Anomalous Rapid Defect Annihilation in Self ... - ACS Publications

Jan 15, 2015 - ABSTRACT: Molecular self-assembly commonly suffers from dense structural defect formation. Spontaneous defect annihilation in block ...
0 downloads 0 Views 9MB Size
Letter pubs.acs.org/NanoLett

Anomalous Rapid Defect Annihilation in Self-Assembled Nanopatterns by Defect Melting Bong Hoon Kim,†,‡ So Jung Park,§ Hyeong Min Jin,†,‡ Ju Young Kim,†,‡ Seung-Woo Son,∥ Myung-Hyun Kim,§ Chong Min Koo,⊥ Jonghwa Shin,‡ Jaeup U. Kim,*,§ and Sang Ouk Kim*,†,‡ †

Center for Nanomaterials and Chemical Reactions, Institute for Basic Science (IBS), Daejeon 305-701, Republic of Korea Department of Materials Science and Engineering, KAIST, Daejeon 305-701, Republic of Korea § School of Natural Science, Department of Physics, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798, Republic of Korea ∥ Department of Applied Physics, Hanyang University, Ansan, Gyeonggi-do 426-791, Republic of Korea ⊥ Center for Materials Architecturing, Korea Institute of Science and Technology (KIST), Hwarangno 14-gil 5, Seongbuk-gu, Seoul 136-791, Republic of Korea ‡

S Supporting Information *

ABSTRACT: Molecular self-assembly commonly suffers from dense structural defect formation. Spontaneous defect annihilation in block copolymer (BCP) self-assembly is particularly retarded due to significant energy barrier for polymer chain diffusion and structural reorganization. Here we present localized defect melting induced by blending short neutral random copolymer chain as an unusual method to promote the defect annihilation in BCP self-assembled nanopatterns. Chemically neutral short random copolymer chains blended with BCPs are specifically localized and induce local disordered states at structural defect sites in the self-assembled nanopatterns. Such localized “defect melting” relieves the energy penalty for polymer diffusion and morphology reorganization such that spontaneous defect annihilation by mutual coupling is anomalously accelerated upon thermal annealing. Interestingly, neutral random copolymer chain blending also causes morphology-healing self-assembly behavior that can generate large-area highly ordered 10 nm scale nanopattern even upon poorly defined defective prepatterns. Underlying mechanisms of the unusual experimental findings are thoroughly investigated by three-dimensional self-consistent field theory calculation. KEYWORDS: Self-assembly, block copolymer, defect, nanopattern

M

short neutral random copolymers.10,16,28−33 The blended neutral random copolymer chains are specifically concentrated at the defect sites of self-assembled morphology and induce local disordered state. Such a defect melting relieves the energy barrier for polymer diffusion and lamellar reorganization,28,34 which are required for defect annihilation by mutual coupling. Interestingly, neutral random copolymer chain blending also facilitates highly ordered nanopattern formation even with poorly formed defective prepattern structures, which is contrary to our old knowledge that defective prepattern structures generally result in poorly ordered self-assembled nanopatterns in DSA approaches.13,14 Figure 1A exhibits SEM images of lamellar BCP thin films, prepared from the blends of various polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) copolymers with neutral random copolymer chain poly(styrene-ran-methyl methacrylate) P(S-r-MMA). The number-average molecular weight of

icrophase separation of block copolymer (BCP) creates self-assembled nanostructures that can complement the intrinsic limitations of conventional photolithography.1−4 Such lithographic application of BCP self-assembly generally requires defect-free pattern formation. In this regard, directed selfassembly (DSA)5−12 has been extensively explored, where chemical13,14 or topographic15−22 prepatterns direct the orientation and registration of self-assembled nanodomains for highly ordered nanopatterns. Eventual success of DSA approach is largely governed by diffusion and merging of defects. Typical defects in selfassembled morphology, such as dislocations and disclinations, annihilate by direct mutual coupling. Unfortunately, such a process is commonly retarded or even frozen as the distance between the paring defects increases. How to promote defect annihilation is the key issue for the rapid assembly of large-area, highly ordered nanopatterns.23−27 In this work, we introduce unusually rapid defect annihilation in BCP self-assembled morphology enabled by “defectmelting”. Localized defect melting is introduced in the selfassembled lamellar nanopatterns of BCP thin films by blending © XXXX American Chemical Society

