Figure 2. VO2 volatile memristor analysis. a)
Schematic diagram of the memristive device, which consists of two Au/Ti
electrodes sandwiching a dielectric film (VO2) in a
lateral device structure. b) Scanning electron microscopy (SEM) image of
the VO2 device. c) Cross-sectional transmission electron
microscopy (TEM) image and the elemental mapping of the materials in the
system for Al, Au, Ti, V and O, respectively. d) Cross-sectional TEM
image of the VO2 device. e) High-resolution TEM image of
the VO2 layer. f) The diffraction pattern extracted by
Fourier transform of Figure 2e. g) Current-voltage (I-V )
characteristics of the device repeated for 100 cycles. h) SimulatedI–V curves from the thermodynamic simulation. The right area of
figure show heat distribution at each moment.
Based on the threshold switching characteristics in VO2memristors, oscillatory neuronal behavior can be implemented with a
simple circuit, whose configuration is depicted in Figure 3 a.
The VO2 volatile memristor is connected in series with a
load resistor (R L), and the intrinsic capacitance
of the VO2 memristor provides the dynamics for
integration. Figure 3d shows the oscillation characteristics of the
spiking neuron. When a suitable voltage (V in) is
applied and a matched serial resistor
(R L) is connected, the voltage dividing effect
between the R L and VO2 memristor
results in a voltage drop over VO2 memristor that
exceeds its V th. Therefore, the
VO2 device will switch from off to on state. Once the
device is in on state, the voltage drops acrossR L and the VO2 device will be
re-distributed, and the voltage gets lower thanV hold and hence the device returns to off state.
To achieve such oscillation effect, the following requirements should be
satisfied:
(1)
(2)
When Equations (1) and (2) are satisfied, the above spike event will be
produced and repeated (Figure 3d). Figure 3d and 3e show the oscillating
behavior of the spiking neuron, when the R L or
input voltage is varied, respectively. As expected, the oscillation
frequency decreases (0.9, 0.7, 0.55, 0.35 MHz) asR L increases (3.0, 3.6, 4.2, 4.8 kΩ) (Figure 3d),
whereas the rate increases (0.45, 0.65, 0.8, 0.9 MHz) as the input
voltage increases (4.2, 4.8, 5.4, 6.0 V) (Figure 3e). The dependence of
the oscillation frequency on the load resistor
(R L) is systematically tested under different
input voltages (4, 5, 6 V), and the results are summarized in Figure 3b,
further demonstrating that the oscillation frequency decreases asR L increases in each V incase. Similarly, Figure 3c systematically analyzes the dependence of the
oscillation frequency on V in, when variedR L (3.0, 3.5, 4.0, 4.5 kΩ) is adopted, implying
the same increasing trend of oscillation frequency with increase ofV in. Therefore, the oscillation frequency of the
spiking neuron can be effectively modulated by the threshold voltage of
the VO2 memristor and circuit parameters
(R L and V in), which paves
the way for the construction of an artificial sensory system.