Experimental Section/Methods

Fabrication of VO2 volatile memristor: The 20 nm VO2 films were epitaxially grown on c-Al2O3 substrates by pulsed-laser deposition (PLD) technique using a 308-nm XeCl excimer laser operated at an energy density of about 1 J/cm2 and a repetition rate of 3 Hz. The VO2 films were deposited at 530 °C in a flowing oxygen atmosphere at the oxygen pressure of 2.0 Pa. Then, the films were cooled down to the room temperature at the speed of 20 °C/min. The deposition rate of VO2 thin films was calibrated by X-ray Reflection (XRR). All VO2 devices studied in this work were fabricated on Al2O3 substrates. First, ~10 nm single crystal VO2 film serving as the switching layer was deposited by pulsed laser deposition (PLD). Afterwards, ~5 nm thick Ti was deposited as the electrodes and capped by ~40 nm thick Au protection layer by e-beam evaporation, where the patterning of the electrodes was done by electron beam lithography and lift-off processes.
Microstructural and compositional characterization: The TEM samples in this work were prepared by the focused ion beam (FIB) technique using a dual-beam FIB system (FEI Helios Nanolab workstation). During FIB patterning, the sample was first coated by SiO2 and Pt layer deposited using the electron beam to avoid surface damages, followed by higher-rate Pt coating using normal ion beam process that served as majority of the protective layer during FIB cutting. TEM and STEM images as well as EDS measurements were performed on FEI Tecnai F20 and the HRTEM and SAED results were analyzed by the Digital Micrograph software (Gatan Inc.). The SEM characterization was conducted on a field emission SEM (Merlin Compact).
Electrical measurements: All the electrical measurements were performed using an Agilent B1500A semiconductor parameter analyzer and the RIGOL MSO8104 digital storage oscilloscope. Voltage pulses were applied by the Agilent B1500A. We used an Agilent B1500A semiconductor parameter analyzer to perform electrical measurements of a single VO2 device in Fig. 2g-h, 4b, 6b and Figure S2-6, S9, S11, S12. In Figs. 3-6 and Figure S14, Agilent B1500A is applied to create the pulse signal, and one channel of the oscilloscope is used to measure the output of Agilent B1500A, while the other channel measures the voltage of the output node in the neuron circuit.
Simulations: A COMSOL Multiphysics package finite element simulation was used to analyze the electro-induced phase change and thermal distribution of the film. The 3D structure and material properties of the simulation model, including test electrodes, substrates, and VO2 composite films, which were the same as those of the experiment. In this simulation, the fitted electrical characteristics of the device is set according to the real test data (see Figure 2f).
           The Multi-layer-perceptron with an architecture of 2×20×11 and 3×20×11 were simulated in MATLAB, that is, 2 or 3 input neurons for dataset inputs, 20 hidden neurons and 11 output neurons for possible classes. Each output neuron represents one of the combinations of pressure and temperature. The neural network was trained online with Backpropagation (BP) algorithm.
Piezoresistive sensor:  The piezoresistive sensors used in this study is RP-C18.3-LT. The detailed technical and physical properties are as follows:
Thickness 0.4 mm
Shape Flexible
Actuation force 20 g, Res.<=200 kΩ
Operation range 20 g to 6000 g
Resolution continuous
Non-actuated resistance >10 MΩ
Response time < 10 ms
Life time >1 million
Repeatability same part +/- 3%, Average R@1000 g
Repeatability part to part +/- 10%, Average R@1000 g
Hysteresis +10%, @1000 g
EDS Not ESD sensitive

Results

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.