Optical reflectance-based software forautomated characterization of nanomaterials:
outcomes of the NSF Nanohub’s NanoMFG nodeVu Nguyen1, Wan Li2, Hannah Gramling1, Yunsu Park1, Ke Xu2, and Hayden Taylor1,*Department of Mechanical Engineering1 and Department of Chemistry2
University of California, Berkeley, CA 94720.
*E-mail: hkt@berkeley.edu

We introduce two software tools to aid in the characterization of nanoscale-thickness materials,
and in the development of nanomanufacturing processes based on them. The first tool,
2dreflect, automatically determines from optical reflectance images the spatial distribution of
the number of atomic layers of a 2D material—or heterostructures of multiple materials—on aflat substrate. Scaling up the manufacturing of devices made from atomically-thin 2D materials
demands high-throughput, non-destructive characterization techniques to provide insights into
the materials’ quality and areal yield. Thin-film optical interference, an inherent effect in theobservation of transparent layered structures [1], provides a promising pathway to studying 2D
materials since it can resolve sub-nanometer thickness differences and can be quickly recordedwith a simple optical setup. Although thin-film interference has been widely used to determine
the number of atomic layers in experimental samples via white light optical microscopy [2], it
requires careful calibration and human judgement when interpreting images. What is needed
for more robust detection is an image-processing algorithm to analyze reflected light intensities
and determine material composition automatically.
We have built such an analysis software tool, called 2dreflect, and used it successfully tocharacterize monolayers, homogenous multilayers, and heterostructures of MoS2 and WS2. The
tool is based on simulation of how a sample’s surface reflectance—relative to that of a bareadjacent substrate—depends on illumination wavelength and layer thickness composition. The
well-known transfer matrix formulation is used, and when given one or more reflection images
obtained at known wavelengths, the tool tags regions of the image from a specified set of
possible layer combinations. We show that 2dreflect distinguishes reliably between MoS2
samples ranging from 1 to 4 molecular layers in thickness (Fig. 1). We can also resolve thesmall differences between bilayer samples that have been constructed from two monolayers by
sequential mechanical exfoliation without angular alignment, and bilayers exfoliated directlyfrom a mined crystal, whose layers are expected to be aligned and therefore more closely
spaced. We further observe that after thermal annealing, the optical signature of artificiallyconstructed bilayers approaches that of natural bilayers. We have used 2dreflect to analyze
mechanically exfoliated and chemical vapor-deposited material. The software is implemented
with a graphical interface and is scheduled to be released on nanohub.org [3] in summer 2019.
The second tool, nanovisc, uses color video of a nanoimprint lithography process to determine
the effective viscosity of the resist. Using our previously described ‘nanocaliper’ apparatus [4],a patterned, semi-transparent stamp is pressed into a spun-on film of UV-curing resist by aconstant backside pneumatic pressure (Fig. 2a). Reduction of the resist’s residual layer
thickness (RLT) over time is tracked by imaging the intensity minima and maxima of red andblue LED light that undergoes thin-film interference in the resist and is partially reflected
through the stamp (Fig. 2b). The extracted RLT–time relationship is interpreted with squeezefilm theory to estimate resist viscosity, potentially accelerating the screening of resist
formulations, pre-bake processes, and UV exposure recipes.

References[1] e.g. W. Li et al., Nano Lett 16, 5027, 2016.
[2] e.g. Nolen et al., ACS Nano 5 (2), 914–922, 2011.
[3] 2dreflect and nanovisc are among the software tools being developed at U.C. Berkeley as part of
the NanoMFG node, a five-year partnership with the University of Illinois at Urbana–Champaign,
funded via the National Science Foundation’s Nanohub.
[4] H. Taylor and N. Dhakal, Proc. NNT 2013; H. Gramling and H. Taylor, Proc. MNE 2016.

(a)

(b)

Figure 1. Operation of the 2dreflect tool. (a) Unprocessed white-light optical microscopy image of two
sets of mechanically exfoliated MoS2 patterns, many of them monolayer, that were sequentiallydeposited onto an SiO2/Si substrate Rectangular features are about 40 µm wide. Overlap regions ofinterest are circled with dashed white lines. (b) Pseudocolor image after analysis by 2dreflect, whereeach color corresponds to a particular layer composition according to the legend. Results have beenvalidated with atomic force microscopy and photoluminescence imaging.

(a)

(b)

Figure 2. Operation of the nanovisc tool. (a) Nanocaliper setup capturing temporal variation of reflected
illumination as RLT reduces [4]; (b) User interface of nanovisc tool showing how peaks and troughs of
red and blue reflected intensities are identified and mapped unambiguously to particular RLT values
that are registered in time. The time course of RLT is then interpreted with a squeeze-film flow model
to evaluate effective viscosity and assess whether resist behavior deviates significantly from Newtonian.