Characterizing Patterned Block Copolymer Thin ... - ACS Publications

Subscriber access provided by Binghamton University | Libraries

Article

Characterizing Patterned Block Copolymer Thin Films with Soft X-rays Daniel F Sunday, Jiaxing Ren, Christopher D. Liman, Lance D. Williamson, Roel Gronheid, Paul F Nealey, and R. Joseph Kline ACS Appl. Mater. Interfaces, Just Accepted Manuscript • Publication Date (Web): 25 May 2017 Downloaded from http://pubs.acs.org on May 30, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Applied Materials & Interfaces is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 24

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

ACS Applied Materials & Interfaces

Characterizing Patterned Block Copolymer Thin Films with Soft X-rays Daniel F Sunday1*, Jiaxing Ren2, Christopher D. Liman1, Lance D. Williamson2, Roel Gronheid3, Paul F. Nealey2, R. Joseph Kline1 1. National Institute of Standards and Technology, Gaithersburg, Maryland 20899 2. Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637 3. IMEC, Kapeldreef 75, B-3001 Leuven, Belgium * [email protected] Abstract The directed self-assembly (DSA) of block copolymers (BCPs) is a potential solution for patterning critical features for integrated circuits at future technology nodes. In order for this process to be implemented there needs to be a better understanding of how the template guides the assembly and induces subsurface changes in the lamellar structure. Using a rotational transmission X-ray scattering measurement coupled with soft X-rays to improve contrast between polymer components, the impact of the ratio of the guiding stripe width (W) to the BCP pitch (Lo) was investigated. For W/Lo < 1 continuous vertical lamella were observed, with some fluctuations in the interface profile near the template that smoothed out further up the structure. Near W/Lo ≈ 1.5 the arrangement of the lamella shifted, moving from PS centered on the guiding stripe, to PMMA centered on the guiding stripe. Keywords: Directed Self-Assembly, Small Angle X-ray Scattering, Block Copolymers, Soft X-ray, Inverse Problem Introduction The combination of “top-down” and “bottom-up” approaches for nanofabrication have the potential to produce systems with well controlled length scales and long range order. The directed selfassembly (DSA) of block copolymers (BCPs) is an example of this combined approach where the long range orientation is controlled by a lithographically patterned guide and the minimum length scale is defined by the pitch (Lo) of the BCP.1–6 BCP DSA is being explored as a lithographic resolution enhancement technique in order to cost effectively pattern magnetic storage media and semiconductor devices.7,8 Understanding the limits of the parameter space which lead to the assembly of BCP thin films

ACS Paragon Plus Environment


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

with orientation and morphology suitable for lithography applications is critical for implementation of this approach, particularly given the limitations of current in-line metrologies.9–14 The chemical composition of the template and template geometry, including topography and width of the guiding stripe (W) relative to Lo, all are known to impact the quality of the assembled film.15–20 The assembly quality is typically assessed via scanning electron microscopy (SEM), which is used to evaluate the alignment and registration with the underlying template.21,22 The SEM analysis is necessary for refining assembly conditions, but cannot provide any information on variations in the internal morphology of the film. These subsurface shifts in morphology have been predicted by coarse grained Monte Carlo (CGMC) simulations and have the potential to disrupt the etch transfer to the underlying wafer.15 Utilizing resonant critical dimension small angle X-ray scattering (res-CDSAXS), a transmission SAXS measurement which uses sample rotation to probe the vertical sample profile, we have investigated the three dimensional morphology of polystyrene-b-poly(methyl methacrylate) (PS-b-PMMA) assembled on chemical templates with a range of W/Lo to understand how shifts in guide stripe width impact the film morphology. Chemoepitaxy DSA utilizes a lithographically patterned template to guide the long range alignment of a BCP, typically an A-B diblock with lamellar morphology (although alternative patterns23– 27

and block architectures28–30 have also been investigated). For DSA of PS-b-PMMA, a crosslinked PS

(X-PS) mat is deposited on the substrate and patterned via traditional lithographic techniques. The width of the patterned X-PS lines is then trimmed with a plasma etch, followed by backfill with a PS-r-PMMA brush. The composition of the brush is tuned to promote the perpendicular orientation of the BCP by minimizing the total interface energy. Initial studies assumed that the X-PS line was completely PS preferential, but recent results have shown that the plasma etch can change the surface energy of the X-PS sidewalls.31,32 This results in a more complex distribution of surface energies than were previously considered, with the template having a three-tone chemical contrast. The center portion of the X-PS line that was protected by the photoresist throughout the plasma etch remains PS preferential, but the sidewalls are partially oxidized and become PMMA preferential and the background region filled by the


Page 2 of 24

Page 3 of 24

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


random brush is non-preferential. This process is outlined in Figure 1. There are two regions of W/Lo which have resulted in long range orientation of the BCP, W/Lo ≈ 0.5 and 1.5. At W/Lo ≈ 0.5 the width of the lamella is equal to the template width, and the PS lamella is centered on the X-PS stripe. Simulations for W/Lo ≈ 1.5 have predicted complex subsurface morphologies, which depend on the film thickness and interface energies.15 Thicker films tend to produce more complex structures and have shown to have a smaller window which produces low defect patterns.33

