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Introducing TEAM-A

Research Challenges

Research challenges

  • To be a recognised world leading centre for both the science and engineering behind and the exploitation of advanced new materials;
  • To work with a diverse variety of companies;
  • To bring together leading advanced materials and manufacturing research at Exeter and QinetiQ to address real technology and innovation challenges.
  • Research excellence;
  • Routes to manufacturing;
  • Developing new generational entrepreneurial researchers;
  • Partnering to bring exploitation science and technology.
Research challengeAcademic staff
1. New materials and structures that control the propagation of microwave and radio frequency radiation.
2. To exploit the use of optical, infra-red and terahertz radiation for identification, signalling and imaging.
3. New materials and structures that control the propagation of acoustic radiation.
4. To develop predictive models of the propagation of electromagnetic and acoustic radiation, supporting the other research challenges.
5. To explore novel approaches to the manufacturing of advanced materials.

Author: Dr Joshua K Hamilton

The problem

In the modern world, the demand for vast amounts of data is increasing at an explosive rate. The wireless backhaul is a bottleneck and needs to be overcome so that 6G systems can be created. Radio frequency orbital angular momentum beams (OAM) are thought to be one solution.

OAM beams have the capability to improve the spectral efficiency of communication by multiplexing parallel data streams along multiple OAM modes at the same frequency. The current crucial drawback of OAM carrying beam being used for applications is the central vortex. For increasing OAM modes, the divergence angle of the beam increases. As a result, the receive aperture size required for optimum reception scales with the OAM mode - which is undesirable and results in the use of OAM beam for large distances virtually impossible.

Our solution

Notable work by F. Tamburini et al [1] focused on using a split parabola antenna to generate a single mode bean while collimating the divergent beam. We are developing a new approach to control the divergence of the OAM beam and generate broadband OAM beams. We are able to generate multiple OAM modes using a single uniform circular antenna array (UCA) [2]. Combining the UCA with a tailored parabolic mirror, we can successfully collimate the generated OAM beam for the range of operating frequencies of the antennas, without affecting the OAM structure of the beam. In addition to this work, we are also looking into methods of further enhancing the generated beam so that it could be useful for point-to-point communications.

Fig1 JH_Case Study_18.09.19

Figure 1. Schematic diagrams showing the difference between a standard divergent OAM beam and a collimated beam.


[1]        F. Tamburini, B. Thidé, E. Mari, A. Sponselli, A. Bianchini, and F. Romanato, “Encoding many channels on the same frequency through radio vorticity: First experimental test,” New J. Phys., vol. 14, 2012

[2]        T. D. Drysdale, B. Allen, C. Stevens, S. J. Berry, F. C. Smith, and J. Coon, “How orbital angular momentum modes are boosting the performance of radio links,” IET Microwaves, Antennas Propag., vol. 12, no. 10, pp. 1625–1632, 2018.

Author: Dr Andrew Corbett

The problem

Computer simulation nowadays has the muscle to address problems previously thought out of reach. Especially in real-time imaging. Our broad problem is to simulate how light is transferred in deep and shallow waters; to produce an image of what one might see from above.

A Corbett_Case Study Image 1

Our solution

Modelling a plane-parallel ocean is, at first glance, slow. This is because one must solve a two-point boundary value problem: there is a differential equation, as a function of depth, with a boundary at the surface and at the bottom. The core of our approach uses a technique to cut this problem in half, solving two initial (one-point) value problems and stitching the solution together at the join via a technique known as invariant embedding. This principal opens up the door to various new approaches, such as:

  • Homogeneous patching of analytic solutions
  • Multiple depth analysis via integration of the initial value problems

Our imaging model further relies on the following ingredients:

  • Surface simulation of a water body
  • Classification on the inherent optical properties of the water body
  • Solutions for the boundary conditions of the ocean floor

The 1D output tells us the strength of radiation at all depths of the ocean (see below). Our next prerogative is build a bird-eye view.

A Corbett_Case Study Image 2


The product we are developing provides foresight. Our ambition is to provide a great deal of data about what may be seen in the water without ever having to dip your toes in. Can we detect objects a short distance below the sea’s surface (e.g. ‘growlers’ – shipping containers that are a threat to shipping) or on the seabed (e.g. oil pipes and lost cargo)? How accurately can we monitor the health of a coral reef? What colour/texture should life vests exhibit to most easily be spotted from above?  These are amongst the scenarios we wish to simulate accurately for metamaterial design.