Quantitative Principles for Precise Engineering of Sensitivity in Graphene Electrochemical Sensors

Wu, Ting; Alharbi, Abdullah; Kiani, Roozbeh; Shahrjerdi, Davood

doi:10.1002/adma.201805752

Title: Quantitative Principles for Precise Engineering of Sensitivity in Graphene Electrochemical Sensors

Journal Article · Thu Dec 13 00:00:00 EST 2018 · Advanced Materials

DOI:https://doi.org/10.1002/adma.201805752· OSTI ID:1485704

Wu, Ting ^[1]; Alharbi, Abdullah ^[1]; Kiani, Roozbeh ^[2];

^[3]

Electrical and Computer Engineering New York University Brooklyn NY 11201 USA
Center for Neural Science New York University New York NY 10003 USA, Neuroscience Institute New York University Langone Medical Center New York NY 10016 USA
Electrical and Computer Engineering New York University Brooklyn NY 11201 USA, Center for Quantum Phenomena Physics Department New York University New York NY 10003 USA

Abstract A major difficulty in implementing carbon‐based electrode arrays with high device‐packing density is to ensure homogeneous and high sensitivities across the array. Overcoming this obstacle requires quantitative microscopic models that can accurately predict electrode sensitivity from its material structure. Such models are currently lacking. Here, it is shown that the sensitivity of graphene electrodes to dopamine and serotonin neurochemicals in fast‐scan cyclic voltammetry measurements is strongly linked to point defects, whereas it is unaffected by line defects. Using the physics of point defects in graphene, a microscopic model is introduced that explains how point defects determine sensitivity. The predictions of this model match the empirical observation that sensitivity linearly increases with the density of point defects. This model is used to guide the nanoengineering of graphene structures for optimum sensitivity. This approach achieves reproducible fabrication of miniaturized sensors with extraordinarily higher sensitivity than conventional materials. These results lay the foundation for new integrated electrochemical sensor arrays based on nanoengineered graphene.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: DE‐SC0012704

OSTI ID:: 1485704

Journal Information:: Advanced Materials, Journal Name: Advanced Materials Vol. 31 Journal Issue: 6; ISSN 0935-9648

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: Germany

Language:: English

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Cited by: 27 works

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