Solution Processing Dependent Bulk Heterojunction Nanomorphology

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Solution processing dependent bulk heterojunction nanomorphology of P3HT: PCBM thin films Joydeep Munshi, Rabindra Dulal, TeYu Chien, Wei Chen, and Ganesh Balasubramanian ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.9b02719 • Publication Date (Web): 09 Apr 2019 Downloaded from http://pubs.acs.org on April 11, 2019

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ACS Applied Materials & Interfaces

Solution processing dependent bulk heterojunction nanomorphology of P3HT: PCBM thin films Joydeep Munshi1, Rabindra Dulal2, TeYu Chien2, Wei Chen3, and Ganesh Balasubramanian1* 1

Department of Mechanical Engineering & Mechanics, Lehigh University, Bethlehem, PA, USA 2

3

Department of Physics & Astronomy, University of Wyoming, Laramie, WY, USA

Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA

Keywords Organic solar cell, P3HT: PCBM, Coarse grain molecular dynamics, X-ray diffraction, Small angle X-ray scattering (SAXS)

Abstract Mixtures of poly-(3-hexyl-thiophene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM) have been widely employed as donor and acceptor materials, respectively, for the active layer of the bulk heterojunction (BHJ) organic solar cells. Experiments are able to provide only limited insights on the dynamics of blend morphology of these organic materials because of the

*

Corresponding author. Email: [email protected]. Phone: +1-610-758-3784.

Address: Packard Laboratory 561, 19 Memorial Drive West, Bethlehem, PA 18015, USA.

ACS Paragon Plus Environment

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challenges in extracting microstructural characterization amidst the poor contrast in electron microscopy. We present results from coarse-grained molecular dynamics simulations (CGMD) describing the morphological evolution of P3HT:PCBM active layer under solution processing in chlorobenzene (CB). We examine the impact of various processing parameters such as weight ratio, degree of polymerization (DOP), thermal annealing and pre-heating on the BHJ active layers using morphological characterizations from atomic trajectories. Simulated diffraction patterns are compared with experimental results of X-ray diffraction and Small Angle X-ray Scattering (SAXS). Both simulated scattering and experimental X-ray diffraction and X-ray scattering measurements reveal increase in crystallinity for P3HT upon annealing until PCBM weight fraction ~ 50%. The solubility of PCBM being greater in CB than that of P3HT facilitates the phase separation of the polymer during early stages of solvent evaporation. An increase in the average size of the P3HT domain relative to the pre-annealed morphology, is due to phase segregation and crystallization of the polymer upon annealing. Percolation for PCBM remains unchanged until PCBM constitutes at least one-half of the composition. Although 1.0:2.0 weight ratio is predicted to be ideal for balanced charge transport, 1.0:1.0 weight ratio is the most beneficial of overall power conversion based on exciton generation and charge separation at the interface. DOP of P3HT molecules is another important design variable as larger P3HT molecules tend to entangle more often deteriorating molecular order of P3HT phase in the active layer. Pre-heating the ternary mixture of P3HT, PCBM and CB modifies the structural order and morphology of the BHJ due to changes in PCBM diffusion into the P3HT phase.


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I.

Interface of the bulk heterojunction active layer Solar power has emerged as an attractive renewable energy source due to its abundance,

relatively low environmental impact and negligibly small CO2 emission. Photovoltaic (PV) solar cells that convert solar energy to electricity have shown tremendous promise as a technology, especially over the last decade 1,2. Amongst the different materials considered, organic solar cells (OSCs) based on electron-donor semiconducting polymers

3-7

have received significant interest

due to their solution processability, low weight and device flexibility 8-10. The most efficient OSCs contain interpenetrating phases (bulk heterojunction, a.k.a. BHJ, photoactive layer) of the electrondonor semiconducting polymer and electron-acceptor fullerene materials 11,12. The solar energy to electricity conversion efficiency (PCE) depends not only on the electronic properties of the acceptor and donor materials 14,15

13

but also the morphology and dynamics of the BHJ active layers

. Hence, optimization of the vast parameter space affecting the microstructures of BHJ active

layers is crucial to improve the efficiencies of OSCs. Despite recent advances in experimental as well as computational research towards morphological characterization of these devices there exists a shortfall in the obtained device efficiencies of polymer-fullerene BHJ solar cells. Although these polymer-fullerene based BHJ devices suffer from relatively low PCE (~10%)

8-10

, recent

advances in non-fullerene and all non-polymeric small molecule based BHJ devices have demonstrated further improvements in PCE ~ 15% 16-18. When light is absorbed in the BHJ photoactive layer excitons are formed (bound electron-hole pair) in the donor polymer, followed by diffusion of quasistable excitons to the donor-acceptor interface and finally exciton dissociate as electrons and holes that migrate to the respective electrodes 19. Therefore, for enhancing the power conversion in BHJ photovoltaic cells, efficient charge separation (exciton dissociation) at the donor-acceptor interface, preventing charge


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(exciton) recombination and increasing electron (hole) mobility in the acceptor (donor) are extremely important

20

. A greater donor-acceptor interfacial area facilitates efficient charge

separation, while domain sizes compatible with the exciton diffusion length (e.g. ~ 5.4 nm in P3HT) 7,21 impede charge recombination. Poly-(3-hexyl-thiophene) (P3HT) in combination with phenyl-C61-butyric acid methyl ester (PCBM) have been explored over the past decade as promising donor and acceptor materials because of their notable thermal and mechanical stability in the BHJ 22-39. A bi-continuous interpenetrating network of P3HT and PCBM is achieved by spin coating a ternary mixture of P3HT, PCBM and chlorobenzene (CB) and hence, the final nanomorphology of the photoactive layer with the solvent-free mixture depends on the processing 15,40

.

Experimental characterization of the 3-dimensional morphology of the BHJ active layer is challenging, and the poor contrast of the reconstructed morphology due to weak electron scattering of organic materials is a major limitation of the microstructural imaging by electron microscopy. On the other hand, coarse-grain molecular dynamics (CGMD) simulations of the BHJ can reproduce detailed morphology of the active layers with nanoscale resolution

41-56

. Here, we

present results from CGMD simulations of the solvent evaporation of pre-heated P3HT:PCBM mixture in CB followed by thermal annealing of solvent-free P3HT:PCBM bulk heterojunction photoactive layers. X-ray diffraction (SAXS and XRD) measurements are employed to compare simulated scattering profiles found for P3HT: PCBM BHJ with different weight ratios. The effects of different compositions, degree of polymerization (DOP) and pre-heating on the solvent-free and annealed morphologies are examined to correlate the microstructural parameters to the OSC performance. The shortest exciton diffusion path to prevent loss of excitons and the highest interfacial area for enhanced exciton dissociation is found for compositions with ~ 1:1 weight ratio


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of P3HT and PCBM. While the processing parameters and the annealing temperature affect the blend morphology and crystallinity of P3HT phase, and consequently the device performance, the DOP for the organic molecules does not exert a notable influence beyond a threshold chain length. II.

Coarse-grained molecular dynamics simulations

The advantage of CGMD computations that employ molecular models composed of beads representative of multiple atomic sites is in the reduced degrees of freedom of the overall system, enabling simulations of larger samples and for longer times. We note that several efforts in the literature examine the effect of solution processing parameters ––– solvents

44,46,55,57-59

,

evaporation rates 44,52,57 , weight ratios of the polymeric mixtures 43,45,47,50,52,55,57 , small molecule additives to the mixture

48,51

, thermal annealing

42,43,47,52,55,60

––– on BHJ morphology and the

performance of P3HT:PCBM thin film solar cells. However, these CGMD simulations 42,43,46,47,50 lack the chemical specificity in the modeling of the P3HT monomer, particularly the thiophene ring that is represented as a single CG bead at its center of mass (COM). The recently developed Martini CG force field, although computationally intensive, is able to restore the anisotropic π-π interaction between the adjacent backbones of the thiophene rings 53. Our CGMD simulations that employ the Martini potentials

53

for P3HT, PCBM and CB molecules (Figure 1), improve the

earlier predictions providing accurate estimates of interface properties in the BHJ. A. Simulation procedure P3HT, PCBM and CB molecules are coarse grained into beads using the Martini force field extended to polymers

53,61,62

, fullerene (carbon based nanoparticles)

63

and benzene rings,

respectively. Typically, 4 atoms are mapped to one CG bead, except for the thiophene rings in P3HT and the fullerene cage in the PCBM molecule where approximately 2-3 atoms are represented together by one CG bead, as shown in Figure 1. Details of force field parameters for


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bonded (bond, angle, torsional and dihedral) and non-bonded interactions are available in reference 52

