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DOI: 10.1039/C3CP53834F

Influence of Ionizing Dopants on Charge Transport in Organic Semiconductors

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a

Department of Physics, University of Oxford, Oxford OX1 3PU, U.K. Department of Physics, University of Bath, Bath BA2 7AY, U.K. ‡ These authors contributed equally. * Corresponding author: ABW [email protected] KEYWORDS. organic semiconductors / triphenylamine / conductivity / p-doping / Monte Carlo simulation / ionizing dopants / charge transport / lithium doping / solid state dye-sensitized solar cells / perovskite solar cells b

Abstract Ionizing chemical dopants are widely used in organic semiconductors to enhance the charge transport properties by increasing the number of mobile charge carriers. However, together with mobile charges, chemical doping produces anion-cation pairs in the organic matrix. In this work we use experimental and computational analysis to study the influence of these ionic species on the charge transport. We show that the anion-cation pairs introduced upon doping have a detrimental, doping-level dependent effect on charge mobility. For doping levels of 0.02 - 0.05 % molar ratio with respect to the molecular organic semiconductor, the increase in conductivity from the extra mobile charges is partially cancelled by a reduction in charge mobility from traps introduced by the anion-cation pairs. As the doping concentration increases, anion-cation pairs start to overlap, resulting in a comparatively smoother potential landscape, which increases the charge mobility to values closer to the undoped semiconductor. This result has a significant, practical impact, as it shows the need to dope at or slightly above a threshold level, which depends on the specific hostdopant combination. Introduction Organic semiconductors (OSs) are highly versatile materials with progressively advancing properties that provide a low-cost alternative to inorganic materials in light emitting diodes for displays and lighting, organic thin-film light emitting diodes,1 sensors, field effect transistors,2 transport and recombination layers in organic solar cells,3 and hybrid organic-inorganic solar cells such as solid-state dye-sensitized solar cells4,5and perovskite solar cells.6 Fast charge transport in OSs is vital, especially in hybrid and organic solar cells, to allow photogenerated charges to reach the extracting electrode before recombination can occur. For ptype (hole transporting) OSs, dopants are strong oxidants that enhance the concentration of holes by withdrawing electrons from the OS. In the case of n-type (electron transporting) OSs, chemical doping can be achieved through the introduction of electron donating impurities (reducing agents). The charge carriers generated by doping fill deep trap states, improving the mobilities. Applications of chemical doping include transistors for sensors, radio-frequency identification tags, organic and hybrid organic-inorganic solar cells. Doping introduces charge donating or accepting atoms or molecules, generating sufficient charge carriers to control charge conduction and negate the influence of unwanted impurities. In OSs only a small fraction of these generated charges are mobile, while the remainder are bound to their donors or acceptors due to the low electrical permittivity of the host,7 forming anion-cation pairs. Electrostatic interactions of the mobile charges

Physical Chemistry Chemical Physics Accepted Manuscript

Antonio Abate,a‡ Daniel R. Staff, b‡ Derek J. Hollman,a Henry J. Snaitha and Alison B. Walkerb*

