Speaker
Description
The reliable fabrication of complex three-dimensional nanostructures via focused electron beam induced deposition (FEBID) requires precise control over a wide range of process parameters [1]. Conventional workflows rely heavily on manual operation, limiting reproducibility, throughput, and scalability. Automation is therefore the key to faster prototyping and application-oriented nanofabrication.
In this work, we present a Python-based automation approach that integrates the layer-by-layer 3D nanoprinting software f3ast into the patterning control of a scanning electron microscope (SEM) [2]. The system interfaces with key instrument components, allowing for stage motion, gas injection system (GIS) operations, and electron optics adjustments, enabling fully automated deposition sequences. A central element is a robust autofocus routine tailored for FEBID. To this end, we investigated gradient- and variance-based focus metrics, combined with algorithmic region-of-interest selection and noise reduction, and evaluated the reproducibility of the resulting focus under varying deposition conditions and sample geometries [3]. The routine is embedded into the deposition workflow and executed at predefined positions prior to each writing step to ensure consistent beam focus and placement. Its performance is evaluated using standard calibration patterns for f3ast, enabling quantitative assessment of focus quality based on these well-understood structures.
In addition, we implement a feedback loop that evaluates deposited calibration structures and estimates f3ast calibration parameters, enabling adaptive optimization of the fabrication process. Together, the integration of automated focusing, deposition, and feedback-driven parameter adjustment enables reproducible FEBID processes, while reducing operator workload and supporting efficient, high-throughput nanoscale prototyping with minimal user intervention.
[1] V. Reisecker, R. Winkler, H. Plank, Adv. Funct. Mater. (2024). https://doi.org/10.1002/adfm.202407567
[2] L. Skoric et al., Nano Lett. (2019). https://doi.org/10.1021/acs.nanolett.9b03565
[3] C. Batten, M.S. thesis, Cornell University (2000).