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Enabling the Perception of Invisible Near Infrared Light via Engineered Nanocrystals S&T9

  • School: School of Science and Technology
  • Study mode(s): Full-time / Part-time
  • Starting: 2022
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Fully-funded


NTU's Fully-funded PhD Studentship Scheme 2022

Project ID: S&T9

Human eyes only see visible light, which is a tiny portion of the entire electromagnetic spectrum - about 0.0035%. Among all invisible lights around us, the near-infrared (NIR) range is of particular interest because of its broad application, for example, for medical diagnosis, food quality control, autonomous vehicles, and night-vision. For instance, if our eyes could see NIR waves directly, we would see in the dark, and there would be no need for streetlights. Imagine no light pollution and a massive reduction in greenhouse gases associated with a world where the lighting was not required to see at night. Unfortunately, current NIR-imaging cameras cannot realise these imaginings due to their limitations. Today's NIR cameras require the conversion of NIR light to electrons and the projection of the resultant image on display. This display blocks the preception of visible light, therefore disrupting normal vision. Moreover, the components for light/electron conversion are bulky.

This PhD project is a part of a larger programme to develop new technology for seeing both visible and near-infrared lights, simultaneously via engineered glass surfaces such as goggles, house windows, and car windscreens. The over-arching aim of this PhD project is to engineer nanocrystals, 100-1000 times thinner than a human hair, and embed them within a thin and transparent layer that will be used to capture the NIR light and re-emit it in the visible range. During this PhD, the candidate will develop

  • The best effective way to couple engineered nano-particles with light;
  • The best configuration of engineered nano-particles to be integrated into a prototype device.


Modelling: Currently, the standard approach for optimising nonlinear nano-particles is to fix a large number of parameters (various materials' properties, geometry, etc.) and to optimise one or two parameters via direct simulations. However, in this project, the candidate will employ machine learning and artificial intelligence to engineer and optimise all parameters simultaneously.

Experimental verifications: All optimised nano-particles will be fabricated and verified experimentally. The fabrication facilities are available at newly developed cleanrooms at NTU Medical Technologies Innovation Facility (MTIF).



Supervisory Team

Mohsen Rahmani, Professor in Optics and Photonics in Department of Engineering at the School of Science & Technology.

Prof. Rahmani obtained his PhD from the National University of Singapore in 2013, followed by postdoc fellowship at Imperial College London, and the Australian Research Council Early Career Fellowship at the Australian National University (ANU). In 2020, he moved to the Nottingham Trent University as a Royal Society Wolfson Fellow, and has recently been awarded the UK Research and Innovation Fellowship. His research interests are NIR imaging, flat optics and ultra-sensitive biochemical sensing. He is the recipient of several prestigious awards and prizes, including the Eureka Prize for Outstanding Early Career Academics (Australian Oscar of Science), Early Career Medal from the International Union of Pure and Applied Physics, and the Australian Optical Society Geoff Opat Award. He is an editorial board member of Opto-Electronic Advances. Currently, he serves as the chair of the IEEE Nanotechnology Chapter in the UK and Ireland Section.

Lei Xu, Senior Lecturer in Electrical Engineering at Department of Engineering at the School of Science & Technology.

Dr Xu obtained his PhD (2014) in Optics from Nankai University, China. Since then, he has been performing research and engineering activities in different universities: Nankai University, The Australian National University and the University of New South Wales. His research interests are nanophotonics, optoelectronics meta-devices, low carbon technologies (i.e. solar energy harvesting, as well as innovative radiative cooling for energy saving), and bio-photonics (i.e. tissue engineering via light, and wearable optical sensors).

School strategic research priority

This project is in line with School's investments in low carbon technologies (in line with UK's Grand Challenge (GC) for clean growth). The outcomes of this project will lead to reduced greenhouse gases associated with a world where lighting will no longer be required to see at night. Meanwhile, this project is in line with autonomous technologies (in-line with another GC: future of mobility), which is also one of the Department of Engineering priorities.

Entry qualifications

For the eligibility criteria, visit our studentship application page.

How to apply

For guidance and to make an application, please visit our studentship application page. The application deadline is Friday 14 January 2022.

Fees and funding

This is part of NTU's 2022 fully-funded PhD Studentship Scheme.

Guidance and support

Download our full applicant guidance notes for more information.

Still need help?

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