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Optimization of e-beam lithography parameters for nanofabrication of sub-50 nm gold nanowires and nanogaps based on a bilayer lift-off process, Osman Sahin, Oguz Mustafa Albayrak, Murat Kaya Yapici, Nanotechnology, July 2024
https://iopscience.iop.org/article/10.1088/1361-6528/ad5e89
Electron beam lithography (EBL) stands out as a powerful direct-write tool offering nanometer-scale patterning capability and is especially useful in low-volume R&D prototyping when coupled with pattern transfer approaches like etching or lift-off. Among pattern transfer approaches, lift-off is preferred particularly in research settings, as it is cost-effective and safe and does not require tailored wet/dry etch chemistries, fume hoods, and/or complex dry etch tools; all-in-all offering convenient, 'undercut-free' pattern transfer rendering it useful, especially for metallic layers and unique alloys with unknown etchant compatibility or low etch selectivity. Despite the widespread use of the lift-off technique and optical/EBL for micron to even sub-micron scales, existing reports in the literature on nanofabrication of metallic structures with critical dimension in the 10–20 nm regime with lift-off-based EBL patterning are either scattered, incomplete, or vary significantly in terms of experimental conditions, which calls for systematic process optimization. To address this issue, beyond what can be found in a typical photoresist datasheet, this paper reports a comprehensive study to calibrate EBL patterning of sub-50 nm metallic nanostructures including gold nanowires and nanogaps based on a lift-off process using bilayer polymethyl-methacrylate as the resist stack. The governing parameters in EBL, including exposure dose, soft-bake temperature, development time, developer solution, substrate type, and proximity effect are experimentally studied through more than 200 EBL runs, and optimal process conditions are determined by field emission scanning electron microscope imaging of the fabricated nanostructures reaching as small as 11 nm feature size.