Physical Chemistry Chemical Physics

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with these anion-cation pairs create a disordered landscape that hampers charge carrier mobility in OSs since the charges are localised, in our case, to regions 2 nm across, which is similar to the length scale on which the disorder occurs.7 The effects of disorder on mobilities have been widely studied in simulations of undoped OSs based on the Gaussian Disorder Model introduced by Bässler8 and studies of organic device characteristics, for example, by Kimber et al.9 In this paper we focus on the doped materials used in solid-state dye-sensitized and perovskite solar cells in the light of recent interest in these cells due to significant increases in power efficiency;6,10 however, our modelling techniques and the results reported here are applicable to other doped OSs. The most efficient reported hybrid solar cells employ the host-dopant system spiro-OMeTAD (2,2’,7,7’-tetrakis(N,N-di-(p-methoxyphenyl)-amino)9,9’-Spirobifluorene) p-doped with Li-TFSI (Li [(CF3SO2)2N])11 as their hole transporting material. Li-TFSI doping occurs when the devices are exposed to air through electron transfer from the OS to lithium-oxygen complexes in reactions that, unlike previous reports,12 do not require an interface with TiO2 or dye molecules.11 This doping mechanism is also seen in hole transporters such polythiophene derivatives.13,14 Evidence that a significantly improved device performance from doping can be attributed to reduced charge transport resistance in the hole-transporting matrix comes from measurements on protic ionic liquids used as a p-dopant for spiro-OMeTAD.5 Protic ionic liquids, with an oxygenfree doping mechanism, have an advantage over Li-TFSI in that the devices can be fabricated in an inert atmosphere, providing greater control and reproducibility.5 It is important to identify the changes to device performance caused by doping. For example, the effects on the hole conductivity depend on changes in the free hole density p and changes in the hole mobility µh. An effective mobility is often introduced that assumes p is fixed and that assigns changes in hole conductivity with temperature and applied voltage to changes in µh without allowing for the possibility that p is also changing, causing errors in interpreting experimental results. Additionally, in most studies on doped spiro-OMeTAD, measurements take place on illuminated solid-state dye-sensitized cells, so it is difficult to separate out the effect of the Li-TFSI dopant on charge mobility, due to disorder mentioned above, from changes in recombination rates and electron transport caused by the dopants at the TiO2 interface with the spiro-OMeTAD. We use electronic structure calculations and mesoscopic scale charge transport simulations coupled with experimental studies to elucidate how OS doping influences hole transport. We have focused on the influence of disorder on the hole mobility µh arising from anion-cation pairs through measuring the hole conductivity of the doped hole transporter for a dopant that introduces free carriers and the hole conductivity for materials doped with inert dopants that introduce similarly sized anion-cation pairs without generating free carriers. These measurements were made for single layer devices where the only active layer is the OS using the procedures adopted by Planells et al.15 and used this procedure to compare the measurements of Cappel et al.12 and Abate et al.5 on variations in hole conductivity of spiro-OMeTAD doped with Li-TFSI and measurements of spiroOMeTAD doped with the “inert dopants” (no electron transfer from OS to dopant occurs) sodium bis(trifluoromethylsulfonyl)-imide (Na-TFSI) and tetraethylammonium bis(trifluoromethylsulfonyl)-imide (Et4N-TFSI). Anion-cation pairs caused by electron transfer on doping spiro-OMeTAD were modelled with density functional calculations, and a kinetic Monte Carlo simulation showed how µh is influenced by the dipoles created by these pairs. We have investigated how µh changes with the anion-cation separation. Our key finding is that the electrostatic effect of the dipoles significantly decreases the

Physical Chemistry Chemical Physics Accepted Manuscript

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DOI: 10.1039/C3CP53834F

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DOI: 10.1039/C3CP53834F

Experimental Methods All the chemicals used in the experimental part of this work have been purchased from SigmaAldrich UK with puriss plus purity grade (assay ≥ 99.5%) and used without further purifications. All the solvents were ReagentPlus Grade (purity ≥ 98.5%) and anhydrous. Devices for measuring the conductivity of OSs were prepared on glass substrates, which were cleaned with Hellmanex (2% in deionized water), deionized water, acetone, and ethanol. These were then oxygen plasma etched before OS deposition. A thin film (400 nm) of spiro-OMeTAD was deposited from a 5% v/v solution in chlorobenzene by spin coating. For doped spiro-OMeTAD, the spin coating solutions again consisted of the same concentration of spiro-OMeTAD with varying concentrations of salts to achieve the desired doping level. The doped solutions were prepared in a mix of n-butanol and chlorobenzene, due to the insolubility of the salts in chlorobenzene alone. Although the solvent mixture could influence the film morphology and thus the conductivity, we observed a negligible effect for the prepared samples. The electrodes were deposited on the organic film by evaporating gold in ultra-high vacuum with a shadow mask to obtain a pattern for conductivity measurements. The electrode pattern was designed for four point probe measurements with a force channel length (direction of current flow) of 1 mm and a width of 1 cm, and a sense channel length of 300 µm and width of 1 mm. The JV characteristics of these samples were collected at room temperature with a Keithley 2420 Source Meter unit to extract both the bulk and the contact resistance. The contact resistance was negligible compared to the bulk value at all doping levels. No relevant visible light dependence of conductivity was observed. Modelling Methods The intrinsic carrier density in OSs, as commonly reported is reported as being less than ~10 cm-3, see Mendels, 16 and dopants are less than 10 mol%. At the end of this section, we show how we have deduced a higher intrinsic density of 8.67 x 1014 cm-3 from conductivity measurements on undoped spiro-OMeTAD. This high value for the intrinsic density probably originates from chemical impurities within the spiro-OMETAD we used (assay ≥ 99.5%), and may further be enhanced by the impurities within the solvents (purity ≥ 98.5%) used to prepare the films for the conductivity measurements. At this measured density, carriers are separated by ~100 nm, so their electrostatic interaction energy is ~0.01 eV, small compared to the width characterising the disordered energetic landscape that the carriers experience. We therefore neglect carrier-carrier interactions and the influence of carrier density on mobility in our model of charge transport in OSs.17 At higher doping levels employed, for example, in OLEDs, site-exclusion will produce an increase in charge mobility. The reason is that site exclusion forbids more than one charge to be localised in a given trap. The traps therefore fill up as more free charge is added to the semiconductor and so the quasi-Fermi level (quasi because charge is generally added via injection or electron-hole charge generation under illumination) is raised. The detrapping rate for charges depends exponentially on the energy difference between the trap level and conduction band, divided by the thermal energy. Hence, detrapping occurs mainly from traps at the quasi-Fermi level and becomes much faster as this level approaches the conduction band, leading to an increase in the mobility with the charge density. This increase in mobility means that the conductivity will increase

