Biomimetic Mineral Synthesis by Nanopatterned Supramolecular-Block Copolymer Templates.

Supramolecular structures of matrix proteins in mineralizing tissues are known to direct the crystallization of inorganic materials. Here we demonstrate how such structures can be synthetically directed into predetermined patterns for which functionality is maintained. The study employs block copolymer lamellar patterns with alternating hydrophilic and hydrophobic regions to direct the assembly of amelogenin-derived peptide nanoribbons that template calcium phosphate nucleation by creating a low-energy interface. Results show that the patterned nanoribbons retain their ß-sheet structure and function and direct the formation of filamentous and plate-shaped calcium phosphate with high fidelity, where the phase, amorphous or crystalline, depends on the choice of mineral precursor and the fidelity depends on peptide sequence. The common ability of supramolecular systems to assemble on surfaces with appropriate chemistry combined with the tendency of many templates to mineralize multiple inorganic materials implies this approach defines a general platform for bottom-up-patterning of hybrid organic-inorganic materials.

Responsive blends of block copolymers stabilize the hexagonally perforated lamellae morphology.

Blends of block copolymers can form phases and exhibit features distinct from the constituent materials. We study thin film blends of cylinder-forming and lamellar-forming block copolymers across a range of substrate surface energies. Blend materials are responsive to interfacial energy, allowing selection of pure or coexisting phases based on surface chemistry. Blending stabilizes certain motifs that are typically metastable, and can be used to generate pure hexagonally perforated lamellar thin films across a range of film thicknesses and surface energies. This tolerant behavior is ascribed to the ability of blend materials to redistribute chains to stabilize otherwise high-energy defect structures. The blend responsiveness allows the morphology to be spatially defined through multi-tone chemical surface patterns.

Thin film block copolymer self-assembly for nanophotonics.

The nanophotonic engineering of light-matter interactions has profoundly changed research behind the design and fabrication of optical materials and devices. Metasurfaces-arrays of subwavelength nanostructures that interact resonantly with electromagnetic radiation-have emerged as an integral nanophotonic platform for a new generation of ultrathin lenses, displays, polarizers and other devices. Their success hinges on advances in lithography and nanofabrication in recent decades. While existing nanolithography techniques are suitable for basic research and prototyping, issues of cost, throughput, scalability, and substrate compatibility may preclude their use for many metasurface applications. Patterning via spontaneous self-assembly of block copolymer thin films offers an enticing alternative for nanophotonic manufacturing that is rapid, inexpensive, and applicable to large areas and diverse substrates. This review discusses the advantages and disadvantages of block copolymer-based nanopatterning and highlights recent progress in their use for broadband antireflection, surface enhanced Raman spectroscopy, and other nanophotonic applications. Recent advances in diversification of self-assembled block copolymer nanopatterns and improved processes for enhanced scalability of self-assembled nanopatterning using block copolymers are also discussed, with a spotlight on directions for future research that would enable a wider array of nanophotonic applications.

Controlling Drug Absorption, Release, and Erosion of Photopatterned Protein Engineered Hydrogels.

A protein-engineered triblock copolymer hydrogel composed of two self-assembling domains (SADs) has been fabricated by a photoactivatable diazirine group followed by ultraviolet (UV)-mediated crosslinking. The photocrosslinkable protein polymer CEC-D has been patterned into various features including different micrometer-scale stripes by using lithographic techniques. The patterned hydrogels are important for encapsulation of small molecules where a photopatterned fraction of 50% is optimal for maximum absorption. Stripe-patterned CEC-D100-100 exhibits slightly lower swelling ratios, an 8.9 times lower erosion profile, and a 2.6-fold higher drug release compared to the unpatterned hydrogel control, CEC-D0. Our studies demonstrate the potential of photocrosslinkable protein polymer hydrogels to be used as scaffolds for therapeutic delivery of small molecules. Through photolithographic techniques on the protein hydrogel, a variety of functionalities can be achieved by patterning different features enabling the mimicry of biological systems.

Transfer of self-aligned spacer patterns for single-digit nanofabrication.

We report the transfer of sub-10 nm half-pitch grating patterns created through a combination of block copolymer directed self-assembly and sidewall spacer-based self-aligned double patterning into Si substrates. Low substrate bias reactive ion etching of TiOx conformally deposited onto carbon mandrels using atomic layer deposition renders distinct, pitch-halved spacers with minimal etch byproduct redeposition. Independent spacer and mandrel width control and the use of an underlying CrNx hard mask deposited by reactive sputtering facilitates etching of Si lines with low roughness and fine placement control. The insights into pattern transfer presented here are directly applicable to the fabrication of rectangular bit pattern nanoimprint templates at densities above 1.5 Td in(-2).

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.

Autonomous discovery of emergent morphologies in directed self-assembly of block copolymer blends.

