Thickness-Dependent Ordering Kinetics in Cylindrical Block Copolymer/Homopolymer Ternary Blends

Assembling Vertical Block Copolymer Nanopores via Solvent Vapor Annealing on Homopolymer-Functionalized Substrates

Utilizing the self-assembly of block copolymers with large Flory-Huggins interaction parameters (χ) for nanofabrication is a formidable challenge due to the attendant large surface energy differences between the blocks. This work reports a robust protocol for the fabrication of thin films with highly ordered cylindrical nanopore arrays via the self-assembly of an asymmetric poly(styrene-block-4-vinylpyridine) (PS-b-P4VP) diblock copolymer blended with a P4VP homopolymer. The desired vertical domain orientation is achieved at the air-polymer interface by controlled solvent vapor annealing (SVA) using acetone, a solvent with weak selectivity for PS over P4VP, and at the substrate interface by functionalization using a hydroxy-terminated poly(2-vinylpyridine) (P2VP-OH) homopolymer brush. In contrast, the vertical cylinder orientation is unstable during acetone SVA on substrates functionalized using hydroxy-terminated poly(methyl methacrylate) (PMMA-OH). Although PMMA exhibits more balanced interfacial energies between PS and P4VP than P2VP in the dry state, it is also swollen more selectively by acetone. We hypothesize that the nearly balanced solvent swelling of the three polymers (P2VP, P4VP, and PS) stabilizes the vertical cylinder orientation, while unbalanced swelling (PMMA > P4VP and PS) does not. We further characterize pore formation by addition of a P4VP homopolymer and its postassembly extraction using ethanol, revealing a narrow window of pore size tunability. Notably, minimal differences in nanopore morphologies are observed for P4VP volume fractions as high as 0.1, regardless of the P4VP molar mass. However, further increasing the P4VP volume fraction results in domain reorientation or macrophase separation when its molar mass is less than or greater than the P4VP block molar mass, respectively. Using a P4VP homopolymer that is nearly equal in length to the P4VP block enables the fabrication of well-ordered arrays of vertical, through-film nanopores with high aspect ratios (>10), small periods (<23 nm), and diameters less than 10 nm.

Hybrid Metrology for Nanostructured Optical Metasurfaces

Metasurfaces have garnered increasing research interest in recent years due to their remarkable advantages, such as efficient miniaturization and novel functionalities compared to traditional optical elements such as lenses and filters. These advantages have facilitated their rapid commercial deployment. Recent advancements in nanofabrication have enabled the reduction of optical metasurface dimensions to the nanometer scale, expanding their capabilities to cover visible wavelengths. However, the pursuit of large-scale manufacturing of metasurfaces with customizable functions presents challenges in controlling the dimensions and composition of the constituent dielectric materials. To address these challenges, the combination of block copolymer (BCP) self-assembly and sequential infiltration synthesis (SIS), offers an alternative for fabrication of high-resolution dielectric nanostructures with tailored composition and optical functionalities. However, the absence of metrological techniques capable of providing precise and reliable characterization of the refractive index of dielectric nanostructures persists. This study introduces a hybrid metrology strategy that integrates complementary synchrotron-based traceable X-ray techniques to achieve comprehensive material characterization for the determination of the refractive index on the nanoscale. To establish correlations between material functionality and their underlying chemical, compositional and dimensional properties, TiO2 nanostructures model systems were fabricated by SIS of BCPs. The results from synchrotron-based analyses were integrated into physical models, serving as a validation scheme for laboratory-scale measurements to determine effective refractive indices of the nanoscale dielectric materials.

