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Alex Ruyack, DecJan. 22, 2017 - Parts repurposed re-purposed from 2017 issue of the Nanometer
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Nanolithography is a fundamental requirement for the future of electronics patterning. Current trends indicate the end of Moore’s Law for traditional lithography processes. Directed self-assembly (DSA) of block copolymers (BCPs) can generate ordered, periodic arrays of various structures down to single nanometer (nm) size scale. The heterogeneous nature of these structures act intrinsically as their own mask, enabling nanometer (nm) scale resolution with a flood exposure and no traditional photo mask. BCP lithography offers low-cost processing of nm scale periodic structures typically only available by e-beam lithography, and can act as a complementary technology to conventional photolithography.
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Below, we detail our specific work on the PS-b-PMMA BCP while also providing insights necessary for determining if BCP lithography is right for your needs, and if so, how to chose and polymer and develop a process.
Block Copolymer Lithography Overview
BCP lithography relies on the microphase separation of the two comprising polymers to achieve a nanoscale pattern. Due to the reliance on self-assembly, the resulting photolithographic features are intrinsically periodic. As such, this process is useful for applications in areas where long range repeating structures are needed, such as nano-porous substrates, nanoparticle synthesis, or high-density information storage media.
For the development of this method, we used a poly(styrene-block-methyl methacrylate) (PS-b-PMMA) block copolymer due to its popularity in literature, which stems from its excellent etch selectivity, low surface energy mismatch, and theoretical 12 nm feature size.
The typical fabrication flow for a BCP lithographic process is shown in Figure 1 (left) (adapted from [1]). First, a surface treatment is applied to create a neutral layer/brush. This prevents a surface parallel BCP domain orientation from occurring by making the substrate surface interfacial energy equal for both polymer phases. Next, the BCP is spin coated and then thermally annealed allowing for phase separation and formation of the pattern. Finally, one phase is selectively removed and subsequent substrate processing can occur from this point.
Fig. 1: Left: Typical BCP lithography fabrication flow (adapted from [1]). Right: Fabrication flow for PS-b-PMMA BCP.
We used P9085-SMMAranOHT as our neutral layer and P8205-SMMA as our BCP (both obtained from Polymer Source). Our process flow follows that shown in Fig. 1 (right), where the etch is accomplished using a 220 nm flood exposure followed by an acetic acid dip. Various polymer concentrations, film thickness, and anneal conditions were tested for their effect on pattern formation (morphology, uniformity, periodicity, etc.). Figure 2 shows the resulting BCP thickness as a function of two solution concentrations (1 and 2% in toluene) and spin speed showing achievable thicknesses ranging from 30-150 nm. Figure 3 shows SEM micrographs of the BCP at various points in fabrication.
Fig. 2: Film thickness vs. spin speed for 1 and 2% PS-b-PMMA BCP in toluene
Fig 3: SEM micrographs of BCP film. Left: after annealing. Right: after etching. The increase in contrast comes from the removal of the PMMA phase in the pore regions after the etch.
In order to quantify the effect of our parameter sweeps it was necessary to develop an image processing technique that could quickly evaluate samples. We used ImageJ to develop two separate macros for 1) measuring feature sizes and 2) evaluating inter-feature spacing. In our case, the BCP morphology is a hexagonal array of pores, so these methods were tuned to generate information on pore diameter and interpore spacing. The former was accomplished using built in ImageJ functions and the Particle Analysis tool. The latter is comprised of built in ImageJ functions along with an additional macro for K-Nearest Neighbor analysis that was expanded on from an existing implementation, as well as a custom Matlab script [2]. Figure 4 shows the visual output of these macros.
Fig 4: Output of ImageJ macros. Left: Pore size analysis with designated pores shown in red. Right: K‑Nearest Neighbor Analysis with lines corresponding to 6 nearest neighbors.
Through this system of evaluation, we were able to achieve BCP films of 30 nm thickness with long range order. Pore sizes of ~23.12 nm with 1.78 nm standard deviation and interpore spacing of ~54.26 nm with 7.33 nm standard deviation and a circularity of ~0.92 were obtained. Figure 5 shows example SEM images of a typical sample. Using these films, pattern transfer through 50 to 100 nm of oxide has been achieved, as well as a subsequent Si etch (Figure 6).
Fig 5: SEM micrographs of optimized BCP film. Left: 350kx magnification showing pore diameter and interpore spacing uniformity. Right: 50kx magnification showing long range order.
Fig 6: SEM micrograph of BCP on 50nm of SiO2 on Si after CH2F2/He and HBr/Ar etch. Left: Top down. Right: Cleaved, 45 degrees.
In the future, we are working on various path forwards for BCP lithography implementation at the CNF. One path is further process tuning to reduce defects in the film and improve uniformity and periodicity. Beyond this, we are also looking into additional processing steps required to alter the BCP film morphology. In particular, we are working on a graphoepitaxy process that will result in parallelly aligned domains, rather than pores. Finally, we are also investigating other BCP systems for smaller features sizes (<10 nm), such as PS-b-PDMS.