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Spectrally-resolved scanning photocurrent microscopy: Revealing new physics in carbon nanotubes
Here we describe a combination of nanoscale spectroscopy and transport measurements to explore the full relationship between CNT structure, electrical properties, and dielectric environment. We use spectrally-resolved scanning photocurrent spectroscopy to determine the chiral index of individual-contacted suspended CNTs. Dielectric environment is controlled by using various dielectric liquids. In semiconducting CNTs we observe band gap renormalization of approximately 30%. In metallic CNTs we observe a transport gap that is consistent with the theoretical predictions of a Mott gap. The gap is independent of chiral angle, inversely proportional to CNT diameter and scales inversely with the dielectric constant of the environment. Our results highlight the importance of spectrally-resolved scanning probe techniques in nanometrology, and highlight the important effect of dielectric environment on nanoscale physical properties.
A wearable graphene sensor patch for individual neurons
Graphene field-effect transistors (GFETs) have unique properties that make them ideal candidates for recording the activity of electrogenic cells. Graphene is mechancially strong yet flexible enough to conform to irregular shapes. Transistors made from graphene are capable of locally amplifying small voltage signals. Lastly, graphene is optically transparent and biocompatible. Here we present the use of ultra-flexible GFETs for recording action potentials from individual neurons. Measurements have been performed in two configurations. (1) A “standard” configuration with GFETs on a rigid substrate and neurons cultured on top of the GFETs. (2) A novel wearable graphene sensor configuration, in which the GFET is released from the substrate and placed over a neuron. The wearable graphene configuration makes use of graphene’s intrinsic strength and flexibility. Cells remain active while in contact with the wearable sensor and high signal-to-noise ratios are demonstrated. These proof-of-concept measurements demonstrate new possibilities for ultra-flexible brain-machine interfaces.