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Progress in Top-Down Control of Bottom-Up Assembly Benjamin P. Isaacoff, and Keith A Brown Nano Lett., Just Accepted Manuscript • Publication Date (Web): 20 Oct 2017 Downloaded from http://pubs.acs.org on October 21, 2017
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Nano Letters
Progress in Top-Down Control of Bottom-Up Assembly
Benjamin P. Isaacoff†,* and Keith. A Brown‡,* †
Applied Physics Program and Department of Chemistry, University of Michigan, Ann Arbor, Michigan, United States
‡
Department of Mechanical Engineering, Physics Department, and Division of Materials Science & Engineering, Boston University, Boston, Massachusetts, United States *Address correspondence to
[email protected] (B.P.I.);
[email protected] (K.A.B.)
In nanoscience, the ability to make new structures enables new science and technology. The ways nanomaterials are made can be classified according to what determines the final structure of the material. Specifically, top-down approaches are those in which the sample is effectively a blank canvas and an external stimuli is used to write patterns. In contrast, bottom-up approaches are those in which the final structure is encoded in the material itself and the precursors self-assemble into the desired arrangement. In recent years, there has been great progress in the convergence of these ideas, where top-down control is used to guide bottom-up processes. A unifying theme of these approaches is that the components form into a desired configuration by randomly interacting in a thermodynamic landscape that the experimenter can locally adjust. Materials made using these methods have formed the basis for advances in fields spanning photonics, electronics, and mechanics. This virtual issue seeks to highlight a selection of recent papers in Nano Letters and ACS Nano that illustrate the breadth and unifying themes of this field. In particular, we have chosen to center the discussion on a key opportunity and a key challenge that pervade the field. The key benefit of approaches that marry top-down and bottom-up techniques is that they endow experimenters with multiscale control over materials, a benefit that leads to new phenomena, better utilization of nanoscale effects, and even new classes of combinatorial experiments. The key challenge is the dichotomy between the desire for deterministic control over features and the reality that bottom-up processes are stochastic. Techniques that leverage both top-down and bottom-up control often combine concepts of materials science, physics, and chemistry, and as such, they are intrinsically interdisciplinary. It is important to emphasize that the papers in this virtual issuewere selected to illustrate the diversity and challenges in this emerging field. Not only is this not an exhaustive evaluation of the literature, but even the papers highlighted herein can often fit in multiple categories.
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Figure 1. Schematic showing benefits of using top-down patterning to guide bottom-up assembly. Resultant structures often include control of hierarchical length scales, incorporate materials with mesoscopic effects, and are amenable to combinatorial explorations of parameters.
Benefit of Multiscale Control A major benefit of using top-down control to guide bottom-up assembly is that the length scales one can readily address using top-down means are complementary to those that are well controlled by the molecular-scale interactions between nanoscale objects. Structures made using these approaches are often difficult if not impossible to make using top-down or bottom-up methods alone. These benefits have led to advances that span three general areas:
(1) Hierarchically Structured Materials. The use of top-down approaches allow researchers to tune microscale and larger length scales in an arbitrary fashion while bottom-up control allow researchers to dictate molecular-scale lengths. For instance, top-down approaches such as electron-beam lithography (EBL) can be used to define patterns from the macroscale to the nanoscale while biomolecular interactions can be used to program sub-nanometer spacing between nanoscale elements. For instance, DNA has been used to immobilize gold nanocubes in massive arrays defined by EBL in that manner that exhibits strong coupling between plasmonic and photonic modes.[1] It is worth noting that the top-down step does not need to precede the bottom-up step in order to obtain hierarchical control. As an example, self-assembled superlattices composed of semiconductor nanocrystals can be transferred into microscale arrangements using a stamping technique while preserving long range order.[2] Structures made using directed assembly can also serve as the basis for accessing further length scales. For example, microparticles can be assembled in nearly arbitrary patterns on surfaces using capillary-driven assembly, and the resulting structures can serve as an array of lenses to micropattern hierarchical arrays of structures for non-periodic metasurfaces.[3] One of the crucial advantages of these multiscale materials is that functionality at the small scales can impart emergent behavior at the largest scales. As an example of this, monodisperse cuboids made through DNA origami can become macroscopically switchable in that they can assemble and disassemble in response to chemical and thermal stimuli.[4]