. We perform CGMD simulations for solvent evaporation in a mixture of P3HT:PCBM dissolved

in CB. The respective number of molecules and geometry of the initial and final simulation boxes are listed in Table 1. P3HT chains with varying DOP of 24, 48, 72 and 120-mers are randomly inserted into simulation cell followed by PCBM molecules with different weight fractions. Finally, the mixture containing randomly placed P3HT and PCBM molecules is solvated in CB. A simulation box of 15 nm × 15 nm × 44 nm with periodic boundary conditions in all directions is initially occupied by CG beads of P3HT, PCBM and CB with P3HT:PCBM weight ratios of 1.0:0.08, 1.0:0.5, 1.0:0.8, 1.0:1.0, 1.0:2.0 and 1.0:8.0. The pre-heating temperature for the ternary mixture is varied (T= 298K, 323K, 348K and 373K) and its effect on the final morphology is discussed. All simulations are performed using GROMACS 5.1.2 code 64. B. Simulated solvent evaporation The simulated solvent evaporation procedure follows from the literature

44,48,52,57

. The P3HT:

PCBM mixture solvated in the organic solvent (CB) is initially energy minimized employing the steepest descent algorithm with a time step of 20 fs (20×10-15 s) and a Lennard-Jones (LJ) cut-off radius of 1.1 nm (1.1×10-9 m). In general, the Martini force field has been developed using group scheme with a shift function for continuous and differentiable potential across LJ cutoff distance (rcut = 1.2 nm) 65,66. However, recent research efforts modeling the polymers using the CG scheme 52,61

have explored a more efficient Verlet scheme for updating neighbor lists (introduced through

Gromacs 4.6) with a reduced LJ cutoff distance of 1.1 nm. In this work, we have employed Verlet cutoff scheme with LJ cutoff distance varied between 1.1 to 1.4 nm. We have found good agreement of P3HT density to the experimental data even with the LJ cutoff distance = 1.1 nm. Next, the geometrically optimized structures are initiated with a constant initial temperature (T =


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298K, 323K, 348K and 373K) under the canonical (NVT) ensemble for 500 ps (picoseconds) followed by an equilibration under isothermal-isobaric (NPT) ensemble for 4 ns at constant temperature and constant atmospheric pressure constrained by weakly-coupled Berendsen thermostat and barostat with coupling constant of 2 ps-1. Relaxation of an optimized structure to equilibrium at a reference initial temperature and pressure under weakly coupled thermostat such as Berendsen is a rational choice although it leads to inaccurate canonical velocity distribution. We observe oscillatory behavior when the equilibration process is simulated under Nose-Hoover or velocity-rescale thermostat and Parrinello-Rahman barostat. In contrast, the equilibrated and relaxed BHJ structure is obtained using Berendsen thermostat that dissipate energy fluctuations by employing strong exponential damping. Finally, molecular dynamics (MD) simulations using the leap-frog algorithm are performed to simulate the solvent evaporation process. During the evaporation process, the thermostat and barostat are respectively constrained by the velocityrescaling and Parrinello-Rahman methods with a coupling constant of 15 ps-1. Choice of velocityrescale thermostat over Nose-Hoover for evaporation and thermal annealing simulations are due to the trade-off between efficiency and computation time. It is observed that these two thermostats are efficient in simulating the morphology but velocity-rescale thermostat is significantly fast in converging to the final morphology. Additional simulation details are listed in Table 3. Approximately 1.25% of available CB molecules are randomly removed from the mixture at regular time intervals of 3 ns, followed by 4 ns of equilibration under the NPT ensemble until all CB molecules are evaporated from the system. With this evaporation rate, the solvent-free morphology is achieved after 1.1 µs of simulation for the 1:1 P3HT:PCBM BHJ. As the number of initial solvent molecules varies for different blend compositions (shown in Table 1), the overall evaporation time required for BHJ layers decreases with higher PCBM weight fraction. In general,


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solvent-free morphologies are attained after 1 µs. Solvent molecules are evaporated randomly from the bulk mixture despite the fact that evaporation is a surface phenomenon. This is considered to be a valid assumption because due to rapid equilibration of the system concentration gradient along the thickness inside the ternary mixture of the polymer, the fullerene and the solvent is negligible. The solvent evaporation process is performed at different initial temperature conditions (to mimic pre-heating), and the solvent-free pre-heated mixtures at 323, 348 and 373 K are subsequently quenched to 298 K at a cooling rate of 1 K/ns. C. Thermal annealing simulation P3HT:PCBM BHJ solar cells require annealing to attain their full potential

67

. Annealing

enhances polymer crystallization, which improves both optical absorption and charge transport and optimizes phase segregation leading to efficient charge separation at the interface. After complete evaporation of the solvent molecules, we simulate the thermal annealing process on each of the solvent-free mixtures. The simulation cell is equilibrated under an NVT ensemble at a T = 298K for 500 ps constrained by Berendsen thermostat. Further equilibration is performed under an NPT ensemble at 298 K and atmospheric pressure for 4 ns constrained by Berendsen thermostat and barostat similar to solvent evaporation simulations. Then, MD simulations are performed on the equilibrated P3HT:PCBM mixture by gradually increasing the temperature to 498K at a rate of 20 K/ns, to 598K at 5 K/ns and to 698K at 2 K/ns with similar thermostat and barostat as evaporation MD simulations discussed above. Subsequently, the heated mixture is maintained at a constant temperature for 1.7 µs to simulate the annealing process. Finally, the annealed mixture is quenched to 298K at a rate of It is worth noting that in our XRD data (Figures 6 a, c, and e), no P3HT 8 K/ns. In general, a mean time-scaling factor of ~ 4 is obtained with Martini CG model in comparison to all-atom simulations. 52,65,66. Overall, the BHJ blend morphology obtained from CG


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solvent evaporation and thermal annealing simulations (> 3 µs) is equivalent to ~ 12 µs of all-atom MD simulation time. We note that the temperature during experimental annealing is typically ~ 373-423K

68

; the higher temperature employed in our simulations is to compensate for the

differences in the associated time scales (minutes in experiments versus microseconds in the simulations) and achieve comparable microstructural trends. D. Morphological characterization The discretization of 3-dimensional morphology found from experimental characterization 69,70 or CGMD simulations 43,52 assists in correlating processing parameters to the performance of the device. Here, we discretize the simulation box into 0.5×0.5×0.5 nm3 cubes (a.k.a. voxels). A consistent voxel dimension is chosen relative to the CG bead diameter of P3HT and PCBM. Initially, in each voxel the number of P3HT or PCBM beads are calculated followed by assigning ‘0’s and ‘1’s to the 3-dimensional geometry (depending upon the type of bead being PCBM or P3HT, respectively). Figure 2 reproduces the discretized image of P3HT:PCBM BHJ morphology for 1.0:0.08, 1.0:0.8 and 1.0:8.0 weight ratios of P3HT and PCBM, respectively, sampled along the z-direction. All the simulation results are visualized using VMD 71 and discretized for further characterization using MATLAB 2017b. Calculations of domain size, interfacial area to volume ratio (IAVR), percolation ratio and shortest distance to the interface for an exciton are obtained by post processing the discretized morphologies. E. Simulated diffraction pattern Scattering curves provide visual measure of the crystallinity of the P3HT chains in the BHJ active layer. A strategy to compute simulated scattering diffraction from CGMD simulations is adopted from 52 by considering only the backbone thiophene rings of all polymer chains. Usually π-π interactions between P3HT polymer chains are responsible for aromatic π-stacking (010)


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perpendicular to backbone thiophene rings. Additionally, P3HT exhibits lamellar stacking (100) along the backbone thiophene rings. However, there is usually no directional order along 001 direction due to the presence of disordered and liquid-like alkyl side chains

72,73

. Hence, it is

sufficient to consider center of backbone thiophene rings as center of mass (COM) of P3HT monomers to simulate the diffraction pattern. The distances between the center of mass of all thiophene molecules are computed and stored in N×N matrix, N being the total number of thiophene rings. Occurrences of a particular measured distance are binned across the simulation cell, and a histogram of occurrence as a function of distance is analyzed. Finally, Fourier transform of the distribution is computed assuming the scattering intensity in reciprocal space as: I(q) ~ 2

|∑N j=1 Zj exp(iq − rj )| , where Zj is atomic number of atom j, q is reciprocal space vector and rj is position vector of atom j. A python script 52 along with the MDAnalysis package 74 is used to obtain the distance matrix and its Fourier transform to find the scattering intensity as discussed in section 4. III.

Experimental methods

A. Sample Preparation Solutions containing 20 mg P3HT/ 1 mL of CB (purity ≥ 99.5%, Sigma-Aldrich) and 20 mg PCBM/ 1 mL of CB is prepared and mixed in 1.0:0.5, 1.0:1.0 and 1.0:2.0 weight ratio. The solutions are spin coated onto the Si(100) substrate with 1,050 rpm for 1 minute. The films containing P3HT: PCBM/Si(100) are finally annealed at 423K for 5 min inside the glove box. B. X-ray diffraction (XRD) measurement The Small Angle X-ray Scattering (SAXS) and the X-ray diffraction (XRD) are measured with a Rigaku Smartlab diffractometer with Cu target (Kα wavelength of 1.542 Å). SAXS were measured from 0° to 2° (2θ) with scan step of 0.0052° and from 4° to 12° (2θ) for general XRD


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measurements with scan step rate of 0.05°. For further analysis, the 2θ values are changed to q value (in reciprocal space) using the relation, 𝑞 =

4𝜋𝑠𝑖𝑛θ 𝜆

. Finally, the intensity is plotted as a

function of q for comparison. IV.

