Palabras del doctor Abdul Husein Zarin Kub

As discussed, the interface between dilute and neat layers of donor material forms an exciton permeable interface due to an asymmetry in transfer rates. The dilute donor OPVs presented in Chapter 4 show a 30% enhancement in power conversion efficiency (ηP) relative to undiluted control devices [87]. In these devices, dilute layers of the

archetypical electron donating molecule boron subphthalocyanine chloride. (SubPc) [72,92,97] dispersed in the wider energy-gap host material p- bis(triphenylsilyl)benzene (UGH2) [84,85] show a 50% increase in the LD for SubPc

The increase in bulk LD leads to an enhancement in the exciton diffusion efficiency (ηD)

when incorporated as part of a multilayer donor structure. Notably, an exciton permeable interface exists between the 12-nm-thick dilute layer of variable concentration and the 5- nm-thick layer of neat SubPc (Figure 6.2). The control device consists of separately optimized 13-nm-thick donor layer of SubPc [97]. The enhancement in ηD for these

structures is, consequently, a combination of both bulk diffusion and interface effects. In order to understand the balance of these effects and model exciton migration in these devices, proper consideration of energy transfer at the permeable interface is critical. In addition to the imbalance in molecular site density, the variation in average intermolecular separation (𝑑1 > 𝑑2) manifests imbalance across the permeable interface

through the concentration dependence of the self Förster radius (self-R0) and the distance

dependence for the rate of Förster energy transfer. These contributions are pictured schematically in the inset of Figure 6.2.

Figure 6.2 Dilute donor OPV schematic detailing the imbalance in donor molecular density at the interface between the dilute and neat donor layers. Adapted with permission from [116].

To confirm the validity of this model, photoluminescence quenching experiments and complementary simulations were performed for a two-layer system where the outer

150 nm ITO 10 nm MoO_X 12 nm (x wt.% SubPc) 5 nm SubPc 35 nm C₆₀ 10 nm BCP Al Glass

layer consists of a 20-nm-thick layer of 50 wt.% SubPc dispersed in UGH2 while the 10- nm-thick inner layer has a variable SubPc concentration (Figure 6.3). Photoluminescence (PL) is measured with and without the presence of an adjacent 10-nm-thick layer of naphthalene-1,4,5,8-tetracarboxylic acid dianhydride (NTCDA). Experimental photoluminescence ratios are defined as the ratio between quenched photoluminescence (PLQ) and unquenched photoluminescence (PLUQ).

Simulated PL ratios are generated using the KMC approach for two situations namely, with and without the rate imbalance (gating) at the exciton permeable interface. A transfer matrix formalism was used to determine the optical field and rate of exciton generation within the structure. Hopping rates within each layer were determined from measured values of LD as a function of concentration. The imbalance in energy transfer

at the interfaces was captured by explicitly including the effects of both the imbalance in molecular site density and intermolecular separation. Care was taken to include the effect of variable photoluminescence efficiency (ηPL) between the layers. The KMC modeling

also allows for the tabulation of the exciton diffusion efficiency (ηD) as a function of

interlayer concentration. Modeling the experimental PL ratios, consequently, provides a direct confirmation for the presence and sources of the rate imbalance.

Figure 6.3 (a) Photoluminescence (PL) quenching experiment where the concentration of the inner layer was varied. (b) Resulting PL ratios along with the corresponding fit from Kinetic Monte Carlo simulations. Also shown is the associated exciton diffusion efficiency. Adapted with permission from [116].

Agreement between experimental and simulated PL ratios is only achieved when imbalance (gating) at the permeable interface is included. Interestingly, when the effect of the exciton permeable interface is correctly applied, ηD is optimized for an inner layer

comprised of undiluted SubPc. This counterintuitive result contrasts the notion that exciton harvesting is optimized by incorporating active materials with the longest LD and

confirms that the interface plays a critical role in driving excitons toward the D-A interface.

Figure 6.4 shows the measured external quantum efficiency (ηEQE) at a

wavelength λ = 590 nm, corresponding mainly to SubPc absorption, as measured from the devices in Chapter 4. A transfer matrix formalism is employed to model the incident optical field responsible for photon absorption and exciton generation. Simulated ηEQE,

absorption efficiency (ηA), and ηD calculated using the KMC model are also shown as a

function of dilute layer concentration in Figure 6.4. Excellent agreement with experiment is found when an additional, concentration independent loss term equal to 0.85 is

Substrate NTCDA 50 wt.% SubPc θ Pump PLQ X wt.% SubPc θ PLUQ Pump X wt.% SubPc 50 wt.% SubPc (a) (b) 0 20 40 60 80 100 0.0 0.2 0.4 0.6 0.8 1.0 Experiment Sim. with gating Sim. without gating

Photo

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Ratio

Interlayer Concentration (wt.% SubPc) 0 20 40 60 80 100 0 10 20 30 40 50 60 Diffusion Efficiency (%)

included. Here, 𝜂𝐸𝑄𝐸 = 𝜂𝐴𝜂𝐷𝜂𝐶𝑇𝜂𝐶𝐶 = 0.85𝜂𝐴𝜂𝐷 where ηCT and ηCC are the charge

transfer and charge collection efficiencies, respectively. Losses are expected and may reflect exciton quenching at the MoOx anode buffer layer and non-unity ηCC. Further,

previous work shows concentration-independent acceptor ηEQE and fill factor for devices

incorporating dilute layers ≥25 wt.% SubPc, confirming that UGH2 does not have a concentration-dependent effect on the ηCC [87].

Figure 6.4 (a) Measured and modeled external quantum efficiency along with the modeled absorption and diffusion efficiencies for the dilute donor device of Figure 6.2. (b) Separated exciton diffusion efficiencies for the neat and dilute layers with and without adding the exciton gating effects. Adapted with permission from [116].

Interestingly, ηD increases continuously upon dilution. To confirm the origin of

the enhanced ηD, Figure 6.4 displays the separated dilute and neat layer ηD as a function

of concentration. Furthermore, the separate values of ηD are simulated for the actual

device with a rate imbalance at the interface as well as for an artificial device where no imbalance is present. For the latter, the hopping rates within and between each layer in

0 20 40 60 80 100 40 50 60 70 80 90 100 D (%) Concentration (wt.% SubPc) 0 20 40 60 80 100 0 10 20 30 40 50 60 70 80 90 100 Measured EQE Modeled EQE Diffusion Efficiency Absorption Efficiency Eff ici en cy (%) Concentration (wt.% SubPc) Neat Layer Dilute Layer Without Interface With Interface Without Interface With Interface λ = 590 nm (a) (b)

proper bulk LD. The simulation of the artificial devices allows for the determination of

ηD based solely on changes to the bulk LD. Dilution, however, is capable of achieving

very large imbalances (k12/k21 ~ 100–1,000) in energy transfer, yielding ηDDilute and ηDNeat

that are significantly larger than values obtained from solely considering increases in bulk LD. The ηDNeat increases upon dilution owing to more effective reflection at the gating

interface. The η_DDilute _{increases from η} D

Dilute_{=(56.9 ± 1.1)% to η} D

Dilute_{=(74.6 ± 1.5)%. Of}

this enhancement, 20% results from changes in bulk LD with the remainder resulting from

the effect of the gating interface. It should be noted that the increase in η_DDilute would be ~20% larger if compared to an identically thick control device instead of the optimized control device. Remarkably, a total donor layer ηD>85% is achieved.