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charge mobility at low doping levels. For doping levels of 0.1 – 0.6 molar %, the reduction in hole conductivity tends toward 0.1 times the undoped system conductivity.

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faster than it would if the only effect of the doping were to increase the free charge density through ionising the dopants. There will also be space charge effects which may help or hinder charge transport. However, for values of p relevant to solar cell operation, Leijtens et al.18 found that µh in doped spiro-OMeTAD is independent of p for spiro-OMeTAD doped by Li-TFSI. We simulate an      cubic lattice with lattice constant a. A single anion-cation pair is placed in the centre of the lattice so the concentration of anion-cation pairs is 1/ . The coordinates of each ion are , , and the magnitude of the dipole moment is 2 √3 where q is the magnitude of the electronic charge. To simulate an infinite lattice, periodic boundary conditions were enforced such that the electric potential contribution from anion-cation pairs centred at positions 1 , 2 , 3  are included where 1 , 2 , 3 are integers. The trajectories of holes are obtained for the GDM by the Kinetic Monte Carlo (KMC) algorithm, which is faster in this application than MC algorithms that reject some moves. Carrier motion is represented by thermally assisted hopping between sites on a 3D cubic lattice. Each site represents a small molecule that may be occupied by a hole (p-OS).19,20 The GDM states that the energy of a hole on a particular site is randomly drawn from a Gaussian distribution centred at zero with standard deviation σ so that the probability density for a site i with energy , is ρ, 

%

2π!" # & exp *+

& ,-,./011

"!&

2.

(1)

The rate 34 associated with hopping at temperature 5 between sites  and 4 with energy  and 4 is given by the Miller-Abrahams equation8 34 30 e+2α6 7 , 4 . (2) where f(Ei,Ej) is given by exp ;+

,< #,-

@ if 9 C  => ? : (3) 1 if 9 D  where EF is Boltzmann's constant, 6 is the distance between the two sites, and G is a localisation constant that represents the extent of the electron orbital at each hopping site. Each carrier is localized approximately on a single molecule. 30 is the intrinsic hopping rate, set to unity since we only compare changes in mobility. The localization length 1/α depends on the energy of the charge carrier as it is easier for less strongly bound electrons to tunnel between molecules. An increase in localisation length will be similar to changing the dipole length through making the deep traps, traps that most strongly influence transport, shallower. We have not quantified this effect since including this energy dependence would require adding an additional unknown parameter so here we assume G to be energy independent. The site energy of each hopping site Ui is the sum of the contribution from the Gaussian disorder , , the electrostatic interaction energy between an infinite array of anion-cation pairs , HIJK and a carrier, and the energy due to an applied bias ,F .  , L , HIJK L ,F (4) 21 Ui,dipole is calculated by Ewald summation. Ui,bias is the energy due to motion through a distance x moved in an electric field E along the x-direction ,F +MN (5) A site is chosen at random as a starting position for the carrier, which we label site  . The destination for each hop is chosen using the roulette wheel selection method22 using a uniform random deviate generated using the Mersenne twister algorithm so that the probability of hopping 7 , 9 