Results and Discussion

A. Morphology evolution during solvent evaporation The CGMD simulation for solvent evaporation is performed at a fixed rate of 6.57 g/cm2.min, faster than that typically employed in spin-coating process (~ 1.9 × 10-4 g/cm2.min)

75

. The

difference between evaporation rates is compensated by the reduction in the degree of freedom due to coarse-graining. Table 1 lists the final thickness of BHJ film for different compositions. The thickness of the BHJ is observed to increase with increasing weight fraction of PCBM phase in the blend film, but the thickness does not vary with changes in the DOP for the same composition. Additional details on morphological properties such as density, volume fraction of individual phases and void fraction are presented in Table 2. Figures 3(a)-(b) reproduce the evolution of the morphology from initial ternary mixture to a solvent-free P3HT:PCBM binary BHJ film. Initially, P3HT and PCBM molecules are observed to diffuse homogeneously into the CB. When the solvent molecules begin to evaporate, P3HT and PCBM start to agglomerate into small domains as observed in Figure 3(a). As solubility of PCBM is higher in CB than that of P3HT 76, only P3HT phase segregates at an early stage during solvent evaporation. This assertion can be verified from the initial decrease in the PCBM:PCBM contacts as presented in Figure 3(c). Once the solvent concentration is reduced to less than 50% of the initial concentration the fraction of PCBM:PCBM and P3HT:P3HT contacts are decreased while P3HT:PCBM interactions are enhanced in absence of CB molecules 52. Figure 4(a) reproduces the final morphology of the P3HT:PCBM blend after complete evaporation of the solvent.


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B. Morphology evolution during thermal annealing Figure 4(b) shows the annealed morphology of the solvent-free mixture. We observe enhanced ordering in the P3HT chain stacking, in concurrence with previous computational

52

and

experimental reports 67. Average size of the P3HT domain is also increased, in comparison to the pre-annealed morphology, due to phase segregation of the polymer from the fullerene

55

. We

compare the average domain size (Figure 5(a)) and IAVR (Figure 5(b)) for the annealed and ascast (pre-annealed) morphologies. Increase in P3HT domain size for weight ratio ~ 1.0:1.0 is observed for the annealed morphology due to increased crystallinity. To further examine the effect of thermal processing, we compute simulated diffraction scattering curves, as shown in Figures 6 and 7, considering center of the thiophene rings as center of mass (COM) of P3HT monomers. Simulated scattering profiles of all annealed samples reveal an increase in the intensities of the lamellar (100) peaks (as presented in table 4), while those for the as-cast morphologies produce weak lamellar (100) intensities77. Similar trend is observed from the experimental XRD measurements as shown in Figure 6 (a), (c) and (e). In particular, for 1.0:0.5 weight ratio (Figure 6 (a)), the annealed samples exhibited stronger and sharper lamellar (100) peak compared to the unannealed sample. In addition, this peak is found to be shifted toward a lower q value compared to the unannealed case. Similar down shifting is observed in the simulated stacking (010) peak (Figure 6 (b)). For the 1.0:1.0 weight ratio case (Figure 6 (c)), no obvious peak intensity change is found between the lamellar (100) peaks in the annealed and unannealed samples, but a down shifting is observed in the annealed sample. Similarly, a down shifting is found in the stacking (010) peak in the simulated data. And finally, for the 1.0:2.0 weight ratio case (Figure 6 (e)), no lamellar (100) peak is observed in the unannealed sample while the annealed sample exhibited a very small, broad hump, which is consistent with the simulated data. It is worth noting that in our


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XRD data (Figures 6 a, c, and e), no P3HT (010) peak is observed and hence not shown in the figure (out of the displayed range), although this P3HT (010) peak is observed in the CGMD simulation (~1.7 A-1). This peak is associated with the face-on stacking of the P3HT polymers and is rarely observed in the P3HT-PCBM mixture

78

. Even when it is observed in GIXRD

79

, the

intensity of the P3HT (010) peak is much smaller than that of the P3HT (100) peak. While this phenomenon is interesting, it is out of the scope of our current study. The XRD data is analyzed and summarized in Table 4. As P3HT molecules are increasingly ordered due to increase in crystallinity (strong stacking or lamellar peaks), PCBM molecules intermixed with amorphous P3HT are forced to segregate and hence domain sizes for both P3HT and PCBM expand upon annealing 55. This can be attributed to the fact that in case of 1.0:2.0 P3HT: PCBM mixture the amorphous PCBM is dominant which is responsible for decrease in peak intensity upon annealing. There is slight variation in the peak positions between the experimental XRD and the simulated scattering as the latter does not take into account the presence of any residual chlorobenzene solvent. A similar trend is reflected in Figure 5(a) which shows no increase in average domain size between annealed and as-cast morphologies for compositions where P3HT or PCBM is in excess. To gain further information about the domain sizes and domain correlation, SAXS as well as small q simulated scattering profiles are compared. Figure 7 shows the SAXS and small q simulated scattering profiles for 1.0:1.0; 1.0:0.5; and 1.0:2.0 weight ratio cases of P3HT: PCBM blend. It is surprising that the peak observed in Figure 7 at ~0.03-0.04 Å−1 is much stronger than what has been typically reported in the literature. However, similar strong peaks have been noted in some P3HT:PCBM mixtures 80 and other polymers 81, indicating that it is quite possible to obtain such data. In addition, the peak position observed here (~0.03-0.04 Å−1 ) corresponds to what has


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been reported for P3HT:PCBM cases 79,80,82. Also, the peak height, peak position and width of this peak show dependence on the processing conditions (P3HT:PCBM ratio and annealing process). All of these results indicate that the observed strong peak in Figure 7 is indeed associated with the long-range domain correlations in P3HT:PCBM. - Overall, the simulation and the SAXS do not show similar peak positions. However, qualitative agreements could be found. The key quantities to compare here are: (1) I(q) decay rate when q close to 0; and (2) the peak positions located at finite q values. The former is related the domain sizes; while the latter is related to the domain separations. For the 1.0:0.5 weight ratio case, there is an upshift in the peak position for the annealed compared to the unannealed case; while the I(q) decay behavior near q = 0 is overlapping to each other. This indicates that the annealed sample showed closer domains while the domain sizes are relatively similar. However, this is not consistent with the simulated small q scattering profile (Figure 7 (b)), in which a downshift for the annealed case is observed. On the other hand, for the 1.0:1.0 weight ratio case, there is no peak observed in the unannealed sample; while a peak is observed after annealing. This is consistent with the simulated small q scattering profile (Figure 7 (d)). And finally, for the 1.0:2.0 weight ratio case, the unannealed sample exhibited stronger peak compare to the anneal sample. Though a small hump, rather than a strong peak, is found in the simulated small q scattering profile, it is qualitatively agreed with the SAXS data. With these comparisons between the experimental SAXS and the simulated scattering profile data, one may see that the CGMD simulation captured major nanostructure information and agree with the experimental data significantly. Important trends could be studied by CGMD for situations that experiments hardly able to address, such as the effects of the DOP on the morphology. The effect of the DOP on crystallization of the annealed morphology is presented in Figure 8. Lower DOP, i.e. shorter chain lengths, is found to crystallize more readily as noted from the higher


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intensity of the stacking peaks for 24-mer P3HT:PCBM morphology. With increasing polymerization both lamellar and stacking peaks diminish indicating a relatively less ordered morphology. C. Effect of weight ratio We perform CGMD simulations with different weight ratios of P3HT and PCBM to investigate effect of PCBM composition on the morphology during solution processing. We spatially discretize the morphology derived from the molecular trajectories of the CGMD computations to obtain the domain size, IAVR, percolation ratio and shortest exciton diffusion length. Figure 9 compares snapshots of the annealed morphologies for different mixture compositions of the P3HT:PCBM blend. Although final dimensions of the simulation cells for these different cases are not same because of the differences in total number of solvent molecules initially considered, a qualitative comparison between the amount of P3HT and PCBM in the final morphology can be obtained such planar discretization. The stacking of P3HT molecules for 1.0:0.8 and 1.0:0.08 weight ratios is more pronounced relative to 1.0:8.0 P3HT:PCBM composition as observed from the simulated diffraction. An enhanced intermixing of the constituents in 1.0:0.8 leads to the interfacial area and domain sizes of the acceptor and donor phases to be well balanced, unlike for weight ratios of 1.0:0.08 and 1.0:8.0 where either a P3HT or a PCBM domain predominantly occupies the blend with the other molecule only present as a minority phase. We further investigate effect of weight ratios on morphology by examining three additional cases with weight ratios in the neighborhood of 1.0:0.8. Figure 10(a) shows the IAVR of P3HT:PCBM blend for different weight ratios. The greatest interfacial contact is achieved for P3HT:PCBM = 1.0:1.0. Higher IAVR corresponds to increased charge dissociation and hence enhanced performance. Likewise, from Figure 10(b) that shows the percolation ratio of P3HT and PCBM,


