Article pubs.acs.org/JPCC
Controllable Bulk Heterojunction Morphology by Self-Assembly of Oppositely Charged Nanoparticles Kulveer Singh,†,§ Prateek K. Jha,*,‡ and Soumitra Satapathi*,†,§ †
Centre of Nanotechnology, IIT Roorkee, Roorkee, Uttarakhand 247667, India Department of Chemical Engineering, IIT Roorkee, Roorkee, Uttarakhand 247667, India § Department of Physics, IIT Roorkee, Roorkee, Uttarakhand 247667, India ‡
ABSTRACT: Using kinetic Monte Carlo simulations of a simple coarse-grained model, we demonstrate that the self-assembly of oppositely charged nanoparticles is a promising approach to design efficient bulk heterojunction (BHJ) solar cells. Simulations are performed starting from a random configuration of oppositely charged nanoparticles in solution for a range of concentrations. Interconnected percolated morphologies form at high nanoparticle concentrations, when the aggregate growth ceases after certain time. If only Coulombic interactions are present, the observed morphologies have very high interfacial area but too small domain size, whereas optimum values of both the interfacial area and domain size are desired for BHJ. We therefore propose and establish that an additional hydrophobic attraction between nanoparticles of same type is desired to obtain the ideal BHJ morphology. We also discuss the effects of solvent dielectric constant and the size- and charge-asymmetry of nanoparticles, which may provide additional means to control the BHJ morphology.
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INTRODUCTION Organic solar cells (OSCs) have high commercialization prospects due to their low cost, ease of fabrication, and flexibility.1,2 Continuous effort in designing novel low band gap materials with higher photon absorption and improved device architectures have led to power conversion efficiency(PCE) of OSCs as high as 10.6%.3 In addition to broad absorption spectrum, another desired attribute for a high efficiency in OSCs is an optimal BHJ morphology that facilitate efficient charge separation and charge transport.4−6 In an ideal BHJ (Figure 1), both electron- and hole-conducting materials interpenetrate to form a bicontinuous network, such that the interfacial area (active layer) is maximum and the average domain size of both the donor and acceptor materials is comparable to the exciton diffusion length. The interpenetration of the two domains must have an optimum value for high efficiency of OSCs, as too much interpenetration inhibits the charge transfer to the electrodes and too little interpenetration hinders the exciton diffusion to the interfaces. To achieve this optimal morphology, various experimental strategies7,8 such as controlling the solvent removal rate or the ratio of the donor and acceptor components, thermal/solvent annealing have been used. These ensure that the donor and acceptor phases are bicontinuous and length scale of the phases is similar to exciton diffusion length. In some recent studies, adding a third component in blend system have shown improvement in PCE of OSCs.9,10 Nevertheless, achieving an optimal architecture in blend system is a challenge due to interplay of various kinetic processes occurring during fabrication like crystallization, phase separation, solvent evaporation, etc.11 Furthermore, the organic solvents used in fabrication of the blend system are toxic and © 2017 American Chemical Society
volatile, which results in environmental and safety issues for large-scale commercialization.12 Because of these concerns, recently a lot of attention has been gained by solar cells made of polymeric nanoparticles (NPs).13,14 In a very short duration of time, PCE of 4% has been achieved in polymer NP OSCs.15 Besides having an environmental and industrial advantage over the blend system, a controllable morphology with proper domain size can also be achieved by self-assembly of spherical NPs.16−19 In principle, tailored ordering of assembly can be achieved by changing the NPs radii, their composition, surface charge, their number ratio, and other interactions. However, synthesizing NPs of diameters comparable to the exciton diffusion length (∼10 nm) remains difficult using the existing experimental method. The size and charge of the NP can be controlled by varying surfactant concentration18,20 during NP synthesis. Also, using reprecipitation method, Nagai et al.21 have developed NPs in the range of 10− 65 nm. Thus, there is a possibility that the self-assembly of pretailored NPs of different size and charge could facilitate the control of interfacial area and domain size of BHJ devices. Theoretical and computational studies may assist in developing the design rules for “bottom-up” assembly of NPs into BHJ morphology and thus guide future experiments. In earlier studies, charge transport within BHJ was studied using kinetic Monte Carlo (kMC) simulations on an artificially generated morphology developed on a cubic lattice.22−24 However, to the best of our knowledge, a systematic study of the formation of BHJ by NP self-assembly has not been Received: June 23, 2017 Published: July 2, 2017 16045
DOI: 10.1021/acs.jpcc.7b06168 J. Phys. Chem. C 2017, 121, 16045−16050
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Figure 1. Working principle of BHJ organic solar cells. (A) Formation of exciton by photon absorption and diffusion to the interface, (B) generation of charges by dissociation of exciton at the interface, and (C) propagation of charges to the anode and cathode.