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DOI: 10.1039/C3CP53834F

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from site i→j is always proportional to the rate Kij. A second uniform random deviate Γ, between 0 and 1, is used to calculate the time taken for the transition O for a charge at site i from O +log Γ ⁄∑J 3J . (6) The rate 3J is summed over all hopping sites, J, within a radius of 10 nm of site i. The simulation can then proceed indefinitely by repeating the process of choosing a site, calculating the waiting time,O, moving the particle and repeating until the average drift velocity is constant (no more than 107 hops required). For every transition between hopping sites, the displacement in the x direction is added to a running tally. The total net displacement of the carrier is known at every time step during the simulation as is the total simulation time. The calculations of displacement versus simulation time are well converged, giving a linear relationship between the displacement of the carrier and time in every case with an R2 value exceeding 1 + 10#V . Parameter

Symbol Value

Lattice constant

a

1 or 2 nm

Disorder width

σ

0.065 eV 19

Relative Dielectric Constant

ϵr

3

Localization Constant

α

2nm23

External Electric Field

E

0.02 V nm-1

Measure of anion-cation separation dac

0.4, 0.6,0.8 nm

Table 1: Parameters used in the MC model and their associated symbols. The simulation cell contains one dopant and so its length is determined by the dopant concentration. The anion-cation separation is 2dac√3 We use our predicted mobility changes to estimate the change in σ arising from doping by calculating p from the sum of the intrinsic carrier density of 8.67x1014 cm-3, extracted from conductivity measurements on undoped spiro-OMeTAD (σ = 5x10-8 S cm-1, µh = 3.6x10-4 cm2 V-1 s1 5,18 ), and the extra carriers induced by doping, assuming 1% doping efficiency. A molecular weight of 1225.45 g mol-1 and a film density of 1 g cm-3 gives 4.91x1020 spiro-OMeTAD molecules cm-3.5

Results and Discussion A ball and stick model of the inert dopants, Figure 1, allows us to find their anion-cation separations, dAC. Molecular conformations have been calculated by an MM2 energy-minimization on Chem3D software which uses a modified version of Allinger’s MM2 force field.24 As can be seen from Figure 1, dAC of Na-TFSI is smaller than for Et4N-TFSI. Furthermore, on Na-TFSI, the positive charge is localized on a small cation, which has poor solubility in organics. Et4N+ is much larger than Na+, and its alkyl chains give the salt high solubility in organics. The predicted dac of 3.1 Å for spiro-OMeTAD+-TFSI- is in between the dac values of 4.7Å and 2.2 Å respectively for Et4NTFSI and Na-TFSI. We would expect that in the OS film the difference in dAC between Na-TFSI (short dAC) and Et4N-TFSI (large dAC) is larger than the results predicted by the Chem3D package because this model does not consider the solvent, which is expected to reduce the anion-cation

Physical Chemistry Chemical Physics Accepted Manuscript

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DOI: 10.1039/C3CP53834F

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DOI: 10.1039/C3CP53834F

Figure 1. Ball and stick model of the inert salts (Et4N-TFSI and Na-TFSI) and the anion-cation pair generated by lithium doping spiro-OMeTAD (spiro-OMeTAD+-TFSI-). Molecular conformations and anion-cation distance (dAC) have been calculated from MM2 energy-minimization on Chem3D software. Colour legend: C grey, N blue, F yellow, O red, S orange, Na black, H not shown.

Figure 2. Solid lines: fits to measured hole conductivities using a B-spline function for spiroOMeTAD doped with Li-TFSI (circles), and the inert dopants Na-TFSI (squares, short anion-cation distance, dAC) and Et4N-TFSI (triangles, large anion-cation distance, dAC). All measured hole conductivities have been scaled by the conductivity of undoped spiro-OMeTAD. The dashed line shows the increase in hole conductivity deduced from our measurements assuming that only 1% of the lithium salt added in the spiro-OMeTAD will generate extra mobile charges.12 In Figure 2, we compare the hole conductivity of spiro-OMeTAD doped with Li-TFSI to its value when doped with the inert additives Na-TFSI and Et4N-TFSI. We also show the predicted change in conductivity due to Li doping. As discussed in the introduction, to calculate p we assumed that only 1% of the dopant generates mobile extra charges, which contribute to the conductivity.12 Then, even without allowing for any increase in µh with carrier density, we should expect an increase in conductivity with doping level of at least three orders of magnitude at a 1 % doping level. However, the measurements in Figure 2 show that Li-TFSI increases the spiro-OMeTAD conductivity by less

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electrostatic interaction. We have therefore used the larger values for dac shown in Table 1 for our MC model.