Figure 1: Preparation of the chemical template, an X-PS mat is deposited and patterned via optical lithography. The etch removes the portions of the X-PS not covered by the photoresist and alters the chemistry of the sidewalls. The pattern is then backfilled with a neutral random copolymer.16,31 Characterizing thin polymer films with optical approaches can be challenging due to the small volumes and low contrasts, which result in weak scattering. There has been some success using transmission electron microscopy (TEM) tomography, but so far this has required staining to enhance the sample contrast and stability or the use of BCPs with native contrast such as a silicon-containing block.25,34,35 The development of resonant soft X-ray scattering (RSoXS) techniques allows the contrast between components in organic sub 100 nm films to be sufficiently enhanced that they can be probed with transmission scattering.36–38 Organic materials typically have small differences in electron density, resulting in limited contrast for high energy (10 - 20 keV) X-rays. The soft X-ray region (100 - 3000 eV) contains absorption edges for many of the most common elements in polymeric systems including carbon (284 eV), nitrogen (400 eV) and oxygen (540 eV). Conducting measurements near these edges allows the



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

contrast between materials to be varied based on chemical composition. In the vicinity of an absorption edge the index of refraction (n, n = 1-δ-iβ, where δ is the dispersive component and β is the absorptive component) changes rapidly, and the location of the edge for each atom in the molecule depends on the specific chemical composition. This is demonstrated in Figure 2B, where the scattering power as a function of energy near the carbon edge for a PS-b-PMMA film is shown. The absorption for the aromatic carbons in PS peak at 285 eV, whereas the carbonyl carbon in PMMA peaks at 289 eV. The difference in the location of these absorptions allows the contrast to be tuned. In the pre-edge region δ changes rapidly, and as a result the beam damage can be reduced by operating in this region of lower absorption. Resonant scattering techniques have been used to evaluate a wide range of systems, including BCPs,37–42 organic electronics,36,43,44 biomaterials45 and hard material problems.46–48

Figure 2: A) Measurement geometry for res-CDSAXS, including definition of reciprocal space vectors (qx, qy, qz) on the sample and projection of those vectors on the detector. B) Scattering power overlaid on absorption spectrum for PS-PMMA. The combination of soft x-ray techniques with CDSAXS enables the examination of the internal morphology of polymer films with long range order.49,50 Res-CDSAXS utilizes rotation of the sample to probe both the in-plane and out of plane scattering vectors in a line grating, enabling reconstruction of the


Page 4 of 24

Page 5 of 24

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


two dimensional profile.17,51,52 The measurement geometry is defined in Figure 2A, the BCP lamella are oriented parallel to the axis of rotation and diffraction images are acquired at a series of sample rotations. Rotating away from normal incidence increases the contributions from the qz vector (perpendicular to the sample plane), which contains information on the vertical profile of the lamella. The scattering is evaluated by using an inverse, iterative approach, where a structure is assumed and the simulated scattering from that structure is compared to the experimental scattering.51 The structure is iterated until a satisfactory match to the scattering profile is obtained. The res-CDSAXS method was initially demonstrated by measuring samples with 1:1 density multiplication at ≈ 50 nm pitch.50 Measuring the sample with hard X-rays (17 keV) resulted in a scattering map with only 5 peak orders distinguishable from the background. When the same sample was measured with soft x-rays at the carbon edge (282 eV) 9 peak orders were visible. Comparing the fits from the two measurements showed that the uncertainty of the fit on the sample when measuring with soft X-rays was significantly improved. The same comparison was conducted on a series of samples patterned at 4:1 density multiplication.49 For this more complex sample the hard X-ray measurement was incapable of reconstructing the internal morphology of the patterned film. The improved scattering pattern obtained from soft X-rays allowed the structure of the lamella on the guiding surface to be differentiated from the lamella on the neutral brush. Comparisons between samples with different neutral brush widths resulted in changes in the lamellar shape for the lines on the guiding stripe, while the lamella on the neutral brush showed little change with template width.

Materials and Methods Sample preparation: An in-situ back etch method was used to prepare the membrane samples for CDSAXS measurement.53 Silicon nitride (SiNx) layers were first deposited onto both sides of the silicon substrate. “Line” flow DSA of PS-b-PMMA was then performed on a 300 mm wafer process line at imec in



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

Leuven, Belgium, all polymer films were deposited via spin coating.31 Briefly, 8 nm of X-PS (AZEMBLY NLD-128)54 was first coated and thermally crosslinked. The X-PS was patterned with 193 immersion lithography and reactive ion etching into line and space patterns with a pitch of 84 nm. The width of the guide stripe W was systematically varied between different samples and determined by SEM measurements. 7 nm layer of PS-r-PMMA brush (AZEMBLY NLD-127) was then grafted to the exposed background regions between the guide stripes. Lamellar forming PS-b-PMMA (AZEMBLY

PME-312) was coated onto the template to a thickness of 35 nm and assembled using thermal annealing at 250°C for 5 minutes. After DSA, the wafer was cut into 1.5 cm × 1.5 cm coupons. On the back side, a 3 mm × 1 mm region of SiNx was mechanically removed in the center of the coupon. Potassium hydroxide solution was used to back etch the exposed silicon while the polymer on the front side was sealed and protected by a holder. The final membrane consisted of 13 nm SiNx and ~43 nm DSA polymer layer. Res-CDSAXS: Res-CDSAXS measurements were conducted at beamline 11.0.1.2 at the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory. All samples were measured on back-etched wafers as described in the sample preparation section. Measurements were conducted at 282 eV under high vacuum (10-5 Pa). The beam size was approximately 200 µm full width at half maximum. Collection times ranged from 0.1 to 60 s depending on the detector and sample angles and were varied to maximize the signal-noise ratio. The detector was a CCD and a grating of known period was used to calibrate the scattering vectors. The beam was aligned at the center of rotation of the sample with the polymer grating aligned parallel to the axis of rotation. Scattering from the sample (q vectors on the sample defined in Figure 2A, qz perpendicular to the sample plane, qy in plane and parallel to the line grating, qx in plane and perpendicular to the line grating) is projected onto the 2D detector (qxz and qy also defined in Figure 2A). The intensity for individual diffraction spots is integrated and converted from qxz to qx and qz according to Eqs 1a and 1b. = × −