where ϵLJ ij characterizes the strength of the LJ potential between type i and type j NPs. This is also truncated and shifted to result in a modified potential
performed. In this paper, we do not attempt to mimic the equilibrium phase diagram of oppositely charged nanoparticles, which may involve crystal formation.25 Instead, we are interested in out-of-equilibrium gel-like, percolated structures that form when the self-assembly is dynamically arrested.26,27 Here, we discuss our study of the self-assembly of charged NPs into BHJ morphology using a recently developed kMC scheme28 for nonequilibrium simulations. This scheme offers several advantages over conventional Brownian dynamics simulations for short to intermediate time evolution for a range of systems28−30and therefore is particularly suitable for the study of nonequilibrium self-assembly of NPs into thin films used in BHJ where the NP assemblies are far-fromequilibrium states.
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UijLJ , c(r )
Here, the cutoff distance for LJ interaction rij,cut is 2 σij when only soft core LJ repulsion is present and 2.5σij when an additional hydrophobic attraction is also present. Simulations start with a random distribution of NPs inside a ⎡π ⎤1/3 cubic box of length L = ⎣ 6η (σA 3nA + σB3nB)⎦ , where η is the packing fraction, i.e., the fraction of volume occupied by the NPs. One kMC step consists of randomly picking one NP and attempting to move its center to the surface of a sphere of radius a with the NP center being the origin. In order to ensure uniform probability density of choosing points on the sphere surface, the attempted move is performed by choosing an azimuthal angle θ = 2πu and a polar angle ϕ = cos−1(2v − 1), where u and v are random variables in (0, 1). Energy change of the attempted move ΔE is calculated and the move is accepted/ rejected with a Glauber transition probability p = [1+exp(ΔE/ kBT)]−1 for accepting moves. NT such steps constitute one kMC sweep. Time step of a sweep is related to the step size (a) of the move as Δt = a2/12D = (τ0/12)(a/σ0)2, where D is the diffusion coefficient of a free NP of diameter σ0 in solution and τ0 = σ02/D is the diffusion time scale. Δt in theory is derived28 assuming that the energy change associated with each move is small, and therefore small value of a is desired. In simulations, we have used a = 0.02σ0, which was observed to be a proper step size in a previous kMC study of electrolytes in solution.30
MODEL AND METHODS
kBT
=
zizjλBσ0 κσj
(1 + κσ2 )(1 + 2 ) i
e κσije−κr r
(1)
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where i = A, B and σij = (σi + σj)/2 is the average of diameters of NPs of type i and type j. λB = e2/4πεϵokBTσ0 is the dimensionless Bjerrum length and κ−1 = (8πλBσ0cs)−1/2 is the Debye screening length of monovalent electrolyte, where σ0 = (σA + σB)/2, ε is the relative dielectric constant of the solvent, ε0 is vacuum permittivity, kB is the Boltzmann constant, T is absolute temperature, and cs is the salt concentration. In order to improve computational efficiency, we use a truncated and shifted form of the potential in eq 1, that is ⎧ ⎪Uij(r ) − Uij(rij ,cut) r ≤ rij ,cut Uijc(r ) = ⎨ ⎪ 0 r > rij ,cut ⎩
