Nanostructured materials have dimensions approaching atomic length scales. When these materials are first developed in the lab there is a drive to demonstrate their exceptional (opto)electronic properties by incorporating them into functional devices such as transistors, lasers, solar cells, and photodetectors. This early proof-of-concept stage requires precise and time-consuming manual control of characterization equipment and skilled operators to handle and process the nanomaterials. This bottleneck prevents many nanotechnology-based electronics concepts from becoming commercially available, despite their many benefits, as the processes we use to make them are simply too manually intensive and time-consuming. During my PhD I have been developing techniques to remove this bottleneck and translate emerging nanomaterials into new device applications.
One of the first things I had to do in my PhD was to fabricate some transistors based on monolayer MoS2 flakes. So I first had to take hundreds of microscopic images of a sample with randomly grown MoS2, and manually find all monolayer flakes in order to draw contacts around them using a CAD software. This took me a couple of weeks and it made me question why I was even doing a PhD in the first place. It turns out this is a very common problem and many students spend hours looking down the microscope to find material features required to make devices.
So I started thinking, is there a way these simple, repetitive tasks could be automated? Is there a way to save many researchers hundreds of hours of time? Is it possible to remove the manual steps in nanofabrication in order to speed up the manufacture of nano-electronics of benefit to society?
We can do this by using alignment markers for accurate positioning on a sample, but current markers are often damaged during nanofabrication due to physical processes at such a small scale. So we developed a new positioning system optimized for nanoscale processing, named LithoTag. LithoTags are markers that are computer-readable, contain position information, and enable correlation between different techniques. We can use LithoTags to translate the position data of materials we are looking for on a sample. For example, we can find nanowires that have been deposited on a substrate, use LithoTags to remember their location, and automatically deposit metallic contacts on them without picking them up and moving them to a different location.
The main benefit is that hundreds of working nano-devices can be fabricated in fraction of the time, providing statistically relevant data required to study nanomaterials and nanomaterial-based devices. It also provides a pathway to automating nanotechnology-based electronics on a commercial scale and fast-forward nanotechnology research by saving hundreds of hours of time, resources and carbon footprint associated with scientific research.
NanoDTC Associate, a2021