1a


Page 6 of 24

Page 7 of 24

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


= × −

1b

This produces the 2D scattering map with diffraction peaks at regular intervals along the qx direction, each of these peaks are then integrated along qx to produce the intensity “cuts” as a function of qx position and qz. These peaks are fit to reconstruct the structure of the measured sample. The simulated scattering is calculated from a model structure built via a stack of trapezoids (the form factor for a trapezoid stack is analytically solvable, allowing for computational efficiency). In this work, the outline of the lamella is defined by a spline curve, which is then discretized into a trapezoid stack. Examples of model structures are shown in Figure 3, which shows an example of lamella which are continuous throughout the depth of the film with a PS line centered on the X-PS guiding stripe. Scattering intensity (I(q)) is calculated via the Fourier transform of the proposed structure using Eq 2 (ρ(r) is the shape function describing the stack, P is the sample pitch, * represents a convolution operation, and DW is the Debye Waller factor describing roughness between the lamella). In practice this amounts to calculating the Fourier transform of each trapezoid in the model for all q positions and summing prior to squaring the amplitude, the DW factor is then applied to account for the impact of roughness on the scattering. = $ ∗ ∑# − ×

!

" ×

% &' %

2

Optimization and uncertainty analysis were performed using a Monte Carlo Markov Chain algorithm with the Metropolis Hastings acceptance criteria. This algorithm generates a population of samples around the best fit according to the shape of the goodness of fit space local to that fit. The population can then be analyzed to determine the uncertainty of the model to the experimental data, additional details on the algorithm are available elsewhere.49,52 Uncertainties reported represent 95 % confidence intervals as calculated from the resampled population. The goodness of fit (GF) used to evaluate the quality of fit for the simulated scattering to the experimental data is shown in Eq 3 (Exp indicates the experimental intensity, Sim indicates the simulated intensity), this metric was chosen as it balances the contributions from the low and high order peaks. Much of the fine scale information is



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

contained in the higher order peaks, thus the GF metric needs to weight those to a similar degree as the lower order peaks. The impact of the choice of GF metric was recently explored, demonstrating the biases which may occur from weighing the lower order peaks too heavily.55 In order to deal with the challenge of evaluating models which utilize different numbers of parameters the results will also be compared using the Bayesian information criteria (BIC), shown in Eq 4 (n is the total number of data points, k is the total number of fitting parameters). The BIC evaluates whether the addition of more parameters to a model results in a meaningful change to the GF. The addition of more parameters which does not reduce the BIC suggests that the changes in the model with the addition of those parameters may not be statistically significant.56

() =

*!+ ,-% ,-%

./ = − 0

12 #

3 3 0 ln

4


Page 8 of 24

Page 9 of 24

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


Figure 3: Example of the model used to approximate the BCP structure. The lamella interface is defined by a spline, where the nodes of the spline are indicated by the orange spheres. The interfaces are symmetric according to the numbers at the top of the model, i.e. lines 1 and 1 are mirror images of each other. Each lamella was then discretized into a stack of trapezoids and designed as either PS (S), PMMA (M) or brush (B). The stacks are typically discretized into at least twice as many trapezoids as spline points, a smaller number of trapezoids are shown here for image clarity.

Results and Discussion. In order to investigate the impact of varying the width of the guiding stripe on the internal morphology of PS-b-PMMA, a BCP was assembled on templates with a wide range of W/Lo. resCDSAXS measurements were conducted at the carbon edge for samples with W/Lo ranging from ≈ 0.5 to ≈ 1.3. The scattering map obtained from a sample with W/Lo = 0.47 is shown in Figure 4A. (W was determined from the width at the top of the guiding stripe via SEM measurements). Five primary peaks are visible on the scattering map, with the spacing in the qx direction corresponding to the pitch of the BCP lamella (≈ 28 nm). The satellite peaks located between the primary scattering peaks and correspond to the pitch of the BCP template (≈ 84 nm). The satellite peaks are more sensitive to the template structure and to shifts in the lamella position within a unit cell compared to the primary scattering peaks, which are more sensitive to the average lamella shape. The qz cuts from the scattering map are shown in Figure 4B, along with the simulated scattering from the best model fit.



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 10 of 24

Figure 4: A) Scattering map from W/Lo = 0.47, primary scattering peaks are labeled in red numerals, unlabeled peaks are satellites which correspond to scattering from the superlattice structure induced by the chemical template. B) qz cuts obtained by integrating the peaks in the scattering map over the qx direction with experimental (○) and simulated data (-). Simulated scattering was calculated from the model shown in Figure 5. Primary scattering peaks are labeled in red numerals. The data is shifted vertically for clarity. Figure 5 shows the best fit to the scattering map in Figure 4A. When modeling an inverse problem as few parameters should be used as possible, to decrease the potential for multiple solutions and parameter correlations. In order to determine what is the minimum number of parameters which generates the best fit multiple independent runs were performed with different numbers of spline points in the stack, ranging from 3 to 11. In addition to the model which used an interpolated spline to define the edge profile of the lamella, a model which simply used a stack of trapezoids was also examined. The spline model has the advantage of being able to define a smoother edge profile with a smaller number of parameters relative to the trapezoid stack model. It also achieved lower GF and BIC for equivalent numbers of model parameters. Figure S3 shows the comparison between GF and BIC for the two different approaches to defining the model structures. The best GF value obtained with each number of spline points is shown in