RESULTS AND DISCUSSION Aggregation Kinetics. We first studied the aggregation kinetics of oppositely charged NPs in order to understand the aggregation regimes, threshold concentrations and the time scales to obtain percolated structures. Additional hydrophobic attractions are not considered in these simulations; only the Coulombic interactions and the soft-core LJ repulsions are considered. Aggregate size distribution of NPs is computed at different times from which the weight-averaged aggregate size Mw = ∑jnjj2/∑jnjj is calculated, where nj is the number of aggregates having j NPs. Two NPs are considered to be a part of the same aggregate if the distance between them is less than 1.5σ0. Mw evolution for three different packing fractions (η = 0.005, 0.025, 0.060) are shown in Figure 2. As evident from the figure, aggregate size increases with an increase in η and a single aggregate spans whole simulation box for η = 0.060, indicating the formation of percolated structures. In general,Mw evolves as Mw ∼ tα1 for short times and ∼ tα2 at intermediate times, where
(2)
where rij,cut = 2.5σij is the cutoff distance for Coulombic interactions. The LJ interaction between NPs are of the form UijLJ(r ) kBT
⎡⎛ σij ⎞12 ⎛ σij ⎞6 ⎤ = 4ϵijLJ ⎢⎜ ⎟ − ⎜ ⎟ ⎥ ⎝r ⎠⎦ ⎣⎝ r ⎠
(4) 1/6
We have performed implicit-solvent simulations of solutions containing two NP types, type A (+) and type B (−), with opposite and dissimilar valence zA and zB and different diameters σA and σB, respectively. Number of particles of type A and type B are nA and nB respectively, such that nAzA + nBzB = 0 (global electroneutrality) and nA + nB = NT, where NT is the total number of NPs. NPs interact via a Coulombic interaction and a Lennard-Jones (LJ) interaction, where the latter is used to characterize the soft-core repulsion between NPs and an additional, solvent-mediated hydrophobic interaction (if present). The Coulombic interaction between NPs is modeled using a pairwise screened Coulomb potential25 Uij(r )
⎧U LJ(r ) − U LJ(r ) r ≤ r LJ ij ij ,cut ij ,cut ⎪ ij =⎨ ⎪ 0 r > rijLJ,cut ⎩
(3) 16046
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therefore both exponents α1 and α2 increases. We have also investigated (not shown) the effect of λB (= 40, 10), asymmetric size (σA = 1.5σB), asymmetric charge (zA = −2zB), and system size (NT = 200, 500), but did not find any qualitative difference on the aggregation kinetics. Formation of BHJ Structure. On the basis of aggregation kinetics results discussed above, it was decided to use high η values to study the percolated structures desired for BHJ. Simulations of large number of NPs (NT = 5000) is feasible for these simulations, since we are interested in short-time evolution without ensemble averaging. While percolated structures do form at high η in Figure 2, contacts between NPs of same type are missing due to Coulombic repulsion between NPs of same type. We therefore introduce additional LJ hydrophobic attraction between NPs of same type (ϵLJ AA = ϵBB = 5), by increasing the LJ cutoff distances for AA and BB LJ interactions (rLJ AA,cut = 2.5σA,rBB,cut = 2.5σB). The LJ cutoff distance of AB interaction is unchanged (rAB,cut = 21/6σAB), as they do not have an additional hydrophobic attraction. Figure 3A shows how an initial random configuration evolves to configurations with different domain sizes after time t = 10τ0 for different values of λB. The relative importance of additional hydrophobic attraction compared to the Coulombic repulsion between NPs of same type decreases with an increase in λB, LJ LJ since the strength of LJ interaction (ϵAA , ϵBB ) is fixed. Therefore, the domain sizes of positive and negative NPs decrease and the interfacial area increases with an increase in λB.