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we find that P3HT percolation is relatively higher for lower weight fraction of PCBM, as can be expected intuitively. However, percolation for PCBM remains unchanged until PCBM constitutes at least one-half of the composition. For weight ratio of 1.0:2.0, percolations for both P3HT and PCBM are almost equal, indicating this composition to be an optimum for efficient electron and hole percolation. Figures 10(c) and (d) respectively show average domain size of each phase and shortest distance an exciton has to travel to reach the interface before it recombines. Average domain size for P3HT and PCBM concurs with previous experimental (~13-15 nm) computational results

43

83,84

and

. As exciton recombination is inevitable due to their charge instability

(strong Columbic interaction), a smaller P3HT domain size corresponds to lower diffusion length for excitons leading to enhanced performance. Although P3HT domain size decreases with increasing weight fraction of PCBM, the latter also increases PCBM domain size. Larger PCBM domain size can cause loss of electrons through non-geminate charge recombination before they reach their respective electrodes, thereby resulting in reduced charge transport. One of the major modes of charge recombination in thin film OSC is non-geminate recombination, where the electrons and holes are not bound unlike excitons, in contrast to geminate recombination85-88. Although non-geminate recombination process and its correlation to the trap states in PCBM domain is inconclusive in the literature, it is observed that long path (high percolation ratio) and large domains (large domain size) of PCBM increase the likelihood of the non-geminate recombination89,90. As BHJ layer consisting of higher weight fraction of PCBM tends to evolve towards a final morphology with larger domain size of PCBM, it increases the probability of electron loss through non-geminate recombination. Hence, the required balance between domain sizes is achieved for a weight ratio of 1.0:1.0.


16

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In Figure 10(d), we present the shortest distance to the interface for an exciton that is randomly generated inside P3HT domain upon absorption of photons. Our prediction is consistent with the experimental exciton diffusion length found for P3HT (~ 5.4 nm)

21

. In general, a randomly

generated exciton has to diffuse less with increasing fraction of PCBM before it finds an interface minimizing loss due to recombination. However, the smaller domain size of P3HT for higher weight fractions of PCBM generates an insignificant number of excitons. Thus, a tradeoff between the shortest distance to interface and domain size is necessary. Our results suggest that, although percolation of PCBM is not significant in a P3HT:PCBM film of 1.0:1.0 weight ratio, due to higher interfacial area, high P3HT percolation and ideal domain size of P3HT and PCBM, weight ratios ~ 1.0:1.0 should be realized after processing to enhance the overall power conversion efficiencies of OSC devices. D. Effect of degree of polymerization (DOP) Figure 11 illustrates the nanomorphology of solution processed and annealed P3HT:PCBM mixtures at different initial temperatures for polymer chains with 24, 48, 72 and 120-mers. Shorter P3HT chains (24-mer) in Figures 11 (a)-(d) have significantly high molecular order that can be attributed to the reduced entanglement in small polymer molecules, also resulting in an lower fraction of amorphous P3HT:PCBM mixed phase. Longer chains, however, due to entanglement, achieve less ordered molecular arrangement leading to higher fraction of amorphous phase. Figure 12(a) represents the 3-dimensional (3D) distribution of the crystalline P3HT phase (%) as a function of DOP and pre-heating temperatures. We observe a decrease in P3HT phase order with increase in chain length for pre-heating temperature T = 298 K and 323 K. These observations agree with the above analysis of results presented in Figure 11. However, for pre-heating temperatures T = 348 K and 373 K, similar trend is not observed likely owing to the change in


17


Page 18 of 56

miscibility of P3HT in PCBM for different initial temperature of the blend in solution. The highest fraction of crystalline P3HT phase is recorded for 24-mer P3HT with an initial temperature of 298 K and 323 K as shown in Figure 12(a). Enhanced ordering of the P3HT phase for 24-mer P3HT:PCBM BHJ contributes to larger domains and smaller interfacial areas (the morphology illustrated in Figure 11). Domains much larger than the diffusion length of excitons and insignificantly small interfacial areas are not suitable for energy conversion as it leads to large recombination loss. From a visual inspection of Figure 11, we conjecture that performance of OSCs will improve if P3HT:PCBM active layer is designed with DOP greater than or equal to 48. Figure 12(b) shows 3D-illustration representing the variation of IAVR with changes in DOP and initial pre-heating temperature. While IAVR alters significantly from 24-mer to 48-mer P3HT in the blend, the variation is less profound for chain lengths greater than 48-mer (i.e., molecular weight 8 kDa), in agreement with experimental findings80 that demonstrate negligible dependence on P3HT molecular weight above 10 kDa. The IAVR trend is independent of different initial temperatures (representing pre-heating) indicating increase in IAVR with increase in DOP. The relatively less overall change in IAVR with polymerization for a higher pre-heating temperature, as observed in Figure 12(b), can be attributed to the longer P3HT chain length; i.e. heavier the molecule less mobile they are in the blend. We observe that for the 24-mer P3HT pre-heating does enhance the IAVR and hence the performance of the active layer when the blend is initially preheated. However, 48-mer and 72-mer of the polymer in P3HT:PCBM indicate a transition in IAVR trend as a function of initial temperature. Finally, for 120-mer P3HT:PCBM the trend is reversed with increasing pre-heating temperature indicating a potential deterioration in power conversion efficiency. V.

Conclusion


18

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We describe the impact of different processing parameters on the bulk heterojunction morphology of P3HT:PCBM based organic solar cells, using coarse-grained molecular simulations. In particular, we focus on the compositions of the constituent donor and acceptor materials, degree of polymerization of P3HT, thermal annealing and the initial temperature (preheating) of the ternary mixture (P3HT, PCBM and CB). Given that choice of solvent can influence the BHJ morphology because of variable solubility of constituent donor/acceptor materials in the solvent, our results suggest that the morphology derived after solvent evaporation is strongly dependent on the blend composition. Our predictions from simulated diffraction patterns reveal that annealing of the solvent-free polymer-fullerene mixture enhances the intermixing between P3HT and PCBM phases for weight ratios ~1.0:1.0 indicating a balanced exciton generation, charge dissociation and charge transport which is validated with experimental XRD measurements too. The effect of annealing is predominantly noted for shorter polymer chains (DOP < 48) as these small polymer molecules are able to rearrange rapidly upon heating. On the other hand, longer polymer chains tend to entangle, and hence the fraction of amorphous P3HT phase in the BHJ layer is significantly higher. Additionally, we examine pre-heating temperature as a design variable since it can modify the structural ordering of the BHJ layer. While pre-heating does not affect the molecular arrangements in shorter polymer chains as observed from the change in fraction of crystalline P3HT, IAVR is observed to increase with increase in temperature for shorter chains.


19


Page 20 of 56

Tables Table 1: Simulation details for the various cases simulated are listed. The number of P3HT, PCBM and CB molecules for the different compositions and different DOP (chain length) of P3HT are provided. Initially, P3HT and PCBM are diffused in the CB solvent. After a certain time-interval (consistent with evaporation rate), a fraction of CB molecules are removed from the system until the all of them are evaporated from the simulation box, resulting in an intermixed P3HT:PCBM BHJ. Initial and final dimensions of the simulation box correspond to box dimensions before and after solvent evaporation.

(P3HT:PCBM)

Chain length

Initial Number of Number of number of P3HT PCBM CB molecules molecules molecules

Initial dimensions of the simulation box (nm3)

Final dimensions of the simulation box (nm3)

1.0:0.08

48

75

53

39077

15×15×44.0

15×15×4.22

1.0:0.5

48

75

329

37086

15×15×44.0

15×15×5.52

1.0:0.8

48

75

526

35669

15×15×44.0

15×15×6.46

1.0:1.0

48

75

658

34712

15×15×44.0

15×15×7.10

1.0:2.0

48

75

1316

30177

15×15×44.0

15×15×10.37

1.0:8.0

48

35

2460

25821

15×15×44.0

15×15×14.02

1.0:1.0

24

149

658

35745

15×15×44.0

15×15×7.10

1.0:1.0

72

50

658

33943

15×15×44.0

15×15×7.10

1.0:1.0

120

30

658

34471

15×15×44.0

15×15×7.10

Weight ratio


20

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Table 2: Simulation details for different morphological properties are presented. Density of composite systems with different weight ratios are denoted along with volume fraction of individual phase and void fraction of the BHJ system. Weight ratio (P3HT:PCBM)

P3HT density (gm/cm3)

PCBM density (gm/cm3)

Annealed BHJ blend density (gm/cm3)

P3HT volume fraction (φP3HT)

PCBM Void fraction volume fraction (1- (φP3HT + (φPCBM) φPCBM )

1.0:0.08

1.10

1.50

1.155

0.3509

0.0564

0.5926

1.0:0.5

1.10

1.50

1.370

0.5915

0.2791

0.1293

1.0:0.8

1.10

1.50

1.386

0.5119

0.3659

0.1222

1.0:1.0

1.10

1.50

1.387

0.4749

0.3952

0.1298

1.0:2.0

1.10

1.50

1.390

0.3009

0.5636

0.1354

1.0:8.0

1.10

1.50

1.420

0.0757

0.5643

0.3599


21


Page 22 of 56

Table 3: MD simulation parameters related to energy minimization, equilibration (under NVT and NPT ensembles) and the solvent evaporation simulation are listed. Velocity rescale and ParrinelloRahman methods are used as thermostat and barostat, respectively, to achieve smooth convergence for temperature and pressure constraints. Coupling constants for the simulations are considered for the Martini force field 52.