Received: November 9, 2014 Revised: January 4, 2015

A

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

ratio of neutral random copolymer chain was above 0.3 for BCP and blended with 96 or 68.5 kg mol−1 PS-b-PMMA. Interestingly, when the weight ratio of neutral random copolymer chain was 0.3 for 51 kg mol−1 PS-b-PMMA blends, unexpected giant grain growth was observed. When the composition of neutral random copolymer chain was further increased, homogeneous disordered phase was formed over the entire sample rather than macrophase separation (Supporting Information 2). Quantitative analysis of the lamellar grain growth was performed by correlation length measurement, which quatifies the typical distance over which lamellar orientations are correlated. It is frequently measured by the weighted twopoint correlation function of directors for quantitative characterization (Supporting Information 3).35−37 Obviously, the blends of small molecular weight PS-b-PMMA (51 kg mol−1) with neutral random copolymer chains show the fastest grain growth. The average correlation length higher than 800 nm was observed for 7:3 blends, which corresponds to the average grain size larger than 3 μm2 approximately. Figure 1B presents the variation of lamellar period with blend composition. The lamellar period gradually decreases as the neutral random copolymer chain composition increases. It is noteworthy that the 7:3 blends of 51 kg mol−1 PS-b-PMMA with neutral random copolymer chain shows the lamellar thickness of ∼10 nm. Observed abnormal giant grain growth can be combined with a DSA approach for large-area laterally ordered nanopatterns. Interestingly, highly ordered nanopatterns could also be obtained even from defective prepattern structures. Figure 2A,B shows that the blends of 51 kg mol−1 PS-b-PMMA and neutral random copolymer chains generate well-aligned lamellar morphology within a 5 μm wide photoresist trench with highly defective rough side wall profile (Supporting Information 4). While lamellar structure is highly defective and bent near the rough sidewall (Figure 2C), they become highly aligned as located away from the sidewall. Notably, lamellae are highly aligned even when undeveloped PR residues remain within the negative photoresist trench (inset in Figure 2C). This surprising morphology-healing self-assembly behavior is greatly advantageous for practical nanopatterning process. In the preparation of prepattern structures for DSA, unexpected defects can be formed in the practical lithographic process. Our approach can greatly help one to achieve highly ordered selfassembled pattern formation even with such unexpected defects in the prepattern. In a BCP nanopatterning process, thermal annealing time required for self-assembly is a crucial parameter for overall throughput. Neutral random copolymer chains promote the mobility of overall BCP blends and thereby remarkably reduce the annealing time, particularly at a high temperature above 250 °C. Figure 2D,E contrasts the SEM images of lamellar patterns of 51 kg mol−1 PS-b-PMMA thin films with and without neutral random copolymer chains, respectively. Thermal annealing was performed at 250 °C for 6 min. A definite reduction of defect density is observed with neutral random copolymer chains. Owing to the rapid self-assembly, the blend film forms highly aligned defect-free nanopatterns at 0.74 μm wide trench within 1 min at 250 °C, as shown in Figure 2F. Underlying mechanism of abnormal grain growth with neutral random copolymer chains was investigated with a three-dimensional self-consistent field theory (SCFT) calculation.38−41 Symmetric PS-b-PMMA and neutral random

Figure 1. Anomalous giant BCP lamellar grain growth. (A) Plane view SEM images and (B) correlation length measured for lamellar BCP thin films prepared by blending various symmetric PS-b-PMMA with P(S-r-MMA) neutral random copolymer. Correlation length increases with the amount of blended P(S-r-MMA). Macrophase separation is observed when the weight ratio of P(S-r-MMA) is above 0.3 for 94 kg mol−1 PS-b-PMMA and 0.4 for 68.5 kg mol−1 PS-b-PMMA blends. Unexpectedly large grain occurs when P(S-r-MMA) weight ratio is 0.3 for 51 kg mol−1 PS-b-PMMA blends, above which disordered phase is observed. Lamellar period gradually decreases with the amount of blended P(S-r-MMA).