Block copolymer self-assembly to pattern gold nanodots for site-specific placement of DNA origami and attachment of nanomaterials

Directed placement of DNA origami could play a key role in future integrated nanoelectronic devices. Here we demonstrated the site-selective attachment of DNA origami on gold dots formed using a pattern transfer method through block copolymer self-assembly. First, a random copolymer brush layer is grafted on the Si surface and then poly (styrene-b-methylmethacrylate) block copolymer is spin-coated to give a hexagonal nanoarray after annealing. UV irradiation followed by acetic acid etching is used to remove the PMMA, creating cylindrical holes and then oxygen plasma etching removes the random copolymer layer inside those holes. Next, metal evaporation, followed by lift-off creates a gold dot array. We evaluated different ligand functionalization of Au dots, as well as DNA hybridization to attach DNA origami to the nanodots. DNA-coated Au nanorods are assembled on the DNA origami as a step towards creating nanowires and to facilitate electron microscopy characterization of the attachment of DNA origami on these Au nanodots. The DNA hybridization approach showed better DNA attachment to Au nanodots than localization by electrostatic interaction. This work contributes to the understanding of DNA-templated assembly, nanomaterials, and block copolymer nanolithography. Furthermore, the work shows potential for creating DNA-templated nanodevices and their placement in ordered arrays in future nanoelectronics.

Droplet-like Defect Annihilation Mechanisms in Hexagonal Cylinder-Forming Block Copolymers

The annihilation of typical individual defects in hexagonal cylinder-forming block copolymers is investigated using the self-consistent field theory (SCFT) in conjunction with the string method. Usually, defect removal in two-dimensional hexagonal patterns involves reorganizing the cylindrical domains. Unlike atoms in solid crystals, the self-assembled cylindrical domains of block copolymers are "soft". Thus, the kinetic motions of the cylindrical domains resemble liquid droplets. Dislocations in hexagonal patterns are eliminated via creating and removing cylindrical domains. Our results show that new cylindrical domains are created via either a nucleation-like process or a fission-like process, whereas excessive domains are eliminated via a fusion-like or evaporation-like process. For weakly segregated block copolymers, the nucleation-like and evaporation-like processes are preferred.

Phase behavior in thin films of weakly segregated block copolymer/homopolymer blends

We have demonstrated the phase behavior of substrate-supported films of a symmetric weakly segregated polystyrene-block-poly (methyl methacrylate), P(S-b-MMA), block copolymer and its blends with homopolymer polystyrene (PS) at different compositions. Upon increasing the content of added PS in the blends, lamellae (L), perforated layers (PL), double gyroid (DG) and cylinders (C) are obtained in sequence for films. Among these nanodomains, PL and DG only exist in a narrow ϕ_PS region (ϕ_PS denotes the volume fraction of PS). At ϕ_PS = 64%, tuning film thickness and annealing temperature can produce parallel PL or DG with {121}_DG lattice planes being parallel to the substrate surface. The effects of annealing temperature and film thickness on the formation of PL and DG are examined. In thin films with n ≈ 3 (n denotes the ratio of initial film thickness to inter-domain spacing), the PL phase solely exists regardless of temperature. However, for thick films with n ≈ 6 and 10, thermal annealing at the most accessible temperature produces films containing both PL and DG of various fractions, but a low temperature tends to favor a greater fraction of PL. The PL phase becomes the only discernible phase if thick films are shortly annealed at 230 °C.

Influence of Osmotic Pressure on Nanostructures in Thin Films of a Weakly-Segregated Block Copolymer and Its Blends with a Homopolymer

We studied the influence of osmotic pressure on nanostructures in thin films of a symmetric weakly-segregated polystyrene-block-poly (methyl methacrylate), P(S-b-MMA), block copolymer and its mixtures with a polystyrene (PS) homopolymer of various compositions. Thin films were deposited on substrates through surface neutralization. The surface neutralization results from the PS mats, which were oxidized and cross-linked by UV-light exposure. Thus, thermal annealing produced perpendicularly oriented lamellae and perforated layers, depending on the content of added PS chains. Nevertheless, a mixed orientation was obtained from cylinders in thin films, where a high content of PS was blended with the P(S-b-MMA). A combination of UV-light exposure and acetic acid rinsing was used to remove the PMMA block. Interestingly, the treatment of PMMA removal inevitably produced osmotic pressure and consequently resulted in surface wrinkling of perpendicular lamellae. As a result, a hierarchical structure with two periodicities was obtained for wrinkled films with perpendicular lamellae. The formation of surface wrinkling is due to the interplay between UV-light exposure and acetic acid rinsing. UV-light exposure resulted in different mechanical properties between the skin and the inner region of a film. Acetic acid rinsing produced osmotic pressure. It was found that surface wrinkling could be suppressed by reducing film thickness, increasing PS content and using high-molecular-weight P(S-b-MMA) BCPs.