Energy Minimization

NVT

Solvent

Equilibration

NPT Equilibration

Evaporation

Thermal Annealing

Algorithm

Steepest descent

Leap frog

Leap frog

Leap frog

Leap frog

Time step (fs)

20

20

20

20

20

LJ cut-off Verlet scheme

Verlet

Verlet

Verlet

Verlet

Cut-off radius 1.1 (nm)

1.1

1.1

1.1

1.1

Thermostat

Berendsen

Berendsen

Velocityrescale

Velocityrescale

Barostat

Berendsen

Berendsen

ParrinelloRahman

ParrinelloRahman

Coupling constant (ps-1)

1

2

15

15

Temperature (K)

298

298

298

298-698

1

1

1

Pressure (atm.)


22

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Table 4: Fitting results revealing the peak positions and peak widths of the XRD data as shown in Figure 6. With Gaussian fit peak position for the P3HT: PCBM is found close to the previous reported value of 0.379 Å−𝟏

79

. Peak positions for diffraction pattern found from CGMD

simulations are also presented. Positions for the lamellar (100) peaks are in agreement with the XRD results.

P3HT: PCBM

Condition

Peak position Peak position Peak width (Å−𝟏 ) −𝟏 (XRD) (Å ) (CGMD) (Å−𝟏 )

1.0:1.0

Annealed

0.384 ± 0.004

0.3985

0.047 ± 0.008

Unannealed

0.391 ± 0.002

0.4230

0.036 ± 0.004

Annealed

0.379 ± 0.001

0.3984

0.032 ± 0.001

Unannealed

0.394 ± 0.002

0.4475

0.039 ± 0.002

1.0:0.5


23


Page 24 of 56

Figures Chlorine Carbon Hydrogen

Chlorine+Carbon Hydrogen+Carbon

Oxygen Sulfur All-atom

Virtual sites Sulfur+Carbon Coarse-grain

CB

PCBM

P3HT

Figure 1: Coarse-grained models of CB, PCBM and P3HT (3-mer) molecules as employed in the Martini CG potential 52,53. Typically, 4 atoms are considered together to form a single Martini CG bead. However, for the thiophene rings in P3HT and the fullerene cage in PCBM, 2-3 atoms are considered together to form a single CG bead.


24

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P3HT:PCBM = 1.0:0.08

P3HT:PCBM = 1.0:0.8

P3HT:PCBM = 1.0:8.0

(a)

(b)

(c)

(d)

(e)

(f)

Figure 2: Comparison of morphologies with spatial discretization (sampled along the x-y plane) for different weight ratios. (a)-(c): Snapshots of the BHJ morphology for 1:0.08, 1:0.8 and 1:8 weight ratios of P3HT:PCBM, respectively. P3HT molecules are represented using grey beads and PCBM molecules are denoted using black beads. (d)-(f): The corresponding spatially discretized morphologies for 1:0.08, 1:0.8 and 1:8 weight ratios. All the representations are across the x-y plane. White regions represent pure P3HT domains while black represents pure PCBM. Grey areas indicate a mixture of P3HT and PCBM.


25


Page 26 of 56


26

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Figure 3: Snapshots of the temporal morphology evolution during the solvent evaporation along the (a) x-z and (b) x-y planes of the simulation domain. P3HT and PCBM molecules are represented as grey and black beads, respectively, and solvent (CB) molecules are denoted by blue beads. Initially P3HT and PCBM molecules are dispersed randomly in the solvent (left). P3HT molecules agglomerate with the solvent evaporation. When the solvent content is less than 50%, PCBM agglomeration is observed. (c): Variation in the interfacial contact with solvent evaporation. The initial decrease in PCBM:PCBM and increase in P3HT:P3HT contacts explain why P3HT agglomerates earlier due to lower solubility of P3HT in CB than PCBM.


27


Page 28 of 56

Before annealing

After annealing

(a)

(b)

Figure 4: Comparison of BHJ morphologies of solvent free P3HT:PCBM blend (a) before and (b) after thermal annealing process. P3HT segregates and the domain size increases due to annealing. An increase in P3HT chain ordering (crystallinity) forces the dispersed PCBM molecules to phase separate out of the P3HT domain.


28

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Figure 5: Morphology characterization of P3HT:PCBM for the as-cast and annealed blends. (a): Average domain size of P3HT and PCBM as a function of mixture composition before and after thermal processing. Annealing helps to increase P3HT domain size due to increase in crystallinity of P3HT. Increase in domain size is significant for weight ratios 1:0.5, 1:0.8 and 1:1. (b): Interfacial area to volume ratio as a function of the blend composition. For lower weight fractions of PCBM, interfacial area increases with annealing, while interfacial area decreases upon annealing for blends with PCBM weight fraction greater than 50%.


29


Intensity (arb. unit)

cc

annealed as cast fit_annealed fit_as cast

(a)

1.00 0.95

P3HT: PCBM 1.0:0.5

0.90 0.85

P3HT:PCBM 1.0:0.5

0.80

0.3

0.4

0.5

0.6

0.7

-1

q(ang )


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 56

(c)

1.00

annealed as cast fit_annealed fit_as cast

P3HT: PCBM 1.0:1.0

0.95 0.90 P3HT:PCBM 1.0:1.0

0.85 0.3

0.4

0.5

0.6

0.7

-1

q(ang )


30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60



Page 31 of 56

(e)

1.00

annealed as cast

0.95

P3HT: PCBM 1.0:2.0

0.90

0.85

P3HT:PCBM 1.0:2.0

0.80 0.3

0.4

0.5

0.6

0.7

-1

q(ang )

Figure 6: XRD and simulated scattering profiles for different compositions and annealing conditions of the P3HT: PCBM blend. Figure (a), (c) and (e) are experimental X-ray diffraction profiles for blend for 1.0:0.5, 1.0:1.0 and 1.0:2.0 weight ratios of P3HT: PCBM blend, respectively. Figure (b), (d) and (f) are simulated scattering profiles for 1:0.5, 1:1 and 1:2 weight ratios of P3HT: PCBM blend, respectively. Increase in both lamellar (100) and stacking (010) peak intensities upon annealing is visible for 1.0:0.5 and 1.0:1.0 weight ratio. Effect of annealing is less pronounced for compositions where either PCBM is predominant which is accordance with experimental observations in Figure (a), (c) and (e). It is concluded that effect of annealing is less pronounced for compositions where either P3HT or PCBM is predominant.


31



0.4 annealed unanealed

(a)

0.3 0.2

P3HT:PCBM 1.0:0.5

0.1 0.0 0.04

0.08

0.12

-1

q(ang )


0.4 annealed unannealed

(c)

0.3 0.2 P3HT:PCBM 1.0:1.0

0.1 0.0 0.04

0.08

0.12

-1

q(ang )

0.4 Intensity (arb. unit)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 56

annealed unannealed

(e)

0.3 0.2 P3HT:PCBM 1.0:2.0

0.1 0.0 0.04

0.08

0.12

-1

q(ang )


32

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Figure 7: SAXS and small q simulated scattering profiles for different compositions and annealing conditions of the P3HT: PCBM blend. Figure (a), (c) and (e) are experimental SAXS for 1.0:0.5, 1.0:1.0 and 1.0:2.0 weight ratios of P3HT: PCBM blend, respectively. Figure (b), (d) and (f) are small q simulated scattering profiles for 1.0:0.5, 1.0:1.0 and 1.0:2.0 weight ratios of P3HT: PCBM blend, respectively. Both the experimental data and the simulated data show similar trend.


33


Page 34 of 56

Figure 8: Scattering profiles for different polymer chain lengths in the P3HT:PCBM blend. (a)(d): Scattering profiles for 24, 48, 72 and 120-mer P3HT respectively. P3HT:PCBM blend with lower DOP readily crystallizes upon thermal annealing. Effect of annealing reduces with increasing DOP. However, increase in both lamellar and stacking peaks are visible for all cases indicating some degree of crystallization irrespective of P3HT polymerization (chain length).


34

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P3HT:PCBM = 1.0:0.08

P3HT:PCBM = 1.0:0.5

P3HT:PCBM = 1.0:0.8

(a)

(b)

(c)

P3HT:PCBM = 1.0:1.0

P3HT:PCBM = 1.0:2.0

P3HT:PCBM = 1.0:8.0

(d)

(e)

(f)

Figure 9: A cross-sectional view of the morphology along the x-y plane for the annealed P3HT:PCBM blends for different compositions (grey denotes P3HT and black denotes PCBM). (a)-(f): Blend morphology for 1.0:0.08, 1.0:0.5, 1.0:0.8, 1.0:1.0, 1.0:2.0 and 1.0:8.0 weight ratios of P3HT:PCBM, respectively.