symmetric PS-b-PMMAs varied from 51 to 68.5 to 96 kg mol−1, whereas that of P(S-r-MMA) was maintained at 17 kg mol−1 (Supporting Information 1). The 60−80 nm thick BCP films were spin-coated on a silicon wafer, whose surface was chemically modified with P(S-r-MMA) brush. The films were thermally annealed at 200 °C for 24 h for self-assembly. They have the surface-perpendicular BCP nanotemplate because the random brush-treated surface was chemically neutral to PS and PMMA components.29 The lamellar grain size of blend films increases with the composition of neutral random polymer chains as a result of improved chain mobility with excess free volumes. Macrophase separation was observed when the weight B

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

lamellar domain width shrinks almost linearly with the composition of random copolymers. The degree of shrinkage matches well with the experimental results (Figure 3B and Supporting Information 6). In a rough estimation, expressing the random copolymer fraction as ϕrandom, χN times the fraction of BCPs, 1 − ϕrandom is assumed to be the effective χN of blends, (χN)eff. This approximation offers that when χN = 18 and ϕrandom = 0.4, the value of (χN)eff is close to the order− disorder transition (ODT) value of 10.495, below which microphase separation no longer occurs. In Figure 1A, more than 30 wt % of neutral random copolymer chain blending led to macroscopic phase separation for long BCPs (68.5 and 94 kg mol−1 PS-b-PMMA), while disordered phase is formed in the blends of short BCPs (51 kg mol−1 PS-b-PMMA). Our SCFT results and free energy analysis match well with these experimental findings (Figure 3C,E). For the longest BCP chains (94 kg mol−1), phase transition occurred with random copolymer composition as follows: ordered lamellae → macrophase separation (ordered lamellae + disordered phase) → disordered phase (Supporting Information 7 and 8). Similar phase transition was observed for intermediate length BCPs (68.5 kg mol−1), although the free energy gap inducing the phase separation is much weaker (Figure 3D,E, Supporting Information 7 and 9). By contrast, a smooth transition from ordered phase to disordered phase (without macrophase separation) is expected for the 51 kg mol−1 BCPs at 41% of volume fraction (Figure 3A), which is consistent with experimental results. In order to compare the degree of lamellar ordering upon neutral random copolymer chain blending, we performed SCFT calculation starting from a random initial field for a wide area (32.0 × 32.0 R20) of thin film with thickness 1.0 R0, where R0 is the natural end-to-end length of a BCP chain. Figure 3A shows the morphology of thin films of 51 kg mol−1 BCP blends with different neutral random copolymer chain volume fractions. At a small volume fraction, dense defects are observed. As the volume fraction increases, the defect density gradually decreases. At ∼37% (Figure 3A bottom middle), which is slightly below the transition to the disordered phase, the majority of defects disappear and highly aligned selfassembled morphology is established over an extremely large area. Mechanism of the dramatically enhanced defect annihilation was investigated by tracking down the copolymer distribution within the blended films, as shown in Figure 4. In our SCFT iteration, the system is essentially in an almost self-consistent situation. In this nearly equilibrated system, the slow drift of morphology is observed to follow the path that reduces the free energy, provided that the morphology is not stuck in a locally metastable state. Nonetheless, this is still a pseudodynamics analysis which can only give hints about the right path that the system follows after the removal of fluctuation. For the full understanding of the exact kinetic pathway, it would be ideal to employ more advanced techniques such as the string method42,43 or dynamic SCFT.44 However, such methods would be too much time-consuming to apply for the wide area of system in which we are interested. For pure BCP films without neutral random copolymer chain, the defects are immobilized and the system is trapped in a metastable state (Figure 4A). For 37% neutral random copolymer chain blended film, the distribution of PS and PMMA segments are shown in Figure 4B and the corresponding neutral random copolymer chain density is