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than two orders of magnitude. We show below that this result, which is seen in many host-dopant systems,23,25 may be explained by considering the role of dipoles generated from doping. For Na-TFSI and Et4N-TFSI, changes in hole conductivities can be attributed solely to changes in µh due to the interaction of free charges with the anion-cation pairs. For both salts hole conductivities are lower than for undoped spiro-OMeTAD at all dopant concentrations explored in this work. Minima in conductivity can be seen for the two inert dopants for salt contents of 0.1 - 0.8 molar %. The conductivity at the minima decreases by nearly an order of magnitude, which suggests that the difference between expected and measured conductivities shown in Figure 2 for Li-TFSI at a doping level of 1% is due to the dipoles introduced.

Figure 3. Simulated change in hole conductivity versus anion-cation pair concentration with dac of 4 Å cf Na-TFSI, black squares), 6 Å (large anion-cation distance cf Et4N-TFSI, blue triangles) and in the insert 8 Å (large anion-cation distance, pink crosses). Lines show fits to the simulated data using a B-spline function. This behaviour is qualitatively reproduced by our MC simulations. Figure 3 shows the results of three sets of simulations of the conductivity variation with anion-cation pair concentration. The potentials change smoothly as the doping level is varied. We therefore argue that the oscillations in Figure 3 are due to particles getting trapped for a very long time and not detrapping within the simulation timescale. These oscillations do not alter our interpretation of the data nor the resulting conclusions since by examining the potential landscape of the trends in the Monte Carlo simulation, the predictions are easily explained. In each case the hole conductivity for the modelled inert-salt and spiro-OMeTAD mixture has a minimum at doping levels of 0.02 - 0.05 molar %. At doping concentrations of 0.02 mol%, the dipoles are separated by 20 nm, too far for frequent trapping of the carriers, In Figure 4, only one site immediately adjacent to the dipole sits at a potential lower than 0.125σ, constituting one lone site that is effectively a trap. The trap depths are greatest at low concentrations as shown in Figure 5. However, for these low concentrations, only a small fraction of the hopping sites is influenced by the dipoles so that although the dopants cause deep traps, carriers are unlikely to encounter them. At very low doping levels, the mobility is close to its undoped value.

Physical Chemistry Chemical Physics Accepted Manuscript

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DOI: 10.1039/C3CP53834F

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Figure 4. Two dimensional slice of a cubic lattice of hopping sites taken in the plane containing a dipole from an anion-cation pair, showing the contours of its electrostatic interaction energy with an electron, Ui,dipole, scaled by the disorder width σ. Here, for illustration, d = 1 nm and the simulation box width L = 10 nm, corresponding to a dopant concentration of 1×1018 cm-3. The minimum in each data set shown in Figure 3 at doping concentrations of around 1 mol% represents the concentration for poorest charge transport, where there are sufficient anion-cation pairs to trap holes but an insufficient concentration for the potentials to overlap. As the dipole moment increases, the decrease in conductivity becomes more dramatic, and the minimum is found at lower doping levels. The dipoles are separated by 6 nm, bringing the deep traps closer together than at the low doping levels. The carriers are more likely to become trapped and are trapped for longer periods, resulting in the observed minima in mobility and conductivity. The dipole separation distance is 4 nm at concentrations of 4 mol%, so the potential wells produced by the anion-cation pairs shown in Fig. 4 overlap and cancel; so the resulting traps become increasingly shallow as the dopant concentration increases above 4 mol%. For these doping concentrations, the deep trap depth, 6σ, is much smaller than its value, 8σ, at low doping levels. For all values of dAC, the trap depth decreases at high doping levels because the potentials from the dipole cancel as the dipoles move towards each other. This decrease in the trap depth explains why µh is relatively high at doping levels above 1%. We have assumed periodic boundary conditions to reduce the computer resource required by our calculations. Hence the dipoles in our model are aligned. The interaction energy for dipoles of equal dipole moment p in equilibrium at a temperature T is 2p4/[3(4πεrε0)2r6kBT] 26 and for all dopant concentrations considered is at least 4 orders of magnitude less than the thermal energy at room temperature so dipole-dipole interactions are too weak to cause alignment. However, the dipoles in the measured materials are partially aligned by the applied field F of 0.02 V/nm since the interaction energy with the field when the dipole is parallel to the field is pF = 1.0, 1.5 and 2.0 times the room temperature thermal energy for the dipoles with dac = 4,6,8 Å respectively. This partial misalignment is only important at dopant concentrations of 4 mol% and higher where the potentials due to neighbouring dipoles overlap. At such concentrations, there will be considerable cancellation of these potentials even if the dipoles are not completely aligned and so the arguments above are still valid. Figure 5 is an aid to understanding the trends in the hole mobilities with respect to the magnitude of the dipole moment. When dAC is doubled from 4 to 8 Å, the trap depth increases by a factor of 4.5. It is therefore unsurprising that when the cations and anions have the maximum dipole moment