High-throughput morphology mapping of self-assembling ternary polymer blends

Multicomponent blending is a convenient yet powerful approach to rationally control the material structure, morphology, and functional properties in solution-deposited films of block copolymers and other self-assembling nanomaterials. However, progress in understanding the structural and morphological dependencies on blend composition is hampered by the time and labor required to synthesize and characterize a large number of discrete samples. Here, we report a new method to systematically explore a wide composition space in ternary blends. Specifically, the blend composition space is divided into gradient segments deposited sequentially on a single wafer by a new gradient electrospray deposition tool, and characterized using high-throughput grazing-incidence small-angle X-ray scattering. This method is applied to the creation of a ternary morphology diagram for a cylinder-forming polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) block copolymer blended with PS and PMMA homopolymers. Using “wet brush” homopolymers of very low molecular weight (∼1 kg mol⁻¹), we identify well-demarcated composition regions comprising highly ordered cylinder, lamellae, and sphere morphologies, as well as a disordered phase at high homopolymer mass fractions. The exquisite granularity afforded by this approach also helps to uncover systematic dependencies among self-assembled morphology, topological grain size, and domain period as functions of homopolymer mass fraction and PS : PMMA ratio. These results highlight the significant advantages afforded by blending low molecular weight homopolymers for block copolymer self-assembly. Meanwhile, the high-throughput, combinatorial approach to investigating nanomaterial blends introduced here dramatically reduces the time required to explore complex process parameter spaces and is a natural complement to recent advances in autonomous X-ray characterization.

Compositionally graded electrospray deposition combined with grazing incidence small angle X-ray scattering forms a high-throughput approach for mapping phase behavior in ternary mixtures as demonstrated here using block copolymer blends.

Advances in Kriging-Based Autonomous X-Ray Scattering Experiments

Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest. We have recently demonstrated a generalized approach to autonomous experimental control, based on generating a surrogate model to interpolate experimental data, and a corresponding uncertainty model, which are computed using a Gaussian process regression known as ordinary Kriging (OK). We demonstrated the successful application of this method to exploring materials science problems using x-ray scattering measurements at a synchrotron beamline. Here, we report several improvements to this methodology that overcome limitations of traditional Kriging methods. The variogram underlying OK is global and thus insensitive to local data variation. We augment the Kriging variance with model-based measures, for instance providing local sensitivity by including the gradient of the surrogate model. As with most statistical regression methods, OK minimizes the number of measurements required to achieve a particular model quality. However, in practice this may not be the most stringent experimental constraint; e.g. the goal may instead be to minimize experiment duration or material usage. We define an adaptive cost function, allowing the autonomous method to balance information gain against measured experimental cost. We provide synthetic and experimental demonstrations, validating that this improved algorithm yields more efficient autonomous data collection.

A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering

Modern scientific instruments are acquiring data at ever-increasing rates, leading to an exponential increase in the size of data sets. Taking full advantage of these acquisition rates will require corresponding advancements in the speed and efficiency of data analytics and experimental control. A significant step forward would come from automatic decision-making methods that enable scientific instruments to autonomously explore scientific problems—that is, to intelligently explore parameter spaces without human intervention, selecting high-value measurements to perform based on the continually growing experimental data set. Here, we develop such an autonomous decision-making algorithm that is physics-agnostic, generalizable, and operates in an abstract multi-dimensional parameter space. Our approach relies on constructing a surrogate model that fits and interpolates the available experimental data, and is continuously refined as more data is gathered. The distribution and correlation of the data is used to generate a corresponding uncertainty across the surrogate model. By suggesting follow-up measurements in regions of greatest uncertainty, the algorithm maximally increases knowledge with each added measurement. This procedure is applied repeatedly, with the algorithm iteratively reducing model error and thus efficiently sampling the parameter space with each new measurement that it requests. We validate the method using synthetic data, demonstrating that it converges to faithful replica of test functions more rapidly than competing methods, and demonstrate the viability of the approach in an experimental context by using it to direct autonomous small-angle (SAXS) and grazing-incidence small-angle (GISAXS) x-ray scattering experiments.