Figure 1. Schematic diagram of the biological and
artificial multisensory neurons. A biological multisensory neuron that
is stimulated by pressure and temperature. Pressure applied onto
mechanoreceptors change the potentials of receptors that are embedded in
the skin. Temperature applied onto thermal receptor change the receptor
potential. The cell body of the sensory neuron integrates the potentials
and initiates spikes with coded pressure information and temperature
information. Inside the orange dashed box, it is the schematic images of
the artificial multisensory neuron consist of a piezoresistive sensor
and VO2-based oscillation neuron.
Here, we report an artificial multisensory neuron consisting of a
piezoresistive sensor and a VO2 based volatile memristor
connected in series. Such artificial sensory neurons can be used to
sense different pressure inputs and convert them into spike trains as a
result of the voltage dividing effect between the piezoresistive sensor
and VO2 memristor. Besides,
the spiking neuron is also capable of
sensing temperature, by taking advantage of the intrinsic thermal
sensitivity of metal-insulator transition in VO2. The
spiking neuron is utilized to recognize Braille characters using
multiple piezoresistive sensors. Notably, the traditionally separate
haptic and temperature signals can now be fused physically in the
VO2 based sensory neuron when synchronizing the two
sensory cues, which is able to recognize multimodal haptic/temperature
patterns. Such multisensory neurons could provide a promising approach
towards e-skin, neuro-robotics and human-machine interaction
technologies.
2. Results and Discussion
2.1. Oscillation neuron based on VO2 volatile memristor
The perception and cognition ability of human brain assisted with
associative biomechanical and temperature sensations are critical for
acquiring somatosensory information. The brain encloses numerous neurons
to receive the interactive signals in different modalities (e.g.,
mechanical, temperature signals) and implements cross-modal neuromorphic
computation in the multisensory association area.[33,
34] Figure 1 presents the biological multisensory
integration nervous system, and the corresponding artificial
multisensory system that is constructed (as shown in the orange dashed
box), which consists of a piezoresistive sensor and
VO2-based oscillation neuron.
As one of the key components, the oscillation neuron was first built,
and its characteristics were thoroughly analyzed. As schematically
illustrated in Figure 2 a, the oscillation neuron consists of
two Au/Ti electrodes sandwiching a VO2 film in a lateral
device structure. The structure of the device is characterized by the
scanning electron microscopy (SEM) image in Figure 2b, showing that the
channel length of the device is approximately 400 nm. Figure 2c and 2d
show transmission electron microscopy (TEM) images of the
VO2 device, with spatial mapping of Al, Au, Ti, V and O
elements using energy-dispersive X-ray spectroscopy (EDS). An EDS line
scan of the cell is shown in Figure S1, Supporting Information. Figure
2e exhibits a high-resolution TEM image of the VO2layer. The clear lattice fringes and the corresponding Fast Fourier
Transformation (FFT) result (Figure 2f) show that the
VO2 has high-quality crystalline structure with a
tetragonal phase.
Electrical measurements of the Au/Ti/VO2/Ti/Au
memristors show that the devices have threshold switching (TS)
characteristics without going through any electroforming process. As
shown in Figure 2g, reliable TS characteristics can be obtained under
voltage sweeping mode with 100 cycles. Specifically, when the applied
voltage exceeds a threshold voltage (V th) of
~1.4 V, the VO2 device switches from
high resistance state (HRS) to low resistance state (LRS), and
automatically returns to HRS once the applied voltage drops below a
holding voltage (V hold) of ~1.0 V
(Figure 2g, Figure S3 further shows the stable TS characteristics
without compliance current). Transient electrical measurements show that
the switching speed of the VO2 device is <120
ns from off state to on state, and <50 ns from on state to off
state (Figure S2, Supporting
Information). We also examined the stability and uniformity of the
VO2 memristor, including the endurance, the
cycle-to-cycle and device-to-device variations of the device, which
demonstrate that the VO2 memristors have
endurance of
>106 cycles as well as acceptable
cycle-to-cycle and device-to-device variations (Figure S4-S6, Supporting
Information), making them
qualified for functioning as oscillatory neurons.
The TS characteristics in VO2 volatile memristors can be
well interpreted by the Mott transition coupled with a structural phase
transition.[35-37] Figure 2h schematically depicts
the dynamic evolution of the device state during the threshold switching
process through COMSOL simulation. The orange line shows the
experimental current-voltage (I-V ) characteristics, while the
bule line depicts the simulation curve. From state (1) to state (2),
heat is generated in VO2 while the applied voltage
increases. When the applied voltage exceeds V th,
joule heating generated by the voltage induces formation of a filament
through the VO2 gap, leading to a transition from HRS to
LRS, and the filament expands from the channel to both sides as the
process progresses (state (2) to state (4)). When the applied voltage
decreases, the heat is gradually dissipated and the size of the filament
gradually decreases, and the device undergoes a transition from state
(5) to state (8), leading to switching from LRS to HRS.