Page 11 of 24

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


Figure 5D: the fit quality improves quickly from 3 to 5 spline points then gradually reduces until 9 points are used. Beyond this point a small reduction in the GF is observed, but the BIC begins to increase. This indicates that the use of more than 9 spline points in the model does not result in a meaningful improvement in the GF. The shape of the model which resulted in the best fit for each number of spline points is shown in Figure S1 in the supplemental information. The transition from 4 to 5 points in the model corresponds with the largest decrease in the GF and also the emergence of the narrowing of the PS lamella above the X-PS stripe. The next most significant change can be seen to correspond with the emergence of the oscillations in the profile of the PS lamella on the neutral brush, occurring during the addition of the 8th point to the model. This could be indicative of structural variations along the length of the line, as the measured result is the average profile over the area of the beam. The results of the uncertainty analysis conducted using the MCMC algorithm are shown Figure 5A. The solid lines represent the average of the sampled population and the dashed lines show the 95 % confidence intervals. The largest model uncertainties are observed around the base of the structure and near the top of the lines, while the uncertainties around the bulk of the lamella are very small. The width of the chemical template below the height of the neutral brush has significantly more uncertainty than any other portion of the model. The neutral brush is composed of approximately equal amounts of PS and PMMA, as a result the optical constants for the brush will be halfway between the two polymers. The contrast (Eq 5) between the brush and the PS layer will be about a quarter of the contrast between the PS and PMMA lamella. The combination of the reduced contrast and relatively small volume fraction of this region results in the greater uncertainty of the template shape relative to the rest of the structure. The DW factor for this sample was found to be 2.31 ± 0.07 nm, this can be converted to an interface width (aI) equivalent to the root mean squared roughness at the interface according to Eq 6., resulting in aI = 5.78 ± 0.18 nm. This value is slightly larger than the established interface width value for PS-b-PMMA of 5 nm,57 indicating that it consists of the native interface width convolved with position fluctuations driven by the chemical template. Because the DW factor is a bulk value the distribution of these fluctuations, whether they occur in all lamella or potentially just in lamella on the neutral brush, is unclear. Figure 5B represents the



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 12 of 24

position of the lamella convolved with contributions from the DW factor. The interface width far exceeds the model uncertainties shown in Figure 5A. Interestingly the PMMA lamella to the left and right side of the template appear to wet the exposed X-PS just above the neutral brush. Recent results have shown that portions of the X-PS sidewalls may be PMMA preferential due to oxidation during the etch process.31 It could be this preference for the PMMA lamella which induces the interface position variations above the template surface.

Figure 5: A) Best fit obtained for W/Lo = 0.47 (scattering pattern shown in Figure 4) using the spline model with 9 spline points. B) Best fit convolved with the DW factor, the space encompassed by the horizontal error bars represent the interface region between the PS and PMMA blocks C) Best fit showing two unit cells with red indicating PS, blue indicating PMMA and purple being the neutral brush. D) GF (■) and BIC (∆) as a function of the number of spline points and total model parameters.

/ = 6! − 7 8 3 69! − 97 8

5

:; = √2>?@ 6


Page 13 of 24

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


W/Lo = 0.47 is close to the ideal value of 0.5 and it is reasonable to anticipate the formation of continuous, perpendicularly oriented lamella. At W/Lo = 0.66 (shown in the supplemental information, Figure S3, S4) a continuous lamella above the X-PS stripe is also observed. As W/Lo increases it becomes important to test possible alternatives to compare how well those structures fit the scattering. In addition to the continuous lamella model alternative morphologies will be examined including broken PS lamella centered over the X-PS stripe (referred to as “Broken lines” for brevity) and structures where the PMMA line is at the center of the X-PS stripe (this will be referred to as the “U” model). All models will be tested using an increasing number of spline points in an approach identical to the first sample. The best fit to the scattering pattern obtained for W/Lo = 0.73 is shown in Figure 6A. All three models were tested for this sample, with the continuous lamella centered over the X-PS stripe providing the best fit, followed by broken lines, then the “U” model which resulted in the worst fit of the three. The GF and BIC as a function of the number of spline points for all three models are shown in Figure 7. With the wider X-PS stripe the oscillations around the lamella on that portion of the template observed for W/Lo = 0.47 are no longer observed. This suggests that the PS preferential portion of the template is more commensurate with the width of the PS lamella compared to the sample with the narrower X-PS template.



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 14 of 24

Figure 6: Results of res-CDSAXS measurements on W/Lo = 0.873 fit with 9 spline points. GF and BIC as a function of spline points are shown in Figure 7. A) Best fit (solid Line) with 95 % confidence intervals (dashed line) from MCMC algorithm. B) Experimental (○) and simulated data (-). qz cuts C) Two unit cells of the best fit with red indicating PS, blue indicating PMMA and purple being the neutral brush.


Page 15 of 24

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


Figure 7: GF (■) and BIC (∆) for W/Lo = 0.73 as a function of the number of spline points for all three models tested, continuous PS lamella centered over the X-PS stripe (black), broken PS lamella centered over the X-PS stripe (red) and continuous lamella with PMMA centered over the X-PS stripe (blue).

The sample with the widest X-PS stripe (W/Lo = 1.14) resulted in a shift from the PS line centered over the X-PS stripe to the PMMA line centered over the X-PS stripe. (Another sample was examined with a W/Lo = 0.93, a clear determination of the morphology could not be made for this sample, the results of that analysis are detailed in the SI). The results of this fit are shown in Figure 8, with the GF



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 16 of 24

and BIC as a function of spline points shown in Figure 9. For this sample the “U” model produced the best fit at all points which were tested, reaching a minima in the BIC at 6 points. As more parameters are added the fit quality of the other models begins to improve but never reaches that of the “U” model. One of the most noticeable features of this fit compared to the previous samples is the flaring out of the PS lamella at the edges of the template. This stretching is likely necessary to accommodate the PMMA lamella which is now centered above the X-PS stripe. The shift from PS centered to PMMA centered arrangements minimizes the contact area between the X-PS and PMMA block. This sample had a DW = 2.38 ± 0.12, similar to W/Lo = 0.53, indicating that both samples had comparable position fluctuations.

