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Martin McMullan

Researcher at Ulster University

Publications -  5
Citations -  842

Martin McMullan is an academic researcher from Ulster University. The author has contributed to research in topics: Biosensor & Detection limit. The author has an hindex of 4, co-authored 5 publications receiving 779 citations. Previous affiliations of Martin McMullan include Peking University.

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Catalyst-Free Efficient Growth, Orientation and Biosensing Properties of Multilayer Graphene Nanoflake Films with Sharp Edge Planes**

TL;DR: In this article, a microwave plasma enhanced chemical vapor deposition strategy was used for the efficient synthesis of multilayer graphene nanoflake films (MGNFs) on Si substrates.
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Streptavidin Modified Carbon Nanotube Based Graphite Electrode for Label-Free Sequence Specific DNA Detection

TL;DR: The DNA biosensor was demonstrated to have excellent selectivity, being able to differentiate complementary sequences from a noncomplementary ones and in addition select the target sequence of DNA from a mixture of other DNA without loss in current sensitivity.
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Aptamer conjugated Mo6S9−xIx nanowires for direct and highly sensitive electrochemical sensing of thrombin

TL;DR: Given the direct label free nature of the approach and the simplicity of the electronic detection, the aptamer conjugated MoSI NWs biosensor appears well suited for implementation in portable point of care microdevices directed at the rapid and sensitive detection of proteins and pathogens.
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Bioassembled nanocircuits of Mo6S9-xIx nanowires for electrochemical immunodetection of estrone Hapten.

TL;DR: A novel and highly sensitive electrochemical detection of estrone based on an immunosensor platform, composed of bioassembled nanocircuits of Mo 6S 9- x I x nanowires (MoSI NWs) covalently connected to anti-estrone antibodies.
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Amplified optical transduction of proteins derived fromMo6S9−xIx nanowires

TL;DR: In this article, the authors demonstrate that Mo6S9−xIx nanowires (MoSI NWs) enable the detection of proteins with cytochrome c as a model protein using UV-vis spectrometry.