Figure 2. Mw as a function of t/τ0 for three different values of η. Markers (η = 0.005 (⊙), 0.025 (●), 0.060 (△)) indicate simulation data and lines indicate power-law fits for different time windows; exponents of these fits are shown on the plot. Typical snapshots at different times for different η are also shown. Mw data in the plot is averaged over 50 different simulations starting with different initial configurations. Model parameters are NT = 100, σA = σB,zA = −zB, λB = LJ 1/6 σij. 80, κ−1 = σ0, ϵLJ ij = 1, and rij,cut = 2
α2 > α1. As η increases, the crossover time from ∼ tα1 regime to ∼ tα2 regime decreases. Also, since α1 < α2, NPs aggregate at slower rate at short times but aggregation rate increases after the crossover time. This increase in aggregation rate is due to the fusion of small NP aggregates that are formed in the first power-law regime. As η increases, average separation between NPs decreases, which results in strong Coulombic force and
Figure 3. (A) Snapshots of morphology after evolving a random configuration for time t = 10τ0 with different λB and keeping other parameters constant. (B) and (C) shows domains of positive and negative NPs separately for λB = 1 and λB = 10 cases. (D), (E), and (F) are the radial LJ distribution functions for AB, AA, and BB pairs, respectively. Other model parameters are σA = σB, rLJ AA,cut = 2.5σA, rBB,cut = 2.5σB, NT = 5000,zA = −zB, LJ −1 κ = σ0, ϵij = 5 and η = 0.3. 16047
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Figure 4. Comparison of morphology between asymmetric size/charge and symmetric case for two different λB. (A and D) Typical snapshots of morphology formed by self-assembly of size- and charge-symmetric NPs (η = 0.3, σA = σB = σ0,zA = −zB) for λB = 1 and 10 respectively. (B, E and C, F) Typical snapshot of morphology formed by self-assembly of size-asymmetric (σA = 1.5σ0, σB = σ0) and charge-asymmetric NPs (zA = −2zB), LJ −1 = σ0, ϵLJ respectively. Other model parameters are rLJ AA,cut = 2.5σA,rBB,cut = 2.5σB,NT = 5000, κ ij = 5, and η = 0.3.
Figure 5. Asymmetric size distribution (A1−A3): Plot of g+−,g++ and g−− for η = 0.3, σA = 1.5, σB = 1, zA = −zB for different λB. Asymmetric charge distribution (B1−B3): Plot of g+−,g++ and g−− for η = 0.3, σA = σB = 1, zA = −2zB for different λB. Peak intensities of g++ and g−− are different for asymmetric size/charge case with same value of λB, which was not the case for the symmetric size/charge case. Change in peak intensities as λB changes is not similar for g++ and g−− and this can be used to separately control the domain sizes of acceptor and donor materials. Other model LJ −1 = σ0, ϵLJ parameters are rLJ AA,cut = 2.5σA, rBB,cut = 2.5σB, NT = 5000, κ ij = 5, and η = 0.3.
interfacial area) for larger values of λB. First peak intensity of g++,g−− decreases and g+− increases as λB increases, which confirms that the number of AA and BB contacts decrease and AB contacts increase with an increase in λB. These correspond to an increase in interfacial area and decrease in domain size of donor and acceptor materials. In fact, for λB = 1,g+− peak vanishes, which indicates the formation of a big single percolated cluster of acceptor and donor materials. This kind of morphology is not suited for BHJ solar cells, as the probability of exciton to reach the interface is less when the domain size is very large and the interfacial area is very small, which results in fewer exciton dissociations and lower PCE. At another extreme (λB = 10 in Figure 3), domain size is least and the interfacial area is maximum, which is also not an efficient
This can be easily visible in parts B and C of Figure 3, where the domains of type A and type B NPs are separately shown for λB = 1 and λB = 10 cases. For λB = 1, domain size of both acceptor and donor are large but the interfacial area is small. On changing λB to 10, domain sizes decrease but the interfacial area increases. To further characterize the resulting BHJ morphology, we computed radial distribution functions (RDFs),g+−(r),g++(r) and g−−(r) (see Figure 3, parts D−F). Intensity of first RDF peak at r/σav ∼ 1 refers to the probability of contacts of NPs of given types (normalized with reference to that in an ideal gas of same η). For example,g+−(r) represents probability of contacts of positive and negative NPs; g+−(1) ≈ 8.4, 5.7, 2.6, 0.9 for λB = 10, 6, 4, 2, implying the formation of more AB contacts (larger 16048
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phobicity,32 and size21,33,34/surface charge20 of NPs. Work in this direction is currently underway.
