Svensson,
M. R. Andersson, V. Sundstro
¨m, K. Magnusson, E. Moons,
A. Yartsev and O. Ingana
¨s, Adv. Funct. Mater., 2006, 16, 667–674.
11 M. Reyes-Reyes, K. Kim and D. L. Carroll, Appl. Phys. Lett.,
2005, 87, 083506.
12A.M.Ballantyne,T.A.M.Ferenczi,M.Campoy-Quiles,
T.M.Clarke,A.Maurano,K.H.Wong,W.Zhang,N.Stingelin-
Stutzmann,J.-S.Kim,D.D.C.Bradley,J.R.Durrant,
I. McCulloch, M. Heeney, J. Nelson, S. Tierney, W. Duffy,
C. Mueller and P. Smith, Macromolecules, 2010, 43, 1169–1174.
13 Y. Kim, S. A. Choulis, J. Nelson, D. D. C. Bradley, S. Cook
and J. R. Durrant, Appl. Phys. Lett., 2005, 86, 063502.
14 C. H. Woo, B. C. Thompson, B. J. Kim, M. F. Toney and
J. M. J. Frechet, J. Am. Chem. Soc., 2008, 130, 16324–16329.
15 T. Agostinelli, S. Lilliu, J. G. Labram, M. Campoy-Quiles,
M. Hampton, E. Pires, J. Rawle, O. Bikondoa,
D. D. C. Bradley, T. D. Anthopoulos, J. Nelson and
J. E. Macdonald, Adv. Funct. Mater., 2011, 21, 1701–1708.
16 E. Verploegen, R. Mondal, C. J. Bettinger, S. Sok, M. F. Toney
and Z. Bao, Adv. Funct. Mater., 2010, 20, 3519–3529.
17 X. Yang, J. Loos, S. C. Veenstra, W. J. H. Verhees,
M. M. Wienk, J. M. Kroon, M. A. J. Michels and
R. A. J. Janssen, Nano Lett., 2005, 5, 579–583.
18 J. Huang, G. Li and Y. Yang, Appl. Phys. Lett., 2005, 87, 112105.
19 C. Nam, D. Su and C. T. Black, Adv. Funct. Mater., 2009, 19,
3552–3559.
20 M.Campoy-Quiles,T.Ferenczi,T.Agostinelli,P.G.Etchegoin,
Y. Kim, T. D. Anthopoulos, P. N. Stavrinou, D. D. C. Bradley
and J. Nelson, Nat. Mater., 2008, 7, 158–164.
21 D.Veldman,O.Ipek,S.C.J.Meskers,J.Sweelssen,M.M.Koetse,
S.C.Veenstra,J.M.Kroon,S.S.vanBavel,J.Loosand
R. A. J. Janssen, J. Am. Chem. Soc., 2008, 130, 7221–7235.
22 P. E. Keivanidis, T. M. Clarke, S. Lilliu, T. Agostinelli,
J. E. Macdonald, J. R. Durrant, D. D. C. Bradley and
J. Nelson, J. Phys. Chem. Lett., 2010, 1, 734–738.
23 R. Hamilton, C. G. Shuttle, B. O’Regan, T. C. Hammant,
J. Nelson and J. R. Durrant, J. Phys. Chem. Lett., 2010, 1,
1432–1436.
24 T. G. J. van der Hofstad, D. Di Nuzzo, M. van den Berg,
R. A. J. Jensses and S. C. J. Meskens, Adv. Energy Mater.,
2012, 2, 1095–1099.
25 C. Mu
¨ller, T. A. M. Ferenczi, M. Campoy-Quiles, J. M. Frost,
D. D. C. Bradley, P. Smith, N. Stingelin-Stutzmann and
J. Nelson, Adv. Mater., 2008, 18, 3510–3515.
26 T. Agostinelli, S. Lilliu, J. G. Labram, M. Campoy-Quiles,
M. Hampton, E. Pires, J. Rawle, O. Bikondoa,
D. D. C. Bradley, T. D. Anthopoulos, J. Nelson and
J. E. Macdonald, Adv. Funct. Mater., 2011, 21, 1701–1708.
27 A. Devizis, A. Serbenta, K. Meerholz, D. Hertel and
V. Gulbinas, Phys. Rev. Lett., 2009, 103, 027404.
28 A. Devizis, K. Meerholz, D. Hertel and V. Gulbinas, Chem.
Phys. Lett., 2010, 498, 302–306.
29 A. Miller and E. Abrahams, Phys. Rev., 1960, 120, 745–755.
30 W. L. Ma, C. Y. Yang and A. J. Heeger, Adv. Mater., 2007, 19,
1387–1390.
31 T. J. Savenije, J. E. Kroeze, M. M. Wienk, J. M. Kroon and
J. M. Warman, Phys. Rev. B: Condens. Matter Mater. Phys.,
2004, 69, 155205.
32 J. Cabanillas-Gonzalez, T. Virgili, A. Gambetta, G. Lanzani,
T. Anthopoulos and D. De Leeuw, Phys. Rev. Lett., 2006,
96, 106601.
33 D. Veldman, O. Ipek, S. C. J. Meskers, J. Sweelssen,
M. M. Koetse, S. C. van Bavel, J. Loos and R. A. J. Janssen,
J. Am. Chem. Soc., 2008, 130, 7721–7735.
34 C. S. Ponseca, H. Nemec, N. Vukmirovic, S. Fusco, E. Wang,
M. R. Andersson, P. Chabera, A. Yartsev and V. Sundstrom,
J. Phys. Chem. Lett., 2012, 3, 2442–2446.
35 A. A. Bakulin, A. Rao, V. G. Pavelyev, P. H. M. van. Loos-
drecht, M. S. Pshenichnikov, D. Niedzialek, J. Cornil,
D. Beljonne and R. H. Friend, Science, 2012, 335, 1340–1344.
36 I. A. Howard, R. Mauer, M. Meister and F. Laquai, J. Am.
Chem. Soc., 2010, 132, 14866–14876.
37 C. Deibel, T. Storbel and V. Dyakonov, Phys. Rev. Lett., 2009,
103, 036402.
PCCP Paper
Published on 05 December 2013. Downloaded by Nanyang Technological University on 08/10/2014 03:18:58.
View Article Online