Figure 2. Morphology-healing directed BCP self-assembly. (A) Schematic representation and (B) SEM image of defect-melting assisted highly ordered lamellar BCP pattern formation within 5 μm width photoresist trenches with rough side wall profiles. (C) Lamellar orderings of blends of 51 kg mol−1 PS-b-PMMA and P(S-r-MMA) near rough side wall. Lamellar grain growth contrasts between (D) blends of 51 kg mol−1 PS-b-PMMA and P(S-r-MMA) and (E) pure 51 kg mol−1 PS-b-PMMA. (F) Defect-melting-assisted BCP lamellar assembly within a 0.74 μm width trench after 1 min annealing at 250 °C. (G) Photograph of defect-melting-assisted BCP lamellar pattern within PR trenches with various widths.

copolymers were regarded as Gaussian chains (Supporting Information 5). First, we evaluated the effect of neutral random copolymer chain blending on the equilibrium lamellar domain size. Because the neutral random copolymer chain screens the repulsive interaction between PS and PMMA blocks, the C

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 3. SCFT modeling of BCP film phase behavior. (A) Morphologies of PS-b-PMMA (51 kg mol−1) blended with P(S-r-MMA) neutral random copolymers (14.5k) with various volume fractions. BCP chains are modeled as symmetric polymers ( f = 0.5) with Flory−Huggins interaction parameter, χN = 18, and the box size is 48.0 × 48.0 × 1.00 R30 (top view). Neutral random copolymer volume fraction is 0, 10, and 20% for the top row from left to right and 30, 37, and 50% for the bottom row from left to right. At 37% of neutral random copolymer composition, globally ordered stripe pattern emerges. Above 41%, disordered phase is observed. (B) Variation of equilibrium lamellar period and (C) modified free energy as a function of the neutral random copolymer volume fraction. (D) Morphologies of PS-b-PMMA (68.5K, f = 0.5, χN = 24) BCPs blended with the same random copolymers at the volume fractions of 40, 50, and 56% from left to right. Simulation box size is 32.0 × 32.0 × 1.00 R30 (top view). Defect density decreases with neutral random copolymer composition but above 45% the lamellar and disordered phases coexist. (E) Modified free energy plot for PS-b-PMMA (68.5K) blended with neutral random copolymers.

shown in Figure 4C. Defect evolution during the SCFT iteration is also provided as a movie file (Supporting Information 10). A clear correlation is found that neutral random copolymer chains are concentrated at the dislocation cores to exceed the order−disorder transition composition (41%). Short chains without any enthalpic preference for a particular BCP block are localized at defect cores and relieve energy penalty for polymer chain distortion and uneven segmental distribution. At the particular composition of ϕrandom = 0.37, which is just below the value for ODT, such a localization renders dislocation cores in the disordered regime, as termed by “defect melting”. This specific localization of neutral random copolymer chain may also compensate any distortion of lamellar ordering enforced by boundary condition or any other external stimuli, as observed by the unusual morphology-healing behavior presented in Figure 2A−C. Figure 4D−F presents the detailed chemical composition and random copolymer distribution around single dislocation defects in pure BCP film and 37% neutral random copolymer chain blended films. For pure BCP (Figure 4D) the boundary between lamellar domains is very sharp following the typical relationship of wI ∝ χ−1/2, where wI is the boundary thickness.38,45 This sharp lamellar boundary suppresses the chain diffusion and corresponding defect mobility across lamellar domains. Furthermore, some defects permanently remain particularly in lamellar self-assembled morphology due to the high energy barrier required for the chain diffusion. The chain diffusion across lamellar layers (∝ exp(−const ·χN)) is