Figure 8: Results of res-CDSAXS measurements on W/Lo = 1.14. A) Best fit (solid Line) with 95 % confidence intervals (dashed line) from MCMC algorithm. B) Experimental (○) and simulated data (-). qz


Page 17 of 24

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


cuts C) Two unit cells of the best fit with the “U” model with red indicating PS, blue indicating PMMA and purple being the neutral brush.

Figure 9: GF (■) and BIC (∆) for W/Lo = 1.14 as a function of the number of spline points for all three models tested, continuous PS lamella centered over the X-PS stripe (black), broken PS lamella centered over the X-PS stripe (red) and continuous lamella with PMMA centered over the X-PS stripe (blue).

The results for all four samples examined are summarized in Figure 10, where the best fit to each scattering profile is accompanied by an image of the first order diffraction peak corresponding to the pitch of the BCP. Expansion of the guide stripe width eventually results in a shift from PS lamella centered over the X-PS stripe to PMMA lamella centered over the X-PS stripe. There is significant variation in the shape of the footing of the X-PS guiding line for the four samples, especially for the structure beneath the



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 18 of 24

surface of the brush layer. As discussed for the W/Lo ≈ 0.47 sample, this is the region with the greatest amount of uncertainty. In addition to the model structures Figure 9 has images of the first order peak at normal incidence. In all cases sharp diffraction peaks are observed, with a small amount of arcing corresponding to misaligned sections of the BCP. For W/Lo < 1 the amount of arcing is extremely small, with over 99.8 % of the intensity observed being found within 1° of the center of the line (essentially the width of the diffraction peak). W/Lo = 1.14 shows significantly more arcing (97.6 % of the observed intensity within 1°), indicating that a larger fraction of lamella are misaligned relative to the chemical template compared to the narrower guiding stripes.


Page 19 of 24

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


Figure 10: Impact of template width on the internal structure of PS-b-PMMA for all four samples examined, along with the image of the first order diffraction peak. A) W/Lo = 0.47, B) W/Lo = 0.66, C) W/Lo = 0.73, D) W/Lo = 1.14.

Conclusions The impact of guide stripe width on the internal structure of 28 nm PS-b-PMMA patterned on an 84 nm chemical template was examined using res-CDSAXS. Measurements using soft x-rays at 282 eV enabled enhancement of the contrast between PS and PMMA by utilizing resonant scattering from the aromatic rings in PS. When the guide stripe width was approximately commensurate with the width of the PS lamella only small variations in the interface profile near the template surface were observed. Examination of a series of different morphologies for wider template widths shows a shift from the PS lamella centered on the guide stripe to the PMMA lamella centered on the guide stripe. For all samples analysis of the DW factor showed that the average interface width was wider by almost 1 nm compared to the native PS-b-PMMA interface width. This suggests that in addition to the native interfacial width there are position fluctuations driven by the template increase the roughness perceived by the measurement. These results demonstrate important insights into how the template structure impacts the assembly and alignment of BCPs in chemoepitaxy DSA. Acknowledgements: Official contribution of the National Institute of Standards and Technology; not subject to copyright in the United States. The Advanced Light Source is supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. We thank Anthony Young and Cheng Wang for assistance at BL 11.0.1.2. Use of the Center for Nanoscale Materials of Argonne National Laboratory was supported by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC0206CH11357. The project was in part funded by award 70NHNB14H012 from the U.S. Department of Commerce, National Institute of Standards and Technology, as part of the Center for Hierarchical Materials Design (CHiMaD).

Supporting Information: Includes the model development details, GF plots and representative fits.

References



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

(1)

(2)

(3)

(4)