35


Page 36 of 56

Figure 10: The variation of morphological parameters with different blend compositions. (a): Interfacial area to volume ratio as a function of PCBM weight fraction. Interfacial area to volume ratio is highest for 1:1 weight ratio, indicating highest exciton dissociation for this composition relative to others. (b): The percolation ratio of both P3HT and PCBM domain as a function of blend composition. Percolations of P3HT decrease with increasing weight fraction of PCBM, while the PCBM percolations are unaffected until the PCBM fraction is 0.5. (c): The average domain size for P3HT and PCBM. Domain size predictions for P3HT and PCBM, in agreement with experimental 83,84 and earlier computational (LPC force field) 43 reports, are almost equal for


36

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1:1 weight ratio indicating optimum exciton diffusion and charge mobility. (d): The shortest distance to interface that an exciton has to travel before it finds an interface to dissociate into electron and holes.


37


T = 323 K

T = 348 K

T = 373 K

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)

(j)

(k)

(l)

48-mer

24-mer

T = 298 K

72-mer

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 56


38

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


120-mer

Page 39 of 56

(m)

(n)

(o)

(p)

Figure 11: A cross-sectional cut along the x-y plan of the annealed blend morphology under different pre-heating conditions (grey represents P3HT and black denotes PCBM). (a)-(d): Blend morphology of mixture containing 24-mer P3HT at 298, 323, 348 and 373 K, respectively. (e)-(h): Blend morphology of mixture containing 48-mer P3HT at 298, 323, 348 and 373 K, respectively. (i)-(l): Blend morphology of mixture containing 72-mer P3HT at 298, 323, 348 and 373 K, respectively. (m)-(p): Blend morphology of mixture containing 120-mer P3HT at 298, 323, 348 and 373 K, respectively.


39


Page 40 of 56

Figure 12: The variation of morphological parameters with degree of P3HT polymerization. (a): The distribution of the crystalline P3HT phase (%) as a function of DOP and initial pre-heating temperatures. The molecular arrangements of the P3HT phase determine the fraction of crystallinity. The highest percentage of phase order is recorded for 24-mer due to its shorter chain lengths as, unlike its longer counterparts, it does not exhibit entanglement. (b): Interfacial area to volume ratio (IVAR) for the P3HT:PCBM blend for different P3HT chain lengths at various preheating temperatures. Interfacial area increases significantly with change in DOP from 24 to 48, but the enhancement is not significant for P3HT chain length greater than 48. For shorter chains (24-mer) pre-heating enhances the IVAR, while the effect diminishes for longer chains. For P3HT 120-mer, IVAR is observed to decrease with increasing pre-heating temperature.

Author Contributions


40

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JM performed all the simulations. JM and GB analyzed the computational results. RD performed the experiments. RD and TC analyzed the experimental results. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Acknowledgment This material is based on the work supported by the National Science Foundation (NSF) under Award Nos. CMMI-1662435, 1662509 and 1753770. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.


41


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References 1

Chun Sing Lai, Youwei Jia, Loi Lei Lai, Zhao Xu, Malcolm D. McCulloch, and Kit Po

Wong, A comprehensive review on large-scale photovoltaic system with applications of electrical energy storage Renewable and Sustainable Energy Reviews 78, 439 (2017). 2

Sarah Kurtz, Nancy Haegel, Ronald Sinton, and Robert Margolis, A new era for solar

Nature Photonics 11, 3 (2017). 3

Letian Dou, Jingbi You, Ziruo Hong, Zheng Xu, Gang Li, Robert A. Street, and Yang

Yang, 25th Anniversary Article: A Decade of Organic/Polymeric Photovoltaic Research Advanced Materials 25 (46), 6642 (2013). 4

Serap Günes, Helmut Neugebauer, and Niyazi Serdar Sariciftci, Conjugated Polymer-

Based Organic Solar Cells Chemical Reviews 107 (4), 1324 (2007). 5

Barry C Thompson and Jean M J Fréchet, Polymer–Fullerene Composite Solar Cells

Angewandte Chemie International Edition 47 (1), 58 (2008). 6

Frederik C. Krebs, Fabrication and processing of polymer solar cells: A review of printing

and coating techniques Solar Energy Materials and Solar Cells 93 (4), 394 (2009). 7

Li-Min Chen, Ziruo Hong, Gang Li, and Yang Yang, Recent Progress in Polymer Solar

Cells: Manipulation of Polymer:Fullerene Morphology and the Formation of Efficient Inverted Polymer Solar Cells Advanced Materials 21 (14-15), 1434 (2009). 8

Gang Li, Rui Zhu, and Yang Yang, Polymer solar cells Nature Photonics 6, 153 (2012).


42

Page 43 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


9

Michael R. Lee, Robert D. Eckert, Karen Forberich, Gilles Dennler, Christoph J. Brabec,

and Russell A. Gaudiana, Solar Power Wires Based on Organic Photovoltaic Materials Science 324 (5924), 232 (2009). 10

Martin Kaltenbrunner, Matthew S. White, Eric D. Głowacki, Tsuyoshi Sekitani, Takao

Someya, Niyazi Serdar Sariciftci, and Siegfried Bauer, Ultrathin and lightweight organic solar cells with high flexibility Nature Communications 3, 770 (2012). 11

G. Yu, J. Gao, J. C. Hummelen, F. Wudl, and A. J. Heeger, Polymer Photovoltaic Cells:

Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions Science 270 (5243), 1789 (1995). 12

J. J. M. Halls, C. A. Walsh, N. C. Greenham, E. A. Marseglia, R. H. Friend, S. C. Moratti,

and A. B. Holmes, Efficient photodiodes from interpenetrating polymer networks Nature 376, 498 (1995). 13

M. C Scharber, D. Mühlbacher, M. Koppe, P. Denk, C. Waldauf, A. J Heeger, and C. J

Brabec, Design Rules for Donors in Bulk-Heterojunction Solar Cells—Towards 10 % EnergyConversion Efficiency Advanced Materials 18 (6), 789 (2006). 14

Nicholas E. Jackson, Brett M. Savoie, Tobin J. Marks, Lin X. Chen, and Mark A. Ratner,

The Next Breakthrough for Organic Photovoltaics? The Journal of Physical Chemistry Letters 6 (1), 77 (2015). 15

Ye Huang, Edward J. Kramer, Alan J. Heeger, and Guillermo C. Bazan, Bulk

Heterojunction Solar Cells: Morphology and Performance Relationships Chemical Reviews 114 (14), 7006 (2014).


43


16

Page 44 of 56

Xiaozhou Che, Yongxi Li, Yue Qu, and Stephen R. Forrest, High fabrication yield organic

tandem photovoltaics combining vacuum- and solution-processed subcells with 15% efficiency Nature Energy 3 (5), 422 (2018). 17

Joseph Kalowekamo and Erin Baker, Estimating the manufacturing cost of purely organic

solar cells Solar Energy 83 (8), 1224 (2009). 18

Jianqi Zhang, Lingyun Zhu, and Zhixiang Wei, Toward Over 15% Power Conversion

Efficiency for Organic Solar Cells: Current Status and Perspectives Small Methods 1 (12), 1700258 (2017). 19

Yuanping Yi, Veaceslav Coropceanu, and Jean-Luc Brédas, Exciton-Dissociation and

Charge-Recombination Processes in Pentacene/C60 Solar Cells: Theoretical Insight into the Impact of Interface Geometry Journal of the American Chemical Society 131 (43), 15777 (2009). 20

Jiamo Guo, Hideo Ohkita, Hiroaki Benten, and Shinzaburo Ito, Charge Generation and

Recombination Dynamics in Poly(3-hexylthiophene)/Fullerene Blend Films with Different Regioregularities and Morphologies Journal of the American Chemical Society 132 (17), 6154 (2010). 21

Oleksandr V. Mikhnenko, Hamed Azimi, Markus Scharber, Mauro Morana, Paul W. M.

Blom, and Maria Antonietta Loi, Exciton diffusion length in narrow bandgap polymers Energy & Environmental Science 5 (5), 6960 (2012). 22

Andrew T. Kleinschmidt, Samuel E. Root, and Darren J. Lipomi, Poly(3-hexylthiophene)

(P3HT): fruit fly or outlier in organic solar cell research? Journal of Materials Chemistry A 5 (23), 11396 (2017).


44

Page 45 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


23

Brian R. Saunders and Michael L. Turner, Nanoparticle–polymer photovoltaic cells

Advances in Colloid and Interface Science 138 (1), 1 (2008). 24

Junfeng Yan and Brian R. Saunders, Third-generation solar cells: a review and

comparison of polymer:fullerene, hybrid polymer and perovskite solar cells RSC Advances 4 (82), 43286 (2014). 25

Frederik C. Krebs, Nieves Espinosa, Markus Hösel, Roar R. Søndergaard, and Mikkel

Jørgensen, 25th Anniversary Article: Rise to Power – OPV-Based Solar Parks

Advanced

Materials 26 (1), 29 (2014). 26

Riccardo Po, Andrea Bernardi, Anna Calabrese, Chiara Carbonera, Gianni Corso, and

Andrea Pellegrino, From lab to fab: how must the polymer solar cell materials design change? an industrial perspective Energy & Environmental Science 7 (3), 925 (2014). 27

Daniel J. Burke and Darren J. Lipomi, Green chemistry for organic solar cells Energy &

Environmental Science 6 (7), 2053 (2013). 28

Neil D. Treat, Alessandro Varotto, Christopher J. Takacs, Nicolas Batara, Mohammed Al-

Hashimi, Martin J. Heeney, Alan J. Heeger, Fred Wudl, Craig J. Hawker, and Michael L. Chabinyc, Polymer-Fullerene Miscibility: A Metric for Screening New Materials for HighPerformance Organic Solar Cells Journal of the American Chemical Society 134 (38), 15869 (2012). 29

Neil D. Treat, Michael A. Brady, Gordon Smith, Michael F. Toney, Edward J. Kramer,

Craig J. Hawker, and Michael L. Chabinyc, Interdiffusion of PCBM and P3HT Reveals Miscibility in a Photovoltaically Active Blend Advanced Energy Materials 1 (1), 82 (2011).


