During neural
activity, action potentials travel down axons, generating effective charge
current pulses, which are central in neuron-to-neuron communication. Consequently, said current pulses generate
associated magnetic fields with amplitudes on the
order of picotesla (pT) and femtotesla (fT) and durations of 10’s of ms.
Magnetoencephalography (MEG) is a technique used to measure the cortical magnetic
fields associated with neural activity. MEG limitations include the inability
to detect signals from deeper regions of the brain, the need to house the
equipment in special magnetically shielded rooms to cancel out environmental
noise, and the use of superconducting magnets, requiring cryogenic temperatures,
bringing opportunities for new magnetic sensors to overcome these limitations
and to further advance neuroscience. An extraordinary magnetoresistance (EMR)
tunable graphene magnetometer could potentially achieve this goal. Its
advantages are linear response at room temperature (RT), sensitivity
enhancement owing to combination of geometric and Hall effects, microscale size
to place the sensor closer to the source or macroscale size for large source
area, and noise and sensitivity tailoring. The magnetic sensitivity of EMR
sensors is, among others, strongly dependent on the charge mobility of the
sensing graphene layer. Mechanisms affecting the carrier mobility in graphene
monolayers include interactions between the substrate and graphene, such as
electron-phonon scattering, charge impurities, and surface roughness. The
present work reviews and proposes a material set for increasing graphene mobility,
thus providing a pathway towards pT and fT detection. The successful
fabrication of large-size magnetic sensors employing CVD graphene is described,
as well as the fabrication of trilayer magnetic sensors employing mechanical
exfoliation of h-BN and graphene. The magneto-transport response of CVD
graphene Hall bar and EMR magnetic sensors is compared to that obtained in
equivalent trilayer devices. The sensor response characteristics are reported,
and a determination is provided for key performance parameters such as current
and voltage sensitivity and magnetic resolution. These parameters crucially
depend on the material's intrinsic properties. The Hall cross magnetic sensor
here reported has a magnetic sensitivity of ~ 600 nanotesla (nT). We find that
the attained sensitivity of the devices here reported is limited by
contaminants on the graphene surface, which negatively impact carrier mobility
and carrier density, and by high contact resistance of ~2.7 kΩ
µm at the metallic contacts. Reducing the contact
resistance to < 150 Ω µm and eliminating surface contamination, as
discussed in this work, paves the way towards pT and ultimately fT sensitivity
using these novel magnetic sensors. Finite
element modeling (FEM) is used to simulate the sensor response, which agrees with
experimental data with an error of less than 3%. This enables the prediction and
optimization of the magnetic sensor performance as a function of material
parameters and fabrication changes. Predictive studies indicate that an EMR
magnetic sensor could attain a sensitivity of 1.9 nT/√Hz employing graphene with
carrier mobilities of 180,000 cm<sup>2</sup>/Vs, carrier densities of 1.3×10<sup>11</sup> cm<sup>-2</sup> and a
device contact resistance of 150 Ω
µm. This
sensitivity increments to 443 pT/√Hz if the mobility is 245,000 cm<sup>2</sup>/Vs,
carrier density is 1.6×10<sup>10</sup> cm<sup>-2</sup>, and a
lower contact resistance of 30 Ω
µm. Such
devices could readily be deployed in wearable devices to detect biomagnetic signals originating from the
human heart and skeletal muscles and for developing advanced human-machine
interfaces.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12264512 |
| Date | 07 May 2020 |
| Creators | Angel Rafael Monroy Pelaez (8803235) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Towards_Picotesla_Sensitivity_Magnetic_Sensor_for_Transformational_Brain_Research/12264512 |
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