Dataset for "Understanding the resolution limit of Displacement Talbot Lithography"

Displacement Talbot lithography (DTL) is a new technique for patterning large areas with sub-micron periodic features with low cost. It has application in fields which cannot justify the cost of deep-UV photolithography such as plasmonics, photonic crystals, and metamaterials and competes with techniques such as nanoimprint and laser interference lithography. It is based on the interference of coherent light through a periodically patterned photomask. However, the factors affecting the resolution limit of the technique are unknown. Through computer simulations, we show the impact of the mask parameters on the size of the features that can be achieved and describe the separate figures of merit that should be optimised for successful patterning. Both amplitude and phase masks are considered for hexagonal and square arrays of openings on the mask. For large pitches, amplitude masks are shown to give the best resolution, whereas, for small pitches, phase masks are superior due to the shorter exposure time that is required. We also show how small changes in the mask pitch can dramatically affect the resolution achievable. As a result, this study provides important information for choosing new masks for DTL for targeted applications.

This dataset is the result of a modelling but also experimental investigation of the DTL resolution for a specific resist and wavelength. The data was acquired using a Hitachi S-4300 scanning electron microscope (SEM), and a MATLAB code.

Keywords:
nanostructures, DTL, Modelling, Resolution, Lithography
Subjects:
Materials processing
Optics, photonics and lasers

Cite this dataset as:
Chausse, P., Le Boulbar, E., Lis, S., Shields, P., 2019. Dataset for "Understanding the resolution limit of Displacement Talbot Lithography". Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00570.

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Data

Fig3_analysis_1um.xlsx
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet (28kB)
Creative Commons: Attribution 4.0

Figure 3: Statistical analysis of the SEM pictures for the 1 µm pitch hexagonal mask.

Fig3_1um_mask_SEM_pictures.zip
application/zip (4MB)
Creative Commons: Attribution 4.0

Figure 3: SEM pictures for the 1 µm pitch hexagonal mask.

Fig3_analysis_1.5um.xlsx
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet (16kB)
Creative Commons: Attribution 4.0

Figure 3: Statistical analysis of the SEM pictures for the 1.5 µm pitch hexagonal mask.

Fig3_1.5um_mask.zip
application/zip (2MB)
Creative Commons: Attribution 4.0

Figure 3: SEM pictures for the 1.5 µm pitch hexagonal mask.

Fig4_data.zip
application/zip (131kB)
Creative Commons: Attribution 4.0

Data of Fig. 4: theoretical width, minimum background, and maximum secondary patterns correspond to width, Min, and Maxbackground respectively. X and Y are the axis index used.

Fig5_data.zip
application/zip (1kB)
Creative Commons: Attribution 4.0

Data of Fig. 5: theoretical width and maximum secondary patterns correspond to width and Maxbackground respectively. x the axis index used.

Fig6_data.zip
application/zip (123kB)
Creative Commons: Attribution 4.0

Data of Fig. 6: theoretical width, minimum background, and maximum secondary patterns correspond to width, Min, and Maxbackground respectively. X and Y are the axis index used.

Fig8_data.zip
application/zip (179kB)
Creative Commons: Attribution 4.0

Data of Fig. 8: theoretical width, minimum background, ratio of maximum intensity between neighbouring features, and maximum secondary patterns correspond to width, Min, Diffprimsecond and Maxbackground respectively. X and Y are the axis index used.

Fig9_data.zip
application/zip (171kB)
Creative Commons: Attribution 4.0

Data of Fig. 9: theoretical width, minimum background, ratio of maximum intensity between neighbouring features, and maximum secondary patterns correspond to width, Min, Diffprimsecond and Maxbackground respectively. X and Y are the axis index used.

readme.docx
application/vnd.openxmlformats-officedocument.wordprocessingml.document (12kB)
Creative Commons: Attribution 4.0

Explanation of the figures data.

Creators

Pierre Chausse
University of Bath

Emmanuel Le Boulbar
University of Bath

Szymon Lis
University of Bath

Philip Shields
University of Bath

Coverage

Collection date(s):

From 2016 to 2018

Documentation

Data collection method:

Full details may be found in the associated paper.

Technical details and requirements:

Secondary electron images were captured using a Hitachi S-4300 scanning electron microscope (SEM). An accelerating voltage of 5 kV was used to collect the images. The statistical analysis was performed thanks to a image analysis software. The modelling has been performed thanks to a code in MATLAB.

Funders

Engineering and Physical Sciences Research Council (EPSRC)
https://doi.org/10.13039/501100000266

Manufacturing of Nano-Engineered III-N Semiconductors - Equipment
EP/M022862/1

Engineering and Physical Sciences Research Council (EPSRC)
https://doi.org/10.13039/501100000266

Manufacturing of Nano-Engineered III-N Semiconductors
EP/M015181/1

Publication details

Publication date: 20 February 2019
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-00570

URL for this record: https://researchdata.bath.ac.uk/id/eprint/570

Related articles

Chausse, P. J. P., Le Boulbar, E. D., Lis, S. D. and Shields, P. A., 2019. Understanding resolution limit of displacement Talbot lithography. Optics Express, 27(5), p.5918. Available from: https://doi.org/10.1364/OE.27.005918.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Departments:

Faculty of Engineering & Design
Electronic & Electrical Engineering

Research Centres & Institutes
Centre for Advanced Sensor Technologies (CAST)
Centre for Nanoscience and Nanotechnology
Centre for Sustainable Chemical Technologies
Condensed Matter Physics CDT