(5) (6) (7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

Ruiz, R.; Kang, H.; Detcheverry, F. A.; Dobisz, E.; Kercher, D. S.; Albrecht, T. R.; de Pablo, J. J.; Nealey, P. F. Density Multiplication and Improved Lithography by Directed Block Copolymer Assembly. Science 2008, 321 (5891), 936–939. Kim, S. O.; Solak, H. H.; Stoykovich, M. P.; Ferrier, N. J.; de Pablo, J. J.; Nealey, P. F. Epitaxial SelfAssembly of Block Copolymers on Lithographically Defined Nanopatterned Substrates. Nature 2003, 424 (6947), 411–414. Stoykovich, M. P.; Kang, H.; Daoulas, K. C.; Liu, G.; Liu, C.-C.; de Pablo, J. J.; Müller, M.; Nealey, P. F. Directed Self-Assembly of Block Copolymers for Nanolithography: Fabrication of Isolated Features and Essential Integrated Circuit Geometries. ACS Nano 2007, 1 (3), 168–175. Cheng, J. Y.; Sanders, D. P.; Truong, H. D.; Harrer, S.; Friz, A.; Holmes, S.; Colburn, M.; Hinsberg, W. D. Simple and Versatile Methods To Integrate Directed Self-Assembly with Optical Lithography Using a Polarity-Switched Photoresist. ACS Nano 2010, 4 (8), 4815–4823. Xiao, S.; Yang, X.; Steiner, P.; Hsu, Y.; Lee, K.; Wago, K.; Kuo, D. Servo-Integrated Patterned Media by Hybrid Directed Self-Assembly. ACS Nano 2014, 8 (11), 11854–11859. Luo, M.; Epps, T. H. Directed Block Copolymer Thin Film Self-Assembly: Emerging Trends in Nanopattern Fabrication. Macromolecules 2013, 130830133651005. Wan, L.; Ruiz, R.; Gao, H.; Patel, K. C.; Lille, J.; Zeltzer, G.; Dobisz, E. A.; Bogdanov, A.; Nealey, P. F.; Albrecht, T. R. Fabrication of Templates with Rectangular Bits on Circular Tracks by Combining Block Copolymer Directed Self-Assembly and Nanoimprint Lithography. J. MicroNanolithography MEMS MOEMS 2012, 11 (3), 031405–1. Tsai, H.; Pitera, J. W.; Miyazoe, H.; Bangsaruntip, S.; Engelmann, S. U.; Liu, C.-C.; Cheng, J. Y.; Bucchignano, J. J.; Klaus, D. P.; Joseph, E. A.; Sanders, D. P.; Colburn, M. E.; Guillorn, M. A. TwoDimensional Pattern Formation Using Graphoepitaxy of PS- B -PMMA Block Copolymers for Advanced FinFET Device and Circuit Fabrication. ACS Nano 2014, 8 (5), 5227–5232. Van Look, L.; Rincon Delgadillo, P.; Lee, Y.; Pollentier, I.; Gronheid, R.; Cao, Y.; Lin, G.; Nealey, P. F. High Throughput Grating Qualification of Directed Self-Assembly Patterns Using Optical Metrology. Microelectron. Eng. 2014, 123, 175–179. Dixit, D. J.; Kamineni, V.; Farrell, R.; Hosler, E. R.; Preil, M.; Race, J.; Peterson, B.; Diebold, A. C. Metrology for Block Copolymer Directed Self-Assembly Structures Using Mueller Matrix-Based Scatterometry. J. MicroNanolithography MEMS MOEMS 2015, 14 (2), 021102–021102. Dixit, D.; Kamineni, V.; Farrell, R.; Hosler, E.; Preil, M.; Race, J.; Peterson, B.; Diebold, A. C. Metrology for Directed Self-Assembly Block Lithography Using Optical Scatterometry; Cain, J. P., Sanchez, M. I., Eds.; 2014; p 90500N. Kato, T.; Sugiyama, A.; Ueda, K.; Yoshida, H.; Miyazaki, S.; Tsutsumi, T.; Kim, J.; Cao, Y.; Lin, G. Advanced CD-SEM Metrology for Pattern Roughness and Local Placement of Lamellar DSA; Cain, J. P., Sanchez, M. I., Eds.; 2014; p 90501T. Ito, C.; Durant, S.; Lange, S.; Harukawa, R.; Miyagi, T.; Nagaswami, V.; Rincon Delgadillo, P.; Gronheid, R.; Nealey, P. Inspection of Directed Self-Assembly Defects. In Proc. SPIE; Resnick, D. J., Bencher, C., Eds.; 2014; Vol. 9049, p 90492D. Rincon Delgadillo, P. A.; Gronheid, R.; Thode, C. J.; Wu, H.; Cao, Y.; Somervell, M.; Nafus, K.; Nealey, P. F. All Track Directed Self-Assembly of Block Copolymers: Process Flow and Origin of Defects. In Proc. SPIE; Tong, W. M., Ed.; 2012; Vol. 8323, p 83230D. Liu, C.-C.; Ramírez-Hernández, A.; Han, E.; Craig, G. S. W.; Tada, Y.; Yoshida, H.; Kang, H.; Ji, S.; Gopalan, P.; de Pablo, J. J.; Nealey, P. F. Chemical Patterns for Directed Self-Assembly of Lamellae-Forming Block Copolymers with Density Multiplication of Features. Macromolecules 2013, 46 (4), 1415–1424.


Page 20 of 24

Page 21 of 24

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


(16)

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24) (25)

(26) (27)

(28)

(29) (30)

(31)

(32)