45


30

Page 46 of 56

Brian A. Collins, Zhe Li, John R. Tumbleston, Eliot Gann, Christopher R. McNeill, and

Harald Ade, Absolute Measurement of Domain Composition and Nanoscale Size Distribution Explains Performance in PTB7:PC71BM Solar Cells Advanced Energy Materials 3 (1), 65 (2013). 31

Christian Müller, On the Glass Transition of Polymer Semiconductors and Its Impact on

Polymer Solar Cell Stability Chemistry of Materials 27 (8), 2740 (2015). 32

Suchol Savagatrup, Adam D. Printz, Timothy F. O'Connor, Aliaksandr V. Zaretski, Daniel

Rodriquez, Eric J. Sawyer, Kirtana M. Rajan, Raziel I. Acosta, Samuel E. Root, and Darren J. Lipomi, Mechanical degradation and stability of organic solar cells: molecular and microstructural determinants Energy & Environmental Science 8 (1), 55 (2015). 33

Suchol Savagatrup, Adam D. Printz, Haosheng Wu, Kirtana M. Rajan, Eric J. Sawyer,

Aliaksandr V. Zaretski, Christopher J. Bettinger, and Darren J. Lipomi, Viability of stretchable poly(3-heptylthiophene) (P3HpT) for organic solar cells and field-effect transistors Synthetic Metals 203, 208 (2015). 34

Harald Hoppe and Niyazi Serdar Sariciftci, Organic solar cells: An overview Journal of

Materials Research 19 (7), 1924 (2011). 35

Mikkel Jørgensen, Kion Norrman, and Frederik C. Krebs, Stability/degradation of polymer

solar cells Solar Energy Materials and Solar Cells 92 (7), 686 (2008). 36

Christoph J. Brabec, Srinivas Gowrisanker, Jonathan J. M. Halls, Darin Laird, Shijun Jia,

and Shawn P. Williams, Polymer–Fullerene Bulk-Heterojunction Solar Cells Advanced Materials 22 (34), 3839 (2010).


46

Page 47 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


37

P. W M Blom, V. D Mihailetchi, L. J A Koster, and D. E Markov, Device Physics of

Polymer:Fullerene Bulk Heterojunction Solar Cells Advanced Materials 19 (12), 1551 (2007). 38

Amaresh Mishra and Peter Bäuerle, Small Molecule Organic Semiconductors on the Move:

Promises for Future Solar Energy Technology Angewandte Chemie International Edition 51 (9), 2020 (2012). 39

Yuze Lin, Yongfang Li, and Xiaowei Zhan, Small molecule semiconductors for high-

efficiency organic photovoltaics Chemical Society Reviews 41 (11), 4245 (2012). 40

Markus C. Scharber, On the Efficiency Limit of Conjugated Polymer:Fullerene-Based Bulk

Heterojunction Solar Cells Advanced Materials 28 (10), 1994 (2016). 41

S. M. Mortuza and Soumik Banerjee, Molecular modeling study of agglomeration of [6,6]-

phenyl-C61-butyric acid methyl ester in solvents The Journal of Chemical Physics 137 (24), 244308 (2012). 42

David M. Huang, Roland Faller, Khanh Do, and Adam J. Moulé, Coarse-Grained

Computer Simulations of Polymer/Fullerene Bulk Heterojunctions for Organic Photovoltaic Applications Journal of Chemical Theory and Computation 6 (2), 526 (2010). 43

Cheng-Kuang Lee, Chun-Wei Pao, and Chih-Wei Chu, Multiscale molecular simulations

of the nanoscale morphologies of P3HT:PCBM blends for bulk heterojunction organic photovoltaic cells Energy & Environmental Science 4 (10), 4124 (2011). 44

Cheng-Kuang Lee and Chun-Wei Pao, Solubility of [6,6]-Phenyl-C61-butyric Acid Methyl

Ester and Optimal Blending Ratio of Bulk Heterojunction Polymer Solar Cells The Journal of Physical Chemistry C 116 (23), 12455 (2012).


47


45

Page 48 of 56

Cheng-Kuang Lee, Olga Wodo, Baskar Ganapathysubramanian, and Chun-Wei Pao,

Electrode Materials, Thermal Annealing Sequences, and Lateral/Vertical Phase Separation of Polymer Solar Cells from Multiscale Molecular Simulations ACS Applied Materials & Interfaces 6 (23), 20612 (2014). 46

Eric Jankowski, Hilary S. Marsh, and Arthi Jayaraman, Computationally Linking

Molecular Features of Conjugated Polymers and Fullerene Derivatives to Bulk Heterojunction Morphology Macromolecules 46 (14), 5775 (2013). 47

Jan-Michael Y. Carrillo, Rajeev Kumar, Monojoy Goswami, Bobby G. Sumpter, and W.

Michael Brown, New insights into the dynamics and morphology of P3HT:PCBM active layers in bulk heterojunctions Physical Chemistry Chemical Physics 15 (41), 17873 (2013). 48

Jan-Michael Y. Carrillo, Zach Seibers, Rajeev Kumar, Michael A. Matheson, John F.

Ankner, Monojoy Goswami, Kiran Bhaskaran-Nair, William A. Shelton, Bobby G. Sumpter, and S. Michael Kilbey, Petascale Simulations of the Morphology and the Molecular Interface of Bulk Heterojunctions ACS Nano 10 (7), 7008 (2016). 49

S. M. Mortuza, Lahiru K. Kariyawasam, and Soumik Banerjee, Combined deterministic-

stochastic framework for modeling the agglomeration of colloidal particles Physical Review E 92 (1), 013304 (2015). 50

T. T. To and S. Adams, Modelling of P3HT:PCBM interface using coarse-grained

forcefield derived from accurate atomistic forcefield Physical Chemistry Chemical Physics 16 (10), 4653 (2014).


48

Page 49 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


51

Mohit Garg and Venkat Padmanabhan, Addition of P3HT-grafted Silica nanoparticles

improves bulk-heterojunction morphology in P3HT-PCBM blends Scientific Reports 6, 33219 (2016). 52

Riccardo Alessandri, Jaakko J. Uusitalo, Alex H. de Vries, Remco W. A. Havenith, and

Siewert J. Marrink, Bulk Heterojunction Morphologies with Atomistic Resolution from CoarseGrain Solvent Evaporation Simulations Journal of the American Chemical Society 139 (10), 3697 (2017). 53

Siewert J. Marrink and D. Peter Tieleman, Perspective on the Martini model Chemical

Society Reviews 42 (16), 6801 (2013). 54

Valentina Marcon and Guido Raos, Molecular Modeling of Crystalline Oligothiophenes:

Testing and Development of Improved Force Fields The Journal of Physical Chemistry B 108 (46), 18053 (2004). 55

Joydeep Munshi, Umar Farooq Ghumman, Akshay Iyer, Rabindra Dulal, Wei Chen, TeYu

Chien, and Ganesh Balasubramanian, Composition and processing dependent miscibility of P3HT and PCBM in organic solar cells by coarse-grained molecular simulations Computational Materials Science 155, 112 (2018). 56

Umar Farooq Ghumman, Akshay Iyer, Rabindra Dulal, Joydeep Munshi, Aaron Wang,

TeYu Chien, Ganesh Balasubramanian, and Wei Chen, A Spectral Density Function Approach for Active Layer Design of Organic Photovoltaic Cells Journal of Mechanical Design (2018).


