New Project: Big-Data for nano-electronics

Patrick has been awarded a 4-year research fellowship from UKRI for a project on “big-data for nano-electronics”. This Future Leaders Fellowship will enable Patrick to focus on building a research group to develop a new methodology for accelerating the study of functional nanotechnology.

Project Summary

The modern world runs on nanotechnology; we are connected by a fibre-network using nanostructured lasers, and use computers and phones made of nanometre scale transistors. The next generation of nanotechnology promises to incorporate multiple functionalities into single nanomaterial elements; this is “functional nanotechnology”. Here, the size of the material itself provides functionality – for instance for sensing, computing, or interacting with light.  The most powerful and scalable approaches to making these structures use bottom-up or “self-assembled” methods; however, as this production technique emerges from the laboratory and into industry, issues such as yield, heterogeneity, and functional parameter spread have arisen.

Functional performance in these nanomaterials is determined by geometry. As such, variations in size or composition affect performance in complex ways. In this project, I will combine high-speed and high-throughput techniques to measure the shape, composition and performance of hundreds of thousands of functional nanoparticles from each production run. By combining this big data with statistical analytics, I will create a new methodology to understand and then optimize cutting-edge functional nanomaterials, working with academic partners in Cambridge, University College London, Strathclyde, Lund (Sweden) and the Australian National University, and industrial partners including AIXTRON and Nanoco.

The ultimate goal of this project is to enable demonstration and scale-up of transformative devices based on novel nanotechnology, for sensing, computing, telecommunication and quantum technology.

Project Summary: Large-scale approaches for nanolaser optimization

The emission of light at the nanoscale is of great importance for information processing, medicine and fabrication for optical circuits. Optical circuits would improve processing speeds and decrease the energy consumption necessary to operate data centres. This is due to the manipulation of light which can carry more information at faster speeds more efficiently than electrical signals over copper.

An important element of optical circuits is the light source; in our case, we focus on semiconductor nanowires. These tiny crystals can emit signals in the form of light and due to their compact size (one tenth the thickness of a human hair) and electronic properties; they can be easily integrated with current silicon technology. However, nanowires cannot be fabricated individually; they require a process which “grows” very big quantities. So, when we want to integrate them with current technology, it is necessary to select the ones with the best light emission quality.

We have developed a technique that allows us to test thousands (from 1000 to 10,000) of these wires rapidly and gather a large amount of information from each one. This gives us the advantage of finding the top performing wires which can be isolated and retrieved for their implementation in optical circuits. Additionally, we can perform a large statistical study to find trends in nanowires performance as a function of particular characteristics. For example, one could find that longer wires tend to emit light more efficiently, or a change in its chemical composition makes them better candidates for lasers.

These findings are a good stepping stone towards the improvement of nanowire design and fabrication.