The directed self-assembly (DSA) of block copolymers (BCPs) is a powerful approach to fabricate complex nanostructure arrays, but finding morphologies that emerge with changes in polymer architecture, composition, or assembly constraints remains daunting because of the increased dimensionality of the DSA design space. Here, we demonstrate machine-guided discovery of emergent morphologies from a cylinder/lamellae BCP blend directed by a chemical grating template, conducted without direct human intervention on a synchrotron x-ray scattering beamline. This approach maps the morphology-template phase space in a fraction of the time required by manual characterization and highlights regions deserving more detailed investigation. These studies reveal localized, template-directed partitioning of coexisting lamella- and cylinder-like subdomains at the template period length scale, manifesting as previously unknown morphologies such as aligned alternating subdomains, bilayers, or a "ladder" morphology. This work underscores the pivotal role that autonomous characterization can play in advancing the paradigm of DSA.

Hierarchical, Self-Assembled Metasurfaces via Exposure-Controlled Reflow of Block Copolymer-Derived Nanopatterns.

Nanopatterning for the fabrication of optical metasurfaces entails a need for high-resolution approaches like electron beam lithography that cannot be readily scaled beyond prototyping demonstrations. Block copolymer thin film self-assembly offers an attractive alternative for producing periodic nanopatterns across large areas, yet the pattern feature sizes are fixed by the polymer molecular weight and composition. Here, a general strategy is reported which overcomes the limitation of the fixed feature size by treating the copolymer thin film as a hierarchical resist, in which the nanoscale pattern motif is defined by self-assembly. Feature sizes can then be tuned by thermal reflow controlled locally by irradiative cross-linking or chemical alteration using lithographic ultraviolet light or electron beam exposure. Using blends of polystyrene-block-poly(methylmethacrylate) (PS-b-PMMA) with PS and PMMA homopolymers, we demonstrate both self-assembled PS grating and hexagonal hole patterns; exposure-controlled reflow is then used to reduce the hole diameter by as much as 50% or increase the PS grating linewidth by more than 180%. Transferring these nanopatterns, or their inverse obtained by a lift-off approach, into silicon yields structural colors that may be prescriptively controlled based on the nanoscale feature size. Furthermore, patterned exposure enables area-selective feature size control, yielding uniform structural color patterns across centimeter square areas. Electron beam lithography is also used to show that the lithographic resolution of this selective-area control can be extended to the nanoscale dimensions of the self-assembled features. The exposure-controlled reflow approach demonstrated here takes a pivotal step toward fabricating complex, hierarchical optical metasurfaces using scalable self-assembly methods.

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.

Electrospray deposition tool: Creating compositionally gradient libraries of nanomaterials.

Electrospray deposition (ESD) enables the growth of solution deposited thin films in a precise and continuous manner by the delivery of submicron droplets of dilute solutions to a heated substrate. By combining ESD with programmable motor control and gradient solution pumping in a first-of-its-kind user tool at the Center for Functional Nanomaterials at Brookhaven National Laboratory, we show the ability to create one or two dimensional compositional gradient nanoscale films via ESD. These capabilities make it possible to construct thin film multicomponent "libraries" on a single substrate to rapidly and systematically characterize composition-dependent properties in a variety of material systems such as thin films involving homopolymer and block copolymer blends. We report the design, construction, and validation of a gradient ESD tool that allows users to carefully control the jet stability, flow composition, spray position, and substrate temperature. Calibrated thin films range in thickness from tens to hundreds of nanometers. We demonstrate gradient thin films using a ternary dye triangle as well as a gradual blending of polystyrene homopolymer with poly(styrene-block-methyl methacrylate) on a single substrate. Paired with the rapid measurement capabilities of synchrotron small angle X-ray scattering, this tool forms an integral part of a new platform for high-throughput, autonomous characterization and design of nanomaterial thin films and soft materials more generally.

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.

Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels.

A majority of experimental disciplines face the challenge of exploring large and high-dimensional parameter spaces in search of new scientific discoveries. Materials science is no exception; the wide variety of synthesis, processing, and environmental conditions that influence material properties gives rise to particularly vast parameter spaces. Recent advances have led to an increase in the efficiency of materials discovery by increasingly automating the exploration processes. Methods for autonomous experimentation have become more sophisticated recently, allowing for multi-dimensional parameter spaces to be explored efficiently and with minimal human intervention, thereby liberating the scientists to focus on interpretations and big-picture decisions. Gaussian process regression (GPR) techniques have emerged as the method of choice for steering many classes of experiments. We have recently demonstrated the positive impact of GPR-driven decision-making algorithms on autonomously-steered experiments at a synchrotron beamline. However, due to the complexity of the experiments, GPR often cannot be used in its most basic form, but rather has to be tuned to account for the special requirements of the experiments. Two requirements seem to be of particular importance, namely inhomogeneous measurement noise (input-dependent or non-i.i.d.) and anisotropic kernel functions, which are the two concepts that we tackle in this paper. Our synthetic and experimental tests demonstrate the importance of both concepts for experiments in materials science and the benefits that result from including them in the autonomous decision-making process.