49


57

Page 50 of 56

Cheng-Kuang Lee and Chun-Wei Pao, Nanomorphology Evolution of P3HT/PCBM Blends

during Solution-Processing from Coarse-Grained Molecular Simulations The Journal of Physical Chemistry C 118 (21), 11224 (2014). 58

S. M. Mortuza, Corinna Cisneros, Mark Bartolo, and Soumik Banerjee, Molecular

Modeling of Nanoparticles and Conjugated Polymers During Synthesis of Photoactive Layers of Organic Photovoltaic Solar Cells. (2013). 59

Naga Rajesh Tummala, Shafigh Mehraeen, Yao-Tsung Fu, Chad Risko, and Jean-Luc

Brédas, Materials-Scale Implications of Solvent and Temperature on [6,6]-Phenyl-C61-butyric Acid Methyl Ester (PCBM): A Theoretical Perspective Advanced Functional Materials 23 (46), 5800 (2013). 60

Rakhee C. Pani, Benjamin D. Bond, Ganesh Krishnan, and Yaroslava G. Yingling,

Correlating fullerene diffusion with the polythiophene morphology: molecular dynamics simulations Soft Matter 9 (42), 10048 (2013). 61

Emanuele Panizon, Davide Bochicchio, Luca Monticelli, and Giulia Rossi, MARTINI

Coarse-Grained Models of Polyethylene and Polypropylene The Journal of Physical Chemistry B 119 (25), 8209 (2015). 62

Martin Vögele, Christian Holm, and Jens Smiatek, Coarse-grained simulations of

polyelectrolyte

complexes:

MARTINI

models

for

poly(styrene

sulfonate)

and

poly(diallyldimethylammonium) The Journal of Chemical Physics 143 (24), 243151 (2015). 63

Luca Monticelli, On Atomistic and Coarse-Grained Models for C60 Fullerene Journal of

Chemical Theory and Computation 8 (4), 1370 (2012).


50

Page 51 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


64

Mark James Abraham, Teemu Murtola, Roland Schulz, Szilárd Páll, Jeremy C. Smith, Berk

Hess, and Erik Lindahl, GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers SoftwareX 1-2, 19 (2015). 65

Siewert J. Marrink, H. Jelger Risselada, Serge Yefimov, D. Peter Tieleman, and Alex H.

de Vries, The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations The Journal of Physical Chemistry B 111 (27), 7812 (2007). 66

Hwankyu Lee, Alex H. de Vries, Siewert-Jan Marrink, and Richard W. Pastor, A Coarse-

Grained Model for Polyethylene Oxide and Polyethylene Glycol: Conformation and Hydrodynamics The Journal of Physical Chemistry B 113 (40), 13186 (2009). 67

Christoph J. Brabec, Martin Heeney, Iain McCulloch, and Jenny Nelson, Influence of blend

microstructure on bulk heterojunction organic photovoltaic performance Chemical Society Reviews 40 (3), 1185 (2011). 68

Minh Trung Dang, Lionel Hirsch, and Guillaume Wantz, P3HT:PCBM, Best Seller in

Polymer Photovoltaic Research Advanced Materials 23 (31), 3597 (2011). 69

Arar Mario, Gruber Manfred, Edler Michael, Haas Wernfried, Hofer Ferdinand, Bansal

Neha, X. Reynolds Luke, A. Haque Saif, Zojer Karin, Trimmel Gregor, and Rath Thomas, Influence of morphology and polymer:nanoparticle ratio on device performance of hybrid solar cells—an approach in experiment and simulation Nanotechnology 24 (48), 484005 (2013). 70

Stefan D. Oosterhout, Martijn M. Wienk, Svetlana S. van Bavel, Ralf Thiedmann, L. Jan

Anton Koster, Jan Gilot, Joachim Loos, Volker Schmidt, and René A. J. Janssen, The effect of


51


Page 52 of 56

three-dimensional morphology on the efficiency of hybrid polymer solar cells Nature Materials 8, 818 (2009). 71

W. Humphrey, Dalke, A., Schulten, K., VMD - Visual Molecular Dynamics J. Molec.

Graphics 14, 33 (1996). 72

Jessy L. Baker, Leslie H. Jimison, Stefan Mannsfeld, Steven Volkman, Shong Yin, Vivek

Subramanian, Alberto Salleo, A. Paul Alivisatos, and Michael F. Toney, Quantification of Thin Film Crystallographic Orientation Using X-ray Diffraction with an Area Detector Langmuir 26 (11), 9146 (2010). 73

Jonathan E. Allen, Kevin G. Yager, Htay Hlaing, Chang-Yong Nam, Benjamin M. Ocko,

and Charles T. Black, Enhanced charge collection in confined bulk heterojunction organic solar cells Applied Physics Letters 99 (16), 163301 (2011). 74

Naveen Michaud-Agrawal, Elizabeth J. Denning, Thomas B. Woolf, and Oliver Beckstein,

MDAnalysis: A toolkit for the analysis of molecular dynamics simulations

Journal of

Computational Chemistry 32 (10), 2319 (2011). 75

G. Li, Y. Yao, H. Yang, V. Shrotriya, G. Yang, and Y. Yang, “Solvent Annealing” Effect

in Polymer Solar Cells Based on Poly(3-hexylthiophene) and Methanofullerenes Advanced Functional Materials 17 (10), 1636 (2007). 76

Florian Machui, Stefan Langner, Xiangdong Zhu, Steven Abbott, and Christoph J. Brabec,

Determination of the P3HT:PCBM solubility parameters via a binary solvent gradient method: Impact of solubility on the photovoltaic performance Solar Energy Materials and Solar Cells 100, 138 (2012).


52

Page 53 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


77

Mao-Yuan Chiu, U-Ser Jeng, Chiu-Hun Su, Keng S. Liang, and Kung-Hwa Wei,

Simultaneous Use of Small- and Wide-Angle X-ray Techniques to Analyze Nanometerscale Phase Separation in Polymer Heterojunction Solar Cells Advanced Materials 20 (13), 2573 (2008). 78

Sanjay Sahare, Naresh Veldurthi, Suwarna Datar, and Tejashree Bhave, Photon assisted

conducting atomic force microscopy study of nanostructured additives in P3HT:PCBM RSC Advances 5 (124), 102795 (2015). 79

Dian Chen, Atsuhiro Nakahara, Dongguang Wei, Dennis Nordlund, and Thomas P.

Russell, P3HT/PCBM Bulk Heterojunction Organic Photovoltaics: Correlating Efficiency and Morphology Nano Letters 11 (2), 561 (2011). 80

Feng Liu, Dian Chen, Cheng Wang, Kaiyuan Luo, Weiyin Gu, Alejandro L. Briseno, Julia

W. P. Hsu, and Thomas P. Russell, Molecular Weight Dependence of the Morphology in P3HT:PCBM Solar Cells ACS Applied Materials & Interfaces 6 (22), 19876 (2014). 81

Suraj N. Bhadani, Yugal K. Prasad, and Swapna Kundu, Electrochemical and chemical

polymerization of acrylamide Journal of Polymer Science: Polymer Chemistry Edition 18 (5), 1459 (1980). 82

Andrew J. Parnell, Ashley J. Cadby, Oleksandr O. Mykhaylyk, Alan D. F. Dunbar, Paul E.

Hopkinson, Athene M. Donald, and Richard A. L. Jones, Nanoscale Phase Separation of P3HT PCBM Thick Films As Measured by Small-Angle X-ray Scattering Macromolecules 44 (16), 6503 (2011).


53


83

Page 54 of 56

Ji Sun Moon, Jae Kwan Lee, Shinuk Cho, Jiyun Byun, and Alan J. Heeger, “Columnlike”

Structure of the Cross-Sectional Morphology of Bulk Heterojunction Materials Nano Letters 9 (1), 230 (2009). 84

Lawrence F. Drummy, Robert J. Davis, Diana L. Moore, Michael Durstock, Richard A.

Vaia, and Julia W. P. Hsu, Molecular-Scale and Nanoscale Morphology of P3HT:PCBM Bulk Heterojunctions: Energy-Filtered TEM and Low-Dose HREM Chemistry of Materials 23 (3), 907 (2011). 85

Andrea Maurano, Rick Hamilton, Chris G. Shuttle, Amy M. Ballantyne, Jenny Nelson,

Brian O’Regan, Weimin Zhang, Iain McCulloch, Hamed Azimi, Mauro Morana, Christoph J. Brabec, and James R. Durrant, Recombination Dynamics as a Key Determinant of Open Circuit Voltage in Organic Bulk Heterojunction Solar Cells: A Comparison of Four Different Donor Polymers Advanced Materials 22 (44), 4987 (2010). 86

Fiona C. Jamieson, Tiziano Agostinelli, Hamed Azimi, Jenny Nelson, and James R.

Durrant, Field-Independent Charge Photogeneration in PCPDTBT/PC70BM Solar Cells The Journal of Physical Chemistry Letters 1 (23), 3306 (2010). 87

C. G. Shuttle, R. Hamilton, B. C. O’Regan, J. Nelson, and J. R. Durrant, Charge-density-

based analysis of the current–voltage response of polythiophene/fullerene photovoltaic devices Proceedings of the National Academy of Sciences 107 (38), 16448 (2010). 88

R. A. Street, Sarah Cowan, and A. J. Heeger, Experimental test for geminate recombination

applied to organic solar cells Physical Review B 82 (12), 121301 (2010).


54

Page 55 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


89

G. Yu, J. Gao, J. C. Hummelen, F. Wudl, and A. J. Heeger, Polymer Photovoltaic Cells:

Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions Science 270 (5243), 1789 (1995). 90

Steffan Cook, Akihiro Furube, Ryuzi Katoh, and Liyuan Han, Estimate of singlet diffusion

lengths in PCBM films by time-resolved emission studies Chemical Physics Letters 478 (1), 33 (2009).


55

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45


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Solution Processing Dependent Bulk Heterojunction Nanomorphology

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