Tunable Neuromorphic Switching Dynamics via Porosity Control in Mesoporous Silica Diffusive Memristors

In response to the growing need for efficient processing of temporal information, neuromorphic computing systems are placing increased emphasis on the switching dynamics of memristors. While the switching dynamics can be regulated by the properties of input signals, the ability of controlling it via electrolyte properties of a memristor is essential to further enrich the switching states and improve data processing capability. This study presents the synthesis of mesoporous silica (mSiO2) films using a sol–gel process, which enables the creation of films with controllable porosities. These films can serve as electrolyte layers in the diffusive memristors and lead to tunable neuromorphic switching dynamics. The mSiO2 memristors demonstrate short-term plasticity, which is essential for temporal signal processing. As porosity increases, discernible changes in operating currents, facilitation ratios, and relaxation times are observed. The underlying mechanism of such systematic control was investigated and attributed to the modulation of hydrogen-bonded networks within the porous structure of the silica layer, which significantly influences both anodic oxidation and ion migration processes during switching events. The result of this work presents mesoporous silica as a unique platform for precise control of neuromorphic switching dynamics in diffusive memristors.

characterized as low-order structures because their intricacies are not likely to be captured.The sample with 0.005 F127:TEOS ratio was found to be a highly-ordered mesoporous silica film, the GISAXS pattern matches well with the orthorhombic Fmmm pore structure with most domains oriented with the (0 1 0) plane vertical to the substrate. 1The lattice parameters are a=10.5 nm, b=8.5 nm and c=15 nm.The samples with 0.007 and 0.009 display a few Bragg peaks and two rings.It indicates that the mesostructures are less ordered and mesostructure domains orient in different directions.In both 0.007 and 0.009 samples, the Bragg peaks are horizontal to the Yoneda peak and vertical to the Yoneda peak, all matching well with the Fmmm mesostructure, with the (0 1 0) plane normal to the substrate.Moreover, the SEM images (Figure 2a-2e) show that samples with 0.005, 0.007 and 0.009 ratios have similar pore arrangements from the top view.It indicates that samples with 0.007 and 0.009 ratios have the same mesostructured as sample 0.005.However, because of less ordering, there are not enough Bragg peaks observed to simulate the lattice parameter values.
To investigate the spatial arrangement of the mesostructured phase, vertical line profiles were exported from the processed data through DPDAK software.As shown in Figure S1f, the qy axis illustrates the intensity calculated from the Yoneda position.][4]    The retentions of devices with different porosity were exhibited in Figure S4.The resistance states were read at 0.1 V, and the reading current in LRS and HRS exhibited excellent stability after 10 3 s, confirming the non-volatility of the memristors.This implies formation of strong filaments in all memristors.Under this condition, the impact of porosity on the retention is not significant.Figure S5 depicts the endurance of the non-volatile switching behaviors of our memristors where repeatable switching can be observed in all memristors.It is worth noting that the non-volatile endurance performance of our memristors were not optimized.Figure S7 plots the I-V characteristic of all memristor devices in the log-log scale.Taking the device with 45.3% porosity as an example, initially from 0 V to 0.15 V at HRS, the device shows a linear dependence of current with applied voltage.An Ohmic conduction mechanism is obtained, which arises from thermally generated charge carriers.At higher applied voltages (0.2 ≤ V ≤ 0.9 V), the slope changes to approximately 2( ∝  2 ), and the current exhibits the voltage square dependence, which can be attributed to the trap-controlled space charge limited current.

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Figure S2 (a) Refractive index change collected over 200-1700nm wavelength range for mesoporous silica films with different F127:TEOS ratios on the silicon substrate; (b).The thickness versus F127:TEOS ratio in mesoporous silica layers.

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Figure S6 Distribution of the programming voltages for the mSiO 2 -based memristors with different porosities.

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Figure S8 illustrates the relationship between current values and consecutive cycles in the

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Figure S8 Current changes versus consecutive cycles of the HRS of the device.The current values were read at 0.5 V.

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Figure S10 presents the gradual change of the envelope peak position with changing mSiO2

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Figure S10.XPS envelope peak position as a function of film porosity.

Table S1
provides a summary of the memristive capabilities observed in different SiO2 and porous material based memristors.

Table S1
An overview of the memristive capabilities observed in different SiO 2 and porous material based memristors.