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To register for this briefing event, please contact Max at m.swinscow-hall@imperial.ac.uk

Sensors and detection technologies are critical tools in national security, deployed in a range of situations for detecting weapons such as guns and knives, as well chemical, biological, radiological, nuclear and explosive threats.

This latest breakfast briefing event from the Institute of Security Science and Technology will include talks from Imperial academics working on cutting edge R&D in this space, and from Smiths Detection, a global leader in commercial sensors and detection technologies.

Time, date, location:

  •  Friday 31 January 2020
  • Breakfast and networking from 08:30am
  • Talks and Q&A 09:00am – 10:00am
  •  Location on South Kensington campus, directions on registration

Speakers and talks:

  • Dr Elizabeth Humphreys, Smiths Detection
    Tracing the source: The detection and identification of chemical threats in the field
     The talk will focus on the specific challenges around detecting trace chemical threats (explosives, narcotics etc.) and the standard approach to detection and identification using Ion Mobility Spectrometry, for which Hemel Hempstead is a centre of excellence within Smiths Detection.

  • Professor Norbert Klein
    Graphene field effect transistors offer great opportunities for wafer scalable sensor applications, ranging from security threat detection, to detection of environmental hazards in polluted air and early stage disease detection. We have developed processes for wafer – scalable graphene device manufacturing, in combination with other functional thin film materials like piezoelectric aluminium nitride, with the aim to achieve high selectivity and ultimate sensitivity, helping to reduce false detection rates.

  • Dr Alex Ivanov.
    We are developing novel strategies for an aptamer/antibody-based protein fingerprinting platform with high sensitivity (sub-pM) for the realtime detection of biomarkers. The application spaces can be in bio and chemical agent detection and medical diagnosis.