Liu, C.-C.; Han, E.; Onses, M. S.; Thode, C. J.; Ji, S.; Gopalan, P.; Nealey, P. F. Fabrication of Lithographically Defined Chemically Patterned Polymer Brushes and Mats. Macromolecules 2011, 44 (7), 1876–1885. Sunday, D. F.; Ashley, E.; Wan, L.; Patel, K. C.; Ruiz, R.; Kline, R. J. Template-Polymer Commensurability and Directed Self-Assembly Block Copolymer Lithography. J. Polym. Sci. Part B Polym. Phys. 2015, 53 (8), 595–603. Park, S.-M.; Craig, G. S.; Liu, C.-C.; La, Y.-H.; Ferrier, N. J.; Nealey, P. F. Characterization of Cylinder-Forming Block Copolymers Directed to Assemble on Spotted Chemical Patterns. Macromolecules 2008, 41 (23), 9118–9123. Kang, H.; Craig, G. S. W.; Han, E.; Gopalan, P.; Nealey, P. F. Degree of Perfection and Pattern Uniformity in the Directed Assembly of Cylinder-Forming Block Copolymer on Chemically Patterned Surfaces. Macromolecules 2012, 45 (1), 159–164. Pandav, G.; Durand, W. J.; Ellison, C. J.; Willson, C. G.; Ganesan, V. Directed Self Assembly of Block Copolymers Using Chemical Patterns with Sidewall Guiding Lines, Backfilled with Random Copolymer Brushes. Soft Matter 2015, 11 (47), 9107–9114. Liu, C.-C.; Thode, C. J.; Rincon Delgadillo, P. A.; Craig, G. S. W.; Nealey, P. F.; Gronheid, R. Towards an All-Track 300 Mm Process for Directed Self-Assembly. J. Vac. Sci. Technol. B Microelectron. Nanometer Struct. 2011, 29 (6), 06F203. Delgadillo, P. R.; Harukawa, R.; Suri, M.; Durant, S.; Cross, A.; Nagaswami, V. R.; Heuvel, D. V. D.; Gronheid, R.; Nealey, P. Defect Source Analysis of Directed Self-Assmebly Process (DSA of DSA). In Proceedings of SPIE; 2013; Vol. 8680, p 86800L. Son, J. G.; Hannon, A. F.; Gotrik, K. W.; Alexander-Katz, A.; Ross, C. A. Hierarchical Nanostructures by Sequential Self-Assembly of Styrene-Dimethylsiloxane Block Copolymers of Different Periods. Adv. Mater. 2011, 23 (5), 634–639. Chang, J.-B.; Son, J. G.; Hannon, A. F.; Alexander-Katz, A.; Ross, C. A.; Berggren, K. K. Aligned Sub10-Nm Block Copolymer Patterns Templated by Post Arrays. ACS Nano 2012, 6 (3), 2071–2077. KG, A. T.; Gotrik, K. W.; Hannon, A. F.; Alexander-Katz, A.; Ross, C. A.; Berggren, K. K. Templating Three-Dimensional Self-Assembled Structures in Bilayer Block Copolymer Films. Science 2012, 336 (6086), 1294–1298. Jung, Y. S.; Ross, C. A. Orientation-Controlled Self-Assembled Nanolithography Using a Polystyrene−Polydimethylsiloxane Block Copolymer. Nano Lett. 2007, 7 (7), 2046–2050. Park, S.-M.; Stoykovich, M. P.; Ruiz, R.; Zhang, Y.; Black, C. T.; Nealey, P. F. Directed Assembly of Lamellae- Forming Block Copolymers by Using Chemically and Topographically Patterned Substrates. Adv. Mater. 2007, 19 (4), 607–611. Zhang, X.; Murphy, J. N.; Wu, N. L. Y.; Harris, K. D.; Buriak, J. M. Rapid Assembly of Nanolines with Precisely Controlled Spacing from Binary Blends of Block Copolymers. Macromolecules 2011, 44 (24), 9752–9757. Tang, C.; Lennon, E. M.; Fredrickson, G. H.; Kramer, E. J.; Hawker, C. J. Evolution of Block Copolymer Lithography to Highly Ordered Square Arrays. Science 2008, 322 (5900), 429–432. Ji, S.; Nagpal, U.; Liu, G.; Delcambre, S. P.; Müller, M.; de Pablo, J. J.; Nealey, P. F. Directed Assembly of Non-Equilibrium ABA Triblock Copolymer Morphologies on Nanopatterned Substrates. ACS Nano 2012, 6 (6), 5440–5448. Williamson, L. D.; Seidel, R. N.; Chen, X.; Suh, H. S.; Rincon Delgadillo, P.; Gronheid, R.; Nealey, P. F. Three-Tone Chemical Patterns for Block Copolymer Directed Self-Assembly. ACS Appl. Mater. Interfaces 2016, 8 (4), 2704–2712. Cushen, J.; Wan, L.; Blachut, G.; Maher, M. J.; Albrecht, T. R.; Ellison, C. J.; Willson, C. G.; Ruiz, R. Double-Patterned Sidewall Directed Self-Assembly and Pattern Transfer of Sub-10 Nm PTMSS- B PMOST. ACS Appl. Mater. Interfaces 2015, 7 (24), 13476–13483.



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

(33) (34)

(35)

(36) (37)

(38)

(39) (40)

(41) (42) (43)

(44)

(45)

(46) (47)

(48)

(49)