BHJ morphology because of the hindrance created by nonpercolated small clusters on the charge transport to respective electrode. Efficient morphology corresponds to intermediate values of λB, where both domain sizes and interfacial area are sufficiently large for exciton migration and dissociation. Effect of Asymmetry on BHJ. Finally, we investigated the effect of size- and charge-asymmetry of NPs on BHJ morphology. Snapshots in Figure 4 show the comparison of obtained morphologies of size-asymmetric NPs (σA = 1.5σB,zA = −zB) and charge-asymmetric NPs (zA = −2zB, σA = σB = σ0) with symmetric NPs (σA = σB,zA = −zB) for two different values of λB. In the size-asymmetric case (Figure 4B, Figure 4E), domain size of type A (larger diameter) NPs do not change appreciably when λB value is varied from 1 to 10 but the interfaces become more rugged, whereas domain size of type B NPs (smaller diameter) shows significant change with change in λB. This can be understood by noting that although the repulsive force between both AA and BB pairs increases with an increase in λB, the effect of repulsive force on BB pair is much greater than AA due to lesser center-to-center separation compared to AA. In the charge-asymmetric case (Figure 4C, Figure 4F), domain size of NPs of type A (higher charge) decreases as λB increases, whereas domain size of type B remains almost same but the interfaces become rugged. Here, the repulsive force strength on AA pair is much greater than BB, due to higher valence of type A NP compared to type B. These asymmetric size/charge effects results in net energy change of AA, BB, and AB pairs. This readjustment of energy makes AB pairs more favorable than AA(BB) as compared to BB(AA) pairs in case of size(charge) asymmetric NP system. These effects are more precisely visible in radial distribution plots in Figure 5.
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AUTHOR INFORMATION
Corresponding Authors
*(P.K.J.) E-mail:
[email protected]. *(S.S.) E-mail:
[email protected]. ORCID
Kulveer Singh: 0000-0002-4554-3290 Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS K.S. acknowledges Science and Engineering Research Board (SERB), India (File No. PDF/2016/000442) for financial support. P.K.J. is supported by an INSPIRE award from the Department of Science and Technology (DST), India (No. IFA14/ENG-72). S.S. acknowledges a Faculty Initiation Grant from IIT Roorkee.
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REFERENCES
(1) Thompson, B.; Frechet, J. Polymer-Fullerene Composite Solar Cells. Angew. Chem., Int. Ed. 2008, 47, 58−77. (2) Gunes, S.; Neugebauer, H.; Sariciftci, N. S. Conjugated PolymerBased Organic Solar Cells. Chem. Rev. 2007, 107, 1324−1338. (3) You, J.; Dou, L.; Yoshimura, K.; Kato, T.; Ohya, K.; Moriarty, T.; Emery, K.; Chen, C.-C.; Gao, J.; Li, G.; et al. A polymer tandem solar cell with 10.6% power conversion efficiency. Nat. Commun. 2013, 4, 1446. (4) Halls, J. J. M.; Walsh, C. A.; Greenham, N. C.; Marseglia, E. A.; Friend, R. H.; Moratti, S. C.; Holmes, A. B. Efficient photodiodes from interpenetrating polymer networks. Nature 1995, 376, 498−500. (5) Yu, G.; Gao, J.; Hummelen, J. C.; Wudl, F.; Heeger, A. J. Polymer Photovoltaic Cells: Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions. Science 1995, 270, 1789−1791. (6) Muth, M.