Unlocking NANOtechnology through autoMATION
Lead Research Organisation:
University of Cambridge
Department Name: Engineering
Abstract
The process of translating new materials into practical devices of benefit to society typically requires substantial time and capital investment. By virtue of their unique geometries and material properties, devices based on nanomaterial structures have unique (opto)electronic characteristics enabling applications not possible with conventional bulk materials. When creating a device based on an individual nanostructure, that structure's exact position needs to be known. Fabricating and measuring nanoscale devices is notoriously labour-intensive, involving searching and alignment before manual routing of electrode layout, or manually performing pick-and-place to transfer these nanostructures onto existing electrode configurations. In a research setting, this need for human intervention is a significant bottleneck that slows the development of new nanomaterials-enabled technologies. Worse still, the slow throughput of this approach precludes its application in any manufacturing setting.
We have developed a three-pronged approach - together known as NanoMation - to remove the human intervention required during inspection, research and manufacturing. The first is a system of fiducial markers, "LithoTags", which are optimised for lithography processing - photo-, electron beam-, or nanoimprint lithography. These markers can be easily read by automated microscopy processes. The second is a computer-vision system that can find, sort and filter nanostructures depending on desired properties. Third is a system of computer-adjustable electrode designs where a machine-learning algorithm automatically routes the supporting electrodes to form an entire circuit. These processes will enable a rapid transition from individual prototype devices to high performance integrated systems (e.g. single-unit nanomaterial photodetectors, transistors, or LEDs respectively - to image sensors, integrated circuits, and displays).
We have developed a three-pronged approach - together known as NanoMation - to remove the human intervention required during inspection, research and manufacturing. The first is a system of fiducial markers, "LithoTags", which are optimised for lithography processing - photo-, electron beam-, or nanoimprint lithography. These markers can be easily read by automated microscopy processes. The second is a computer-vision system that can find, sort and filter nanostructures depending on desired properties. Third is a system of computer-adjustable electrode designs where a machine-learning algorithm automatically routes the supporting electrodes to form an entire circuit. These processes will enable a rapid transition from individual prototype devices to high performance integrated systems (e.g. single-unit nanomaterial photodetectors, transistors, or LEDs respectively - to image sensors, integrated circuits, and displays).
People |
ORCID iD |
| Hannah Joyce (Principal Investigator) |
Publications
Church S
(2024)
Data-Driven Discovery for Robust Optimization of Semiconductor Nanowire Lasers
in Laser & Photonics Reviews
Norman S
(2024)
Resonance-Amplified Terahertz Near-Field Spectroscopy of a Single Nanowire.
in Nano letters
Potocnik T
(2023)
Fast Twist Angle Mapping of Bilayer Graphene Using Spectroscopic Ellipsometric Contrast Microscopy.
in Nano letters
| Description | This project has delivered high-throughput methods for characterising emerging semiconductor materials, and for integrating them into functional devices. |
| Exploitation Route | Collaborators at the University of Manchester are using our software. Collaborators at the University of Oxford and University College London are using devices fabricated with our methods. Spin-out Nanomation is commercialising the technology. |
| Sectors | Electronics Manufacturing including Industrial Biotechology |
| Description | Adaptive Point-of-Use Electronics Manufacturing |
| Amount | £244,952 (GBP) |
| Funding ID | EP/Z002583/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 12/2024 |
| End | 05/2026 |
| Description | Aixtron |
| Organisation | Aixtron Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | High-throughput characterisation of the electrical properties of low-dimensional materials. |
| Collaborator Contribution | Provision of raw low-dimensional materials for processing into devices using our high-throughput methodology. |
| Impact | Continuing collaboration. |
| Start Year | 2022 |