known to be exponentially slow compared to the diffusion along the lamellar layer.34,46,47 As shown in Figure 4E,F, neutral random copolymer chains in blend films are significantly concentrated in the highly bent portion of lamellae nearby the dislocation cores such that the boundary between lamellar domains becomes blurred. This local melting of defect can greatly reduce the energy barrier for chain diffusion and defect movement across lamellar domains. Figure 4G shows the calculated total energy penalty for a pair of defects as a function of neutral random copolymer chain fraction using the parameters of our experimental system. It starts from hundreds of kBT for pure BCPs but decreases by more than 1 order of magnitude as the neutral random copolymer chain fraction increases. This strongly suggests that the energy barrier for the defect movement must be reduced by a similar factor as (χN)eff reduces, and the mobility of chains increases accordingly. We note that the same mechanism does not hold for high molecular weight BCP blends, where macroscopic separation occurs before defect melting (Supporting Information 8 and 9). As an immediate application of ultralarge-area nanopatterning based on defect melting, we demonstrate aluminum nanowire (Al NW) array fabrication48,49 for optical reflective polarizers. Metallic wire grid polarizers may possess strong optical anisotropy with a near-perfect transmission for one polarization and strong attenuation for the other polarization if the period of the grid is much smaller than the visible wavelength. Unfortunately, most of the previously reported wire grid polarizers have periods that are only a few times D

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 4. SCFT modeling of defect annihilation. (A) Morphological evolution of a defect pair of pure PS-b-PMMA (51 kg mol−1) BCPs (2D simulation box size: 19.7 × 19.7 R20) after 18000 iterations (right). Defects are frozen without further evolution. (B) Morphological evolution of PSb-PMMA (51 kg mol−1) blended with neutral random copolymers at volume fraction 37% (simulation box size: 16.0 × 16.0 R20). After 85 200 iterations (right), two defects eventually merge and disappear. (C) Neutral random copolymer migration during defect elimination (0, 5000, 7600, and 85 200 iterations from left to right). Region with high neutral random copolymer volume fraction is shown with red color (scale bar at the bottom). (D,E) magnifies the initial single defect in (A,B) respectively. In (D), BCP chain mobility along the red line is exponentially small compared to the mobility along lamellar direction, while in (E) defect melting is significant and BCP chain mobility along the red line is similar to the mobility along lamellar direction. (F) Neutral random copolymer density corresponding to (E). The maximum density is above the ODT (41%). (G) Total energy for a pair of defects is plotted as a function of neutral random copolymer fraction. BCP film thickness was assumed to be 75 nm (3.88 R0).

smaller than the wavelength. By contrast, our method allows us to fabricate wire grid polarizers with a truly deep-subwavelength period. Figure 5A is a photograph of highly aligned BCP lamellar nanopatterns self-assembled within topographic photoresist prepattern formed on a glass substrate. Figure 5B shows an SEM image of an Al NW array fabricated by selective metal deposition upon highly aligned lamellar nanotemplate and subsequent lift-off (Supporting Information 11). Numerical simulation employing finite difference time domain method (Supporting Information 12) has evaluated the polarization-dependent optical properties of such highly aligned Al NW array (Figure 5C−F). Simulation was executed separately for transverse electric (TE) polarization, where the electric field is perpendicular to the nanowire axis, and transverse magnetic (TM) polarization, where the electric field is parallel to the axis. The result reveals that the nanometer-scale height NWs show distinctive spectra for TE and TM polarizations. For the wavelength range considered (from 400 to 1000 nm), TE-polarized light passes almost uninhibited (over 95% transmission), while the transmission of TM-polarized light is only around 55%. The greatly reduced transmission for the TM light is attributed to the sizable

reflection (20−30%) and non-negligible absorption (10−25%). Interestingly, this structure with only 7 nm thickness possesses more than 6:1 average contrast ratio for reflection. This structure may be used as transmission polarizer with high contrast ratio as well, by stacking it multiple times. We have demonstrated localized defect melting as an effective route to promote the diffusion and annihilation of defects in self-assembled nanoscale morphology. Highly specific localization of neutral random copolymer chains at defect cores triggers anomalously ultralarge grain growth of self-assembled lamellar morphology in the BCP thin films, while the localized disordered state at defect cores greatly relieves the energy penalty for BCP chain diffusion and lamellar ripping/ reorganization. Such an interesting defect melting behavior offers robust rapid BCP nanopatterning with ∼10 nm characteristic length scale. It is noteworthy that defect annihilation process is generally more retarded in selfassembled lamellar morphology compared to analogous cylindrical or spherical morphology due to the less degree of freedom in the structural symmetry. Surprisingly, localization of neutral random copolymer chain gives rise to peculiar morphology-healing self-assembly behavior such that highly E