-A.; Mitchell, W.; Tierney, S.; Lada, T. A.; Xue, X.; Richter, H.; Carrasco-Orozco, M.; Thelakkat, M. Influence of charge carrier mobility and morphology on solar cell parameters in devices of mono- and bis-fullerene adducts. Nanotechnology 2013, 24, 484001. (7) Lu, L.; Zheng, T.; Wu, Q.; Schneider, A. M.; Zhao, D.; Yu, L. Recent Advances in Bulk Heterojunction Polymer Solar Cells. Chem. Rev. 2015, 115, 12666−12731. (8) (a) Chen, D.; Nakahara, A.; Wei, D.; Nordlund, D.; Russell, T. P. P3HT/PCBM Bulk Heterojunction Organic Photovoltaics: Correlating Efficiency and Morphology. Nano Lett. 2011, 11, 561−567. (b) Satapathi, S.; Yan, F.; Anandakathir, R.; Yang, K.; Li, L.; Mosurkal, R.; Samuelson, L. A.; Kumar, J. Fabrication of Dye-sensitized Solar Cells and Fluorescence Quenching Study Using Thiophene Based Copolymers. J. Macromol. Sci., Part A: Pure Appl.Chem. 2010, 47, 1180−1183. (9) Shen, H.; Valadez-Perez, N. E.; Guralnick, B.; Liu, Y.; Mackay, M. E. Performance enhancement of polymer-based solar cells by induced phase-separation with silica particles. J. Mater. Chem. C 2014, 2, 10087−10100. (10) Garg, M.; Padmanabhan, V. Addition of P3HT-grafted Silica nanoparticles improves bulk-heterojunction morphology in P3HTPCBM blends. Sci. Rep. 2016, 6, 33219. (11) Liu, F.; Gu, Y.; Shen, X.; Ferdous, S.; Wang, H.-W.; Russell, T. P. Characterization of the morphology of solution-processed bulk heterojunction organic photovoltaics. Prog. Polym. Sci. 2013, 38, 1990−2052. Topical issue on Conductive Polymers. (12) Ruder, A. M. Potential Health Effects of Occupational Chlorinated Solvent Exposure. Ann. N. Y. Acad. Sci. 2006, 1076, 207−227. (13) Ulum, S.; Holmes, N.; Darwis, D.; Burke, K.; Kilcoyne, A. D.; Zhou, X.; Belcher, W.; Dastoor, P. Determining the structural motif of
CONCLUSION
In summary, we have performed a systematic study of the formation of BHJ morphology by self-assembly of oppositely charged NPs using kMC simulations. The weight-averaged aggregate size Mw evolves in two power-law regimes - initial clustering of NPs is slow but becomes faster at longer times due to the fusion of small aggregates. With an increase in NP concentration (quantified by the packing fraction η), the aggregate size increases and the number of aggregates decreases, eventually giving rise to a single big, percolated structure at high packing densities. Using these results and introducing additional hydrophobic attraction for NPs of same type, various functional BHJ morphologies are achieved by changing the Coulombic strength between NPs. In experiments, Coulombic strength can be easily controlled either by changing the surface charge on NPs (e.g., using surfactants) or by using solvents of different dielectric constants. Indeed, in blend systems, it has been found that changing the solvent can drastically change the efficiency of the solar cells,31 which has been attributed to a change in morphology at molecular level. The additional hydrophobic attraction introduced in our model is also dependent on the solvent and the constituents of NPs. Moreover, we demonstrate that the domain sizes and interfacial area of acceptor and donor materials may also be controlled by varying the size- and charge-asymmetry of NPs. Our simulation results can therefore be used to develop the design rules for the formation of BHJ structure by experimentally controllable parameters like dielectric constant, salt concentration, hydro16049
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The Journal of Physical Chemistry C P3HT:PCBM nanoparticulate organic photovoltaic devices. Sol. Energy Mater. Sol. Cells 2013, 110, 43−48. (14) Darwis, D.; Elkington, D.; Ulum, S.; Bryant, G.; Belcher, W.; Dastoor, P.; Zhou, X. Novel low voltage and solution processable organic thin film transistors based on water dispersed polymer semiconductor nanoparticulates. J. Colloid Interface Sci. 2013, 401, 65− 69. (15) Gärtner, S.; Christmann, M.; Sankaran, S.; Röhm, H.; Prinz, E.M.; Penth, F.; Pütz, A.; Türeli, A. E.; Penth, B.; Baumstümmler, B.; et al. Eco-Friendly Fabrication of 4% Efficient Organic Solar Cells from Surfactant-Free P3HT:ICBA Nanoparticle Dispersions. Adv. Mater. 