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(2) Utilization of Mesoscale Effects. Directed assembly commonly utilizes nanoscale building blocks that have highly tunable emergent properties that exceed their bulk counterparts on a peratom basis. For instance, structure at the nanoscale can lead to quantum confinement in semiconductors or the emergence of localized surface plasmon resonances in metal nanoparticles. These two particle types in particular have been combined to function as photoinitiators to direct local light-initiated cross linking in a manner where bottom-up assembled constructs become the core vehicle for performing top-down patterning.[5] Additionally, size-dependent phenomena that are dependent on distances between particles can be readily exploited using directed assembly. An example of this is surface-enhanced Raman spectroscopy that is enormously enhanced by nanoscopic distances between particles as has been observed for nanoparticle assemblies constructed using laser-directed thermophoresis.[6] Such mesoscale effects can also be used to guide subsequent assembly processes. For instance, a combination of topographical and chemical patterns can be used to guide the defect structure of liquid crystals in 3D, which can subsequently trap particles in precise arrangemnts.[7]
(3) Perform Combinatorial Experiments. Since top-down stimuli can be easily varied across a sample, users can directly probe a variety of conditions in a single experiment. This approach has been used extensively in optics where samples prepared in well-spaced arrays can be sequentially interrogated. For example, this approach was used to study plasmonic metamolecules in which precise arrangements of hexagonally ordered gold nanoparticles were assembled into polygonal templates and optically interrogated.[8] In addition to metamolecules, gold nanoparticles have been assembled into effectively continuous architectures to form myriad metasurfaces in templates defined by thermal nanoimprint lithography.[9] In addition to elucidating the properties of structures, this combinatorial approach has been useful in learning how to design new structures. For instance, the directed self-assembly of block copolymers on arrangements of holes was studied to elucidate an ‘alphabet’ of hole arrangements that allow for the design of arbitrary patterns.[10] Another advantage of directed assembly approaches is that these processes can be materials flexible, which is a stark contrast to top-down approaches alone that often utilize expensive single-task tools, which are difficult or impossible to adapt for alternate processes. As an example of this generality, bubbles that are locally generated using laser pulses can lead to the local assembly of colloidal particles, regardless of their composition, as was shown for semiconductor and dielectric particles.[11]
Challenge of Deterministic Assembly An overarching challenge faced by researchers who attempt top-down control over bottom-up processes is that of yield. Stochastic processes, such as those that govern-bottom up assembly, necessarily produce variability in their end products. While this is unimportant or difficult to explore in many studies that utilize self-assembly alone, the inclusion of top-down stimuli means
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that the end products can be easily analyzed. Most studies approach this challenge in one of three ways:
(1) Embracing Variability. For many applications, variability in the output can be tolerated because the sample to be interrogated is small and the scaling afforded by working with nanoscale samples means that thousands if not millions of samples can be prepared in parallel. Additionally, each individual sample can often be structurally characterized to provide robust structure-property relationships. Photonics has been an area where this trend is successful, due to the possibility of measuring local optical properties. For instance, capillary assembly has been used to place dissimilar particles in close proximity to study how different types of particle dimers exhibit chiro-optical amplification.[12] The study of collections of nanoparticles that are assembled into rings using DNA also illustrates how the corresponding particle arrangement can be used as an input to further computational study to determine the origin of optical properties.[13] Observation of single assembly events more generally has been possible in situ using optical techniques. For example, optical observation has revealed that nanoparticles can be trapped by electric fields produced by electrodes with 10 nm separation with a modest of voltage of below 200 mV.[14]
(2) Systems that Tolerate Variability. In some systems, the samples are large but microscopic variability does not affect performance. For instance, electrodes comprised of assemblies of nanoparticles are insensitive to the position of individual nanoparticles so long as the electrode cross section is shared by numerous particles. For example, arrays of gold nanowires that are arranged in hexagonal lattices constitute a robust transparent conductive electrode provided that the wires have sufficient overlap with one another.[15] Interestingly, the nanomaterials that constitute these electrodes may be rationally chosen to be more tolerant of variation. For instance, assemblies of CdSe tetrapod nanocrystals become more conductive when assembled into films as their arm lengths are increased.[16] Optics also provides examples of systems where precise microscopic order is not crucial. For instance, domains of quantum dots can be positioned using a layer-by-layer assembly technique that allows multiple color dots to be assembled in different regions for the realization of large-area full-color displays, but whose performance appears to be insensitive of the precise distribution of dots in a domain.[17] Further, second harmonic generation was observed in arrays of gold nanoparticles assembled using electrostatic forces into gold substrates prepared using template stripping, despite a lack of control over where the nanoparticles precisely sit along each trench.[18]