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 5. Al nanowire grid polarizer fabrication. (A) Photograph and (B) SEM image of Al NW array formed on glass substrate replicating defectmelting assisted large-area BCP lamellar pattern. (C) Schematic illustration of Al NW array on glass substrate. (D) Transmission and (E) reflection spectra of Al NW arrays for TE and TM-polarized incident light. (F) Intensity of diffraction orders normalized to the zeroth order component.



ordered large-area nanopatterns are generated even with defective prepattern structures. This unprecedented defect melting behavior combined with DSA approach is anticipated to greatly widen the practical processing window of BCP lithography and strengthen the potential of nanomanufacture50−55 based on molecular self-assembly principles.



(1) Koo, K.; Ahn, H.; Kim, S.-W.; Ryu, D. Y.; Russell, T. P. Soft Matter 2013, 9, 9059−9071. (2) Bang, J.; Jeong, U.; Ryu, D. Y.; Russell, T. P.; Hawker, C. J. Adv. Mater. 2009, 21, 4769−4792. (3) Stoykovich, M. P.; Nealey, P. F. Mater. Today 2006, 9, 20−29. (4) Black, C. T.; Ruiz, R.; Breyta, G.; Cheng, J. Y.; Colburn, M. E.; Guarini, K. W.; Kim, H.-C.; Zhang, Y. IBM J. Res. Dev. 2007, 51, 605− 633. (5) Kim, B. H.; Kim, J. Y.; Kim, S. O. Soft Matter 2013, 9, 2780− 2786. (6) Jeong, S.-J.; Kim, J. Y.; Kim, B. H.; Moon, H.-S.; Kim, S. O. Mater. Today 2013, 16, 468−476. (7) Park, S.-M.; Stoykovich, M. P.; Ruiz, R.; Zhang, Y.; Black, C. T.; Nealey, P. F. Adv. Mater. 2007, 19, 607−611. (8) Stoykovich, M. P.; Kang, H.; Daoulas, K. C.; Liu, G.; Liu, C.-C.; de Pablo, J. J.; Müller, M.; Nealey, P. F. ACS Nano 2007, 1, 168−175. (9) Xu, J.; Park, S.; Wang, S.; Russell, T. P.; Ocko, B. M.; Checco, A. Adv. Mater. 2010, 22, 2268−2272. (10) Stoykovich, M. P.; Muller, M.; Kim, S. O.; Solak, H. H.; Edwards, E. W.; de Pablo, J. J.; Nealey, P. F. Science 2005, 308, 1442− 1446. (11) Park, W. I.; Kim, K.; Jang, H.-I.; Jeong, J. W.; Kim, J. M.; Choi, J.; Park, J. H.; Jung, Y. S. Small 2012, 8, 3762−3768. (12) Jeong, J. W.; Park, W. I.; Do, L.-M.; Park, J.-H.; Kim, T.-H.; Chae, G.; Jung, Y. S. Adv. Mater. 2012, 24, 3526−3531. (13) Kim, S. O.; Solak, H. H.; Stoykovich, M. P.; Ferrier, N. J.; de Pablo, J. J.; Nealey, P. F. Nature 2003, 424, 411−414. (14) Park, S. H.; Shin, D. O.; Kim, B. H.; Yoon, D. K.; Kim, K.; Lee, S. Y.; Oh, S.-H.; Choi, S.-W.; Jeon, S. C.; Kim, S. O. Soft Matter 2010, 6, 120−125. (15) Yang, J. K. W.; Jung, Y. S.; Chang, J.-B.; Mickiewicz, R. A.; Alexander-Katz, A.; Ross, C. A.; Berggren, K. K. Nat. Nanotechnol. 2010, 5, 256−260.