Welander, A. M.; Craig, G. S. W.; Tada, Y.; Yoshida, H.; Nealey, P. F. Directed Assembly of Block Copolymers in Thin to Thick Films. Macromolecules 2013, 46 (10), 3915–3921. Segal-Peretz, T.; Winterstein, J.; Doxastakis, M.; Ramírez-Hernández, A.; Biswas, M.; Ren, J.; Suh, H. S.; Darling, S. B.; Liddle, J. A.; Elam, J. W.; de Pablo, J. J.; Zaluzec, N. J.; Nealey, P. F. Characterizing the Three-Dimensional Structure of Block Copolymers via Sequential Infiltration Synthesis and Scanning Transmission Electron Tomography. ACS Nano 2015, 9 (5), 5333–5347. Segal-Peretz, T.; Zhou, C.; Ren, J.; Dazai, T.; Ocola, L. E.; Divan, R. N. S.; Nealey, P. F. Three Dimensional Assembly in Directed Self-Assembly of Block Copolymers. J. Photopolym. Sci. Technol. 2016, 29 (5), 653. Carpenter, J. H.; Hunt, A.; Ade, H. Characterizing Morphology in Organic Systems with Resonant Soft X-Ray Scattering. J. Electron Spectrosc. Relat. Phenom. 2015, 200, 2–14. Wang, C.; Lee, D. H.; Hexemer, A.; Kim, M. I.; Zhao, W.; Hasegawa, H.; Ade, H.; Russell, T. P. Defining the Nanostructured Morphology of Triblock Copolymers Using Resonant Soft X-Ray Scattering. Nano Lett. 2011, 11 (9), 3906–3911. Virgili, J. M.; Tao, Y.; Kortright, J. B.; Balsara, N. P.; Segalman, R. A. Analysis of Order Formation in Block Copolymer Thin Films Using Resonant Soft X-Ray Scattering. Macromolecules 2007, 40 (6), 2092–2099. Chen, X. C.; Kortright, J. B.; Balsara, N. P. Water Uptake and Proton Conductivity in Porous Block Copolymer Electrolyte Membranes. Macromolecules 2015, 48 (16), 5648–5655. Wang, C.; Garcia, A.; Yan, H.; Sohn, K. E.; Hexemer, A.; Nguyen, T.-Q.; Bazan, G. C.; Kramer, E. J.; Ade, H. Interfacial Widths of Conjugated Polymer Bilayers. J. Am. Chem. Soc. 2009, 131 (35), 12538–12539. Stone, K. H.; Kortright, J. B. Molecular Anisotropy Effects in Carbon K -Edge Scattering: Depolarized Diffuse Scattering and Optical Anisotropy. Phys. Rev. B 2014, 90 (10). Sunday, D. F.; Kline, R. J. Reducing Block Copolymer Interfacial Widths through Polymer Additives. Macromolecules 2015, 48 (3), 679–686. Collins, B. A.; Cochran, J. E.; Yan, H.; Gann, E.; Hub, C.; Fink, R.; Wang, C.; Schuettfort, T.; McNeill, C. R.; Chabinyc, M. L.; Ade, H. Polarized X-Ray Scattering Reveals Non-Crystalline Orientational Ordering in Organic Films. Nat. Mater. 2012, 11 (6), 536–543. Yan, H.; Collins, B. A.; Gann, E.; Wang, C.; Ade, H.; McNeill, C. R. Correlating the Efficiency and Nanomorphology of Polymer Blend Solar Cells Utilizing Resonant Soft X-Ray Scattering. ACS Nano 2012, 6 (1), 677–688. Ingham, B.; Erlangga, G. D.; Smialowska, A.; Kirby, N. M.; Wang, C.; Matia-Merino, L.; Haverkamp, R. G.; Carr, A. J. Solving the Mystery of the Internal Structure of Casein Micelles. Soft Matter 2015, 11 (14), 2723–2725. Wilkins, S.; Hatton, P.; Roper, M.; Prabhakaran, D.; Boothroyd, A. Soft X-Ray Resonant Magnetic Diffraction. Phys. Rev. Lett. 2003, 90 (18). Benckiser, E.; Haverkort, M. W.; Brück, S.; Goering, E.; Macke, S.; Frañó, A.; Yang, X.; Andersen, O. K.; Cristiani, G.; Habermeier, H.-U.; Boris, A. V.; Zegkinoglou, I.; Wochner, P.; Kim, H.-J.; Hinkov, V.; Keimer, B. Orbital Reflectometry of Oxide Heterostructures. Nat. Mater. 2011, 10 (3), 189– 193. Lefevre, C.; Thomasson, A.; Roulland, F.; Favre-Nicolin, V.; Joly, Y.; Wakabayashi, Y.; Versini, G.; Barre, S.; Leuvrey, C.; Demchenko, A.; Boudet, N.; Viart, N. Determination of the Cationic Distribution in Oxidic Thin Films by Resonant X-Ray Diffraction: The Magnetoelectric Compound Ga 2− X Fe X O 3. J. Appl. Crystallogr. 2016, 49 (4), 1308–1314. Sunday, D. F.; Hammond, M. R.; Wang, C.; Wu, W.; Delongchamp, D. M.; Tjio, M.; Cheng, J. Y.; Kline, R. J.; Pitera, J. W. Determination of the Internal Morphology of Nanostructures Patterned by Directed Self Assembly. ACS Nano 2014, 8 (8), 8426–8437.


Page 22 of 24

Page 23 of 24

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


(50)

(51) (52)

(53)

(54)

(55) (56)

(57)

Sunday, D. F.; Hammond, M. R.; Wang, C.; Wu, W.; Kline, R. J.; Stein, G. E. Three-Dimensional XRay Metrology for Block Copolymer Lithography Line-Space Patterns. J. MicroNanolithography MEMS MOEMS 2013, 12 (3), 031103 1–7. Sunday, D. F.; List, S.; Chawla, J. S.; Kline, R. J. Determining the Shape and Periodicity of Nanostructures Using Small-Angle X-Ray Scattering. J. Appl. Crystallogr. 2015, 48 (5). Sunday, D. F.; List, S.; Chawla, J. S.; Kline, R. J. Evaluation of the Effect of Data Quality on the Profile Uncertainty of Critical Dimension Small Angle X-Ray Scattering. J. MicroNanolithography MEMS MOEMS 2016, 15 (1), 014001–014001. Ren, J.; Ocola, L. E.; Divan, R.; Czaplewski, D. A.; Segal-Peretz, T.; Xiong, S.; Kline, R. J.; Arges, C. G.; Nealey, P. F. Post-Directed-Self-Assembly Membrane Fabrication for in Situ Analysis of Block Copolymer Structures. Nanotechnology 2016, 27 (43), 435303. Certain Commercial Equipment, Instruments, or Materials Are Identified in This Paper in Order to Specify the Experimental Procedure Adequately. Such Identification Is Not Intended to Imply Recommendation or Endorsement by the National Institute of Standards and Technology, nor Is It Intended to Imply That the Materials or Equipment Identified Are Necessarily the Best Available for the Purpose. Hannon, A. F.; Sunday, D. F.; Windover, D.; Joseph Kline, R. Advancing X-Ray Scattering Metrology Using Inverse Genetic Algorithms. J. MicroNanolithography MEMS MOEMS 2016, 15 (3), 034001. DeCaluwe, S. C.; Kienzle, P. A.; Bhargava, P.; Baker, A. M.; Dura, J. A. Phase Segregation of Sulfonate Groups in Nafion Interface Lamellae, Quantified via Neutron Reflectometry Fitting Techniques for Multi-Layered Structures. Soft Matter 2014, 10 (31), 5763. Anastasiadis, S. H.; Russell, T. P.; Satija, S. K.; Majkrzak, C. F. The Morphology of Symmetric Diblock Copolymers as Revealed by Neutron Reflectivity. J. Chem. Phys. 1990, 92 (9), 5677.



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

Table of Contents Graphic


Page 24 of 24

Characterizing Patterned Block Copolymer Thin ... - ACS Publications

Recommend Documents