(3) Striving for Perfection. The most stringent examples are those in which long range order is important and individual defects affect the performance of the entire sample. Overcoming this challenge requires tuning the thermodynamics and kinetics of the processes such that the desired pattern forms nearly all of the time, but that the top-down driving is gentle enough to allow the reorganization of metastable states. One conceptually straightforward path to achieving large
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area high quality patterns is to use assembly processes that are effectively irreversible but feature templates that cannot fit more than a single particle. For instance, by matching particle and template size, capillary forces during dewetting can assemble sub-10 nm particles with single particle precision in electron beam lithography-defined holes in polymer films with less than 1% defect density.[19] Further, the deterministic assembly of nanowires has been achieved by sliding a random array of nanowires across a sample that contains a series of guide holes that both immobilize single wires and cause them to fold into a U-shape with a specific curvature.[20] Such patterning can also dictate how nanomaterials are synthesized, as exemplified by the tailored electroluminescent properties of semiconductor wires that were synthesized in trenches patterned in a nickel film.[21] The directed self-assembly of block copolymers is a case where the need for perfection is in sharp focus due to target applications in the semiconductor industry. As a result, there have been breakthroughs in balancing thermodynamic and kinetic constraints by discovering a block copolymer chemistry with a high Flory-Huggins interaction parameter that remains processable at modest tempatures.[22] Understanding subtleties of thermodynamics is particularly important in understanding the competing roles of enthalpy and entropy in governing assembly processes. For example, the length of DNA linkers between nanoparticles has been shown to dictate the superlattice symmetry of nanoparticle assemblies in a manner that was attributed to entropic effects in the longer linkers.[23]
Taken together, there has been considerable progress in utilizing top-down approaches to direct bottom-up assembly. Given the many ways that this combined approach has provided new advances to the nanoscience community and the enormous promise of future developments, we expect this area to remain extremely active and exciting. In closing, we note the increasing role in improved imaging to advancing this field. Since the features that are made using directed assembly are often nanoscopic, they are frequently an ideal size to study using high resolution transmission electron microscopy (TEM). For example, block copolymer features made using directed self-assembly can be visualized in 3D, showing a depth dependence of fluctuations that is otherwise invisible.[24] In situ measurements have also begun to be important in observing the kinetics of assembly. For instance, observing nanoparticles assemble in fluid cells has revealed that long range anisotropic forces drive the formation of chains that subsequently fold into hexagonally closed packed lattices.[25]
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Realization of Large-Area, Full-Color, Active Quantum Dot Display. Nano Lett. 2016, 16, 69466953. (18) Dong, Z.; Asbahi, M.; Lin, J.; Zhu, D.; Wang, Y. M.; Hippalgaonkar, K.; Chu, H.-S.; Goh, W. P.; Wang, F.; Huang, Z.; Yang, J. K. W. Second-Harmonic Generation from Sub-5 nm Gaps by Directed Self-Assembly of Nanoparticles onto Template-Stripped Gold Substrates. Nano Lett. 2015, 15, 5976-5981. (19) Asbahi, M.; Mehraeen, S.; Wang, F.; Yakovlev, N.; Chong, K. S. L.; Cao, J.; Tan, M. C.; Yang, J. K. W. Large Area Directed Self-Assembly of Sub-10 nm Particles with Single Particle Positioning Resolution. Nano Lett. 2015, 15, 6066-6070. (20) Zhao, Y.; Yao, J.; Xu, L.; Mankin, M. N.; Zhu, Y.; Wu, H.; Mai, L.; Zhang, Q.; Lieber, C. M. Shape-Controlled Deterministic Assembly of Nanowires. Nano Lett. 2016, 16, 2644-2650. (21) Qiao, S.; Xu, Q.; Dutta, R. K.; Le Thai, M.; Li, X.; Penner, R. M. Electrodeposited, Transverse Nanowire Electroluminescent Junctions. ACS Nano 2016, 10, 8233-8242. (22) Yang, G.-W.; Wu, G.-P.; Chen, X.; Xiong, S.; Arges, C. G.; Ji, S.; Nealey, P. F.; Lu, X.B.; Darensbourg, D. J.; Xu, Z.-K. Directed Self-Assembly of Polystyrene-b-poly(propylene carbonate) on Chemical Patterns via Thermal Annealing for Next Generation Lithography. Nano Lett. 2017, 17, 1233-1239. (23) Thaner, R. V.; Kim, Y.; Li, T. I. N. G.; Macfarlane, R. J.; Nguyen, S. T.; Olvera de la Cruz, M.; Mirkin, C. A. Entropy-Driven Crystallization Behavior in DNA-Mediated Nanoparticle Assembly. Nano Lett. 2015, 15, 5545-5551. (24) Segal-Peretz, T.; Ren, J.; Xiong, S.; Khaira, G.; Bowen, A.; Ocola, L. E.; Divan, R.; Doxastakis, M.; Ferrier, N. J.; de Pablo, J.; Nealey, P. F. Quantitative Three-Dimensional Characterization of Block Copolymer Directed Self-Assembly on Combined Chemical and Topographical Prepatterned Templates. ACS Nano 2017, 11, 1307-1319. (25) Powers, A. S.; Liao, H.-G.; Raja, S. N.; Bronstein, N. D.; Alivisatos, A. P.; Zheng, H. Tracking Nanoparticle Diffusion and Interaction during Self-Assembly in a Liquid Cell. Nano Lett. 2017, 17, 15-20.
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