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.

Rapid Ordering in "Wet Brush" Block Copolymer/Homopolymer Ternary Blends.

The ubiquitous presence of thermodynamically unfavored but kinetically trapped topological defects in nanopatterns formed via self-assembly of block copolymer thin films may prevent their use for many envisioned applications. Here, we demonstrate that lamellae patterns formed by symmetric polystyrene-block-poly(methyl methacrylate) diblock copolymers self-assemble and order extremely rapidly when the diblock copolymers are blended with low molecular weight homopolymers of the constituent blocks. Being in the "wet brush" regime, the homopolymers uniformly distribute within their respective self-assembled microdomains, preventing increases in domain widths. An order-of-magnitude increase in topological grain size in blends over the neat (unblended) diblock copolymer is achieved within minutes of thermal annealing as a result of the significantly higher power law exponent for ordering kinetics in the blends. Moreover, the blends are demonstrated to be capable of rapid and robust domain alignment within micrometer-scale trenches, in contrast to the corresponding neat diblock copolymer. These results can be attributed to the lowering of energy barriers associated with domain boundaries by bringing the system closer to an order-disorder transition through low molecular weight homopolymer blending.

Enabling complex nanoscale pattern customization using directed self-assembly.

Block copolymer directed self-assembly is an attractive method to fabricate highly uniform nanoscale features for various technological applications, but the dense periodicity of block copolymer features limits the complexity of the resulting patterns and their potential utility. Therefore, customizability of nanoscale patterns has been a long-standing goal for using directed self-assembly in device fabrication. Here we show that a hybrid organic/inorganic chemical pattern serves as a guiding pattern for self-assembly as well as a self-aligned mask for pattern customization through cotransfer of aligned block copolymer features and an inorganic prepattern. As informed by a phenomenological model, deliberate process engineering is implemented to maintain global alignment of block copolymer features over arbitrarily shaped, 'masking' features incorporated into the chemical patterns. These hybrid chemical patterns with embedded customization information enable deterministic, complex two-dimensional nanoscale pattern customization through directed self-assembly.

Pattern placement accuracy in block copolymer directed self-assembly based on chemical epitaxy.

The realization of viable designs for circuit patterns using the dense features formed by block copolymer directed self-assembly (DSA) will require a precise and quantitative understanding of self-assembled feature registration to guiding templates or chemical prepatterns. Here we report measurements of DSA placement error for lamellar block copolymer domains indexed to specific lines in the surface chemical prepattern for spatial frequency tripling and quadrupling. These measurements are made possible by the use of an inorganic domain-selective prepattern material that may be imaged upon polymer removal after DSA and a prepattern design incorporating a single feature serving as an in situ registration mark that is identifiable by pattern symmetry in both the prepattern and resulting self-assembled pattern. The results indicate that DSA placement error is correlated with average prepattern line width as well as prepattern pitch uniformity. Finally, the magnitude of DSA placement error anticipated for a uniform, optimized prepattern is estimated.

Single nanowire thermal conductivity measurements by Raman thermography.

A facile, rapid, and nondestructive technique for determining the thermal conductivity of individual nanowires based on Raman temperature mapping has been demonstrated. Using calculated absorption efficiencies, the thermal conductivities of single cantilevered Si nanowires grown by the vapor-liquid-solid method are measured and the results agree well with values predicted by diffuse phonon boundary scattering. As a measurement performed on the wire, thermal contact effects are avoided and ambient air convection is found to be negligible for the range of diameters measured. The method's versatility is further exemplified in the reverse measurement of a single nanowire absorption efficiency assuming diffuse phonon boundary scattering. The results presented here outline the broad utility that Raman thermography may have for future thermoelectric and photovoltaic characterization of nanostructures.

Ex situ vapor phase boron doping of silicon nanowires using BBr3.

An ex situ vapor phase technique for doping vapor-liquid-solid grown silicon nanowires (NWs) based on the reduction of BBr(3) by H(2) has been demonstrated. Electron microscope images show that the excellent crystal quality of the nanowires is preserved with minimal alteration of their surface morphology. Fano resonance in the Raman spectra for single nanowires indicates that active boron concentrations over two orders of magnitude and as high as 10(20) cm(-3) are achievable in a well-controlled manner, with excellent axial uniformity. Electrical resistance measurements from single nanowires confirm that incorporated boron is electrically active, and doping of epitaxial bridging Si NWs is successfully demonstrated. By avoiding the pitfalls of nonuniform concentration profiles and drastic morphological changes that often accompany in situ boron doping, this technique provides a valuable alternative doping route for the development of single Si NW devices in a reliable manner.