2014, 26, 6653−6657. (16) Gehan, T. S.; Bag, M.; Renna, L. A.; Shen, X.; Algaier, D. D.; Lahti, P. M.; Russell, T. P.; Venkataraman, D. Multiscale Active Layer Morphologies for Organic Photovoltaics Through Self-Assembly of Nanospheres. Nano Lett. 2014, 14, 5238−5243. (17) Renna, L. A.; Bag, M.; Gehan, T. S.; Han, X.; Lahti, P. M.; Maroudas, D.; Venkataraman, D. Tunable Percolation in Semiconducting Binary Polymer Nanoparticle Glasses. J. Phys. Chem. B 2016, 120, 2544−2556. (18) Satapathi, S.; Gill, H. S.; Li, L.; Samuelson, L.; Kumar, J.; Mosurkal, R. Synthesis of nanoparticles of {P3HT} and {PCBM} for optimizing morphology in polymeric solar cells. Appl. Surf. Sci. 2014, 323, 13−18. (19) Satapathi, S.; Molla, M. R.; Bhattacharyya, S.; Ghosh, S.; Patra, A. Photophysical study of P3HT/NDI based hybrid nanoparticles. Eur. Phys. J. D 2014, 68, 350. (20) Colberts, F. J. M.; Wienk, M. M.; Janssen, R. A. J. Aqueous Nanoparticle Polymer Solar Cells: Effects of Surfactant Concentration and Processing on Device Performance. ACS Appl. Mater. Interfaces 2017, 9, 13380−13389. (21) Nagai, M.; Huang, J.; Cui, D.; Wang, Z.; Huang, W. Two-step reprecipitation method with size and zeta potential controllability for synthesizing semiconducting polymer nanoparticles. Colloid Polym. Sci. 2017, 295, 1153. (22) Watkins, P. K.; Walker, A. B.; Verschoor, G. L. B. Dynamical Monte Carlo Modelling of Organic Solar Cells: The Dependence of Internal Quantum Efficiency on Morphology. Nano Lett. 2005, 5, 1814−1818. (23) Meng, L.; Shang, Y.; Li, Q.; Li, Y.; Zhan, X.; Shuai, Z.; Kimber, R. G. E.; Walker, A. B. Dynamic Monte Carlo Simulation for Highly Efficient Polymer Blend Photovoltaics. J. Phys. Chem. B 2010, 114, 36−41. (24) Groves, C. Simulating charge transport in organic semiconductors and devices: a review. Rep. Prog. Phys. 2017, 80, 026502. (25) Leunissen, M. E.; Christova, C. G.; Hynninen, A.-P.; Royall, C. P.; Campbell, A. I.; Imhof, A.; Dijkstra, M.; van Roij, R.; van Blaaderen, A. Ionic colloidal crystals of oppositely charged particles. Nature 2005, 437, 235−240. (26) Sanz, E.; Leunissen, M. E.; Fortini, A.; van Blaaderen, A.; Dijkstra, M. Gel Formation in Suspensions of Oppositely Charged Colloids: Mechanism and Relation to the Equilibrium Phase Diagram. J. Phys. Chem. B 2008, 112, 10861−10872. (27) Sanz, E.; Valeriani, C.; Vissers, T.; Fortini, A.; Leunissen, M. E.; van Blaaderen, A.; Frenkel, D.; Dijkstra, M. Out-of-equilibrium processes in suspensions of oppositely charged colloids: liquid-tocrystal nucleation and gel formation. J. Phys.: Condens. Matter 2008, 20, 494247. (28) Jha, P. K.; Kuzovkov, V.; Grzybowski, B. A.; Olvera de la Cruz, M. Dynamic self-assembly of photo-switchable nanoparticles. Soft Matter 2012, 8, 227−234. (29) Jha, P. K.; Kuzovkov, V.; Olvera de la Cruz, M. Kinetic Monte Carlo Simulations of Flow-Assisted Polymerization. ACS Macro Lett. 2012, 1, 1393−1397. (30) Zhang, R.; Jha, P. K.; Olvera de la Cruz, M. Non-equilibrium ionic assemblies of oppositely charged nanoparticles. Soft Matter 2013, 9, 5042−5051.
(31) Shaheen, S. E.; Brabec, C. J.; Sariciftci, N. S.; Padinger, F.; Fromherz, T.; Hummelen, J. C. 2.5% efficient organic plastic solar cells. Appl. Phys. Lett. 2001, 78, 841−843. (32) Wu, Z.; Han, H.; Han, W.; Kim, B.; Ahn, K. H.; Lee, K. Controlling the Hydrophobicity of Submicrometer Silica Spheres via Surface Modification for Nanocomposite Applications. Langmuir 2007, 23, 7799−7803. (33) Lee, H.; Chung, M.; Ahn, H.-G.; Kim, S.-J.; Park, Y.-K.; Jung, S.C. Effect of the surfactant on size of nickel nanoparticles generated by liquid-phase plasma method. International Journal of Precision Engineering and Manufacturing 2015, 16, 1305−1310. (34) Fricke, M.; Voigt, A.; Veit, P.; Sundmacher, K. MiniemulsionBased Process for Controlling the Size and Shape of Zinc Oxide Nanoparticles. Ind. Eng. Chem. Res. 2015, 54, 10293−10300.
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