ASSOCIATED CONTENT

S Supporting Information *

P(S-r-MMA) neutral random copolymer synthesis process, correlation length calculation details, SCFT modeling details, and optical simulation details. This material is available free of charge via the Internet at http://pubs.acs.org.



REFERENCES

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected] (J.U.K.). *E-mail: [email protected] (S.O.K.). Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work was principally supported by Institute for Basic Science (IBS) [CA1301-02]. S.J.P., M.-H.K., and J.U.K. were supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2043633). PLSI supercomputing resource of KISTI is also appreciated. J.S. was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2012M3A7B4035327). F

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters (16) Stuen, K. O.; Detcheverry, F. A.; Craig, G. S. W.; Thomas, C. S.; Farrell, R. A.; Morris, M. A.; de Pablo, J. J.; Nealey, P. F. Nanotechnology 2010, 21, 495301. (17) Park, S.; Lee, D. H.; Xu, J.; Kim, B.; Hong, S. W.; Jeong, U.; Xu, T.; Russell, T. P. Science 2009, 323, 1030−1033. (18) Tavakkoli, K. G. A.; Gotrik, K. W.; Hannon, A. F.; AlexanderKatz, A.; Ross, C. A.; Berggren, K. K. Science 2012, 336, 1294−1298. (19) Bita, I.; Yang, J. K. W.; Jung, Y. S.; Ross, C. A.; Thomas, E. L.; Berggren, K. K. Science 2008, 321, 939−943. (20) Jeong, S.-J.; Moon, H.-S.; Shin, J.; Kim, B. H.; Shin, D. O.; Kim, J. Y.; Lee, Y.-H.; Kim, J. U.; Kim, S. O. Nano Lett. 2010, 10, 3500− 3505. (21) Park, S.; Lee, D. H.; Russell, T. P. Adv. Mater. 2010, 22, 1882− 1884. (22) Aissou, K.; Choi, H. K.; Nunns, A.; Manners, I.; Ross, C. A. Nano Lett. 2013, 13, 835−839. (23) Campbell, I. P.; Lau, G. J.; Feaver, J. L.; Stoykovich, M. P. Macromolecules 2012, 45, 1587−1594. (24) Campbell, I. P.; Hirokawa, S.; Stoykovich, M. P. Macromolecules 2013, 46, 9599−9608. (25) Campbell, I. P.; He, C.; Stoykovich, M. P. ACS Macro Lett. 2013, 2, 918−923. (26) Jeong, J. W.; Hur, Y. H.; Kim, H.; Kim, J. M.; Park, W. I.; Kim, M. J.; Kim, B. J.; Jung, Y. S. ACS Nano 2013, 7, 6747−6757. (27) Son, J. G.; Chang, J.-B.; Berggren, K. K.; Ross, C. A. Nano Lett. 2011, 11, 5079−5084. (28) Li, W.; Nealey, P. F.; de Pablo, J. J.; Muller, M. Phys. Rev. Lett. 2014, 113, 168301. (29) Mansky, P.; Liu, Y.; Huang, E.; Russell, T. P.; Hawker, C. Science 1997, 275, 1458−1460. (30) Hawker, C. J.; Barclay, G. G.; Orellana, A.; Dao, J.; Devonport, W. Macromolecules 1996, 29, 5245−5254. (31) Ryu, D. Y.; Shin, K.; Drockenmuller, E.; Hawker, C. J.; Russell, T. P. Science 2005, 308, 236−239. (32) Bang, J.; Bae, J.; Löwenhielm, P.; Spiessberger, C.; Given-Beck, S. A.; Russell, T. P.; Hawker, C. J. Adv. Mater. 2007, 19, 4552−4557. (33) Ji, S.; Liu, G.; Zheng, F.; Craig, G. S. W.; Himpsel, F. J.; Nealey, P. F. Adv. Mater. 2008, 20, 3054−3060. (34) Ruiz, R.; Sandstrom, R. L.; Black, C. T. Adv. Mater. 2007, 19, 587−591. (35) Fisher, M. E. Rev. Mod. Phys. 1974, 46, 597−616. (36) Yeomans, J. M. Statistical Mechanics of Phase Transitions; Oxford Science Publications: New York, 1992. (37) Harrison, C.; Adamson, D. H.; Cheng, Z.; Sebastian, J. M.; Sethuraman, S.; Huse, D. A.; Register, R. A.; Chaikin, P. M. Science 2000, 290, 1558−1560. (38) Matsen, M. W. J. Phys.: Condens. Matter 2002, 14, R21−R47. (39) Drolet, F.; Fredrickson, G. H. Phys. Rev. Lett. 1999, 83, 4317− 4320. (40) Kim, J. U.; Matsen, M. W. Soft Matter 2009, 5, 2889−2895. (41) Kim, J. U.; Matsen, M. W. Phys. Rev. Lett. 2009, 102, 078303. (42) Li, W.; Nealey, P. F.; de Pablo, J. J.; Müller, M. Phys. Rev. Lett. 2014, 113, 168301. (43) Takahashi, H.; Laachi, N.; Delaney, K. T.; Hur, S.-M.; Weinheimer, C. J.; Shykind, D.; Fredrickson, G. H. Macromolecules 2012, 45, 6253−6265. (44) Fraaije, J. G. E. M.; van Vlimmeren, B. A. C.; Maurits, N. M.; Postma, M.; Evers, O. A.; Hoffmann, C.; Altevogt, P.; GoldbeckWood, G. J. Chem. Phys. 1997, 106, 4260−4269. (45) Semenov, A. N. Sov. Phys. JETP 1985, 61, 733−742. (46) Cavicchi, K. A.; Lodge, T. P. Macromolecules 2004, 37, 6004− 6012. (47) Chang, S.-W.; Evans, J. P.; Ge, S.; Ginzburg, V. V.; Kramer, J. W.; Landes, B.; Lee, C.; Meyers, G.; Murray, D. J.; Park, J.; Sharma, R.; Trefonas, P.; Weinhold, J. D.; Zhang, J.; Hustad, P. D. Proc. SPIE 2013, 86800F. (48) Park, S.; Kim, B.; Cirpan, A.; Russell, T. P. Small 2009, 5, 1343− 1348.