Physical Chemistry Chemical Physics Accepted Manuscript

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DOI: 10.1039/C3CP53834F

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DOI: 10.1039/C3CP53834F

Figure 5:The most negative site potential (deep trap depth) scaled by the disorder width σ for each doping level and the anion-cation separation distance measure dAC = 4, 6, 8 Å. Conclusions We have used both Monte Carlo (MC) simulations and conductivity measurements to demonstrate the influence of the ionizing dopants on charge transport in organic semiconductors (OS). Doping an OS introduces immobile anion-cation pairs alongside mobile charge carriers, which also affect the charge conductivity in the organic matrix. It is therefore difficult to separate out experimentally the changes in conductivity due to the charge carrier concentration and the presence of anion-cation pairs. We probed the mobility changes caused by the anion-cation pairs by measuring the change in conductivity upon doping with inert salts, which produce anion-cation pairs without introducing extra mobile charges in the OS film. The results from conductivity measurements and MC simulations suggest that for very low doping levels of less than 0.02 mol%, the dopants are too sparse to influence the charge mobility. However, for doping levels in the range 0.02 - 1 mol % , the increase in conductivity due to the extra mobile charges is negated by a reduction in charge mobility. At these doping levels, the ionized molecules generated by doping create additional disorder above that present in the undoped material and are sufficiently close together that the mobile charges are trapped in the negative site potentials created by the electrostatic potential from the dipoles seen by the mobile charges. As the dopant concentration increases above 4 mol %, the average distance between the ionic species decreases so the electrostatic potentials overlap, the energy barrier between traps becomes lower, and carrier mobility is less impaired. In contrast to previous work,27 we observe no instance, even at very high ion concentrations, when the electrostatic potential from the anion-cation pairs has a positive influence on hole-mobility. We focused on spiro-OMeTAD p-doped by Li-TFSI, yet the key findings can be transposed to any OS-dopant system. Indeed, similar trends have been reported for other OSs such as poly-3hexylthiophene (P3HT)23 and pentacene.25 These OSs are commonly oxidized (p-doped) with tetrafluorotetracyanoquinodimethane (F4TCNQ), which generates extra holes in the organic matrix and F4TCNQ anions. A similar scenario can be analogously described for n-doping, where extra

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considered, the mobility is reduced to a negligible quantity. For larger dipole moments, the minimum in conductivity is shifted towards lower doping concentrations because the size of the trapping regions is greater.

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electrons are produced in the OSs and positively charged dopants are dispersed in the organic matrix. For example, 1,3-Dimethyl-2-phenyl-2,3-dihydro-1H-benzoimidazole derivatives (DMBI) can increase the conductivity of [6,6]-phenyl C61 butyric acid methyl ester (PCBM) by injecting electrons (n-doping) in the PCBM and leaving DMBI cations in the organic matrix.28,29 Acknowledgments We thank the Engineering and Physical Sciences Research Council (EPSRC) APEX project for financial support (AA), the EPSRC Excitonic Cells Consortium for a studentship (DRS). The research leading to these results has also received funding from the European Union Seventh Framework Programme [FP7/2007-2013] under grant agreement 316494 (ABW, HJS) and from the EPSRC Supersolar Hub (ABW,HJS).

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DOI: 10.1039/C3CP53834F

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Physical Chemistry Chemical Physics Accepted Manuscript

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DOI: 10.1039/C3CP53834F

Influence of ionizing dopants on charge transport in organic semiconductors.

Ionizing chemical dopants are widely used in organic semiconductors to enhance the charge transport properties by increasing the number of mobile char...
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