(49) Gu, W.; Zhao, H.; Wei, Q.; Coughlin, E. B.; Theato, P.; Russell, T. P. Adv. Mater. 2013, 25, 4690−4695. (50) Lee, J. I.; Cho, S. H.; Park, S.-M.; Kim, J. K.; Kim, J. K.; Yu, J.W.; Kim, Y. C.; Russell, T. P. Nano Lett. 2008, 8, 2315−2320. (51) Tang, J.; Wang, H.-T.; Lee, D. H.; Fardy, M.; Huo, Z.; Russell, T. P.; Yang, P. Nano Lett. 2010, 10, 4279−4283. (52) Choi, H. K.; Gwyther, J.; Manners, I.; Ross, C. A. ACS Nano 2012, 6, 8342−8348. (53) Jung, H.; Hwang, D.; Kim, E.; Kim, B.-J.; Lee, W. B.; Poelma, J. E.; Kim, J.; Hawker, C. J.; Huh, J.; Ryu, D. Y.; Bang, J. ACS Nano 2011, 5, 6164−6173. (54) Jeong, J. W.; Park, W. I.; Kim, M.-J.; Ross, C. A.; Jung, Y. S. Nano Lett. 2011, 11, 4095−4101. (55) Gotrik, K. W.; Hannon, A. F.; Son, J. G.; Keller, B.; AlexanderKatz, A.; Ross, C. A. ACS Nano 2012, 6, 8052−8059.

G

DOI: 10.1021/nl5042935 Nano Lett. XXXX, XXX, XXX−XXX