READ ME File For 'Dataset in support of publication 'Tunable neuromorphic switching dynamics via porosity control in mesoporous silica diffusive memristors'

Dataset DOI: 10.5258/SOTON/D2975 

Date that the file was created: April, 2024

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GENERAL INFORMATION
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ReadMe Author: Tongjun Zhang, University of Southampton 

Date of data collection: ADD IN COLLECTION DATES

Information about geographic location of data collection: United Kingdom

Related projects:
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SHARING/ACCESS INFORMATION
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This dataset supports the publication:
AUTHORS:Tongjun Zhang, Li Shao, Ayoub Jaafar, Ioannis Zeimpekis, Cornelis H. de Groot, Philip N. Bartlett, Andrew L. Hector, and Ruomeng Huang
TITLE:Tunable Neuromorphic Switching Dynamics via Porosity Control in Mesoporous Silica Diffusive Memristors
JOURNAL:ACS Applied Materials & Interfaces
PAPER DOI IF KNOWN:https://doi.org/10.1021/acsami.3c19020

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DATA & FILE OVERVIEW
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This dataset contains:

The raw data of figure 2 to 9 and 11.


The figures are as follows:

Figure 2 SEM images showing the pore structure of the samples prepared with different F127:TEOS ratios: (a) 0.001 F127: 1 TEOS ratio; (b) 0.003 F127: 1 TEOS ratio; (c) 0.005 F127: 1 TEOS ratio; (d) 0.007 F127: 1 TEOS ratio; (e) 0.009 F127: 1 TEOS ratio; (f) Refractive index and calculated porosity change of mesoporous silica films prepared with different F127:TEOS ratios.

Figure 3 Resistive switching behavior of mesoporous silica memristors: (a) Schematic of the mSiO2-based memristor. (b)-(f) I-V curve showing the forming process for different porosity mesoporous silica devices. (g) Forming electric field and (h) formation current (measured @ 0.1 V) distribution for mSiO2 memristors with different porosity.

Figure 4 I-V characteristics showing the typical non-volatile resistive switching properties of the mSiO2 memristors under a CC of 1 mA. Porosities (a) 7.1%, (b) 27.1%, (c) 34.5%, (d) 41.8%, (e) 45.3%. (f) Resistance state distribution of non-volatile resistive switching behaviors.

Figure 5 Consecutive switching I-V characteristics of samples with different porosity showing the analogue switching behavior. Porosities (a) 7.1%, (b) 27.1%, (c) 34.5%, (d) 41.8%, (e) 45.3%. (f) Current changes versus consecutive cycles of the LRS of the device. The current values were read at 0.1 V.

Figure 6 (a) Schematic representation of a biological neural network and a memristor device showing the correspondence between biological and electronic synapses; Gradual PSC change with a series of voltage pulses (+1 V, 50 ms duration) and the subsequent auto-decay showing STP behavior on the device with 45.3% porosity: (b) 7.1%, (c) 27.1%, (d) 34.5%, (e) 41.8%, and (f) 45.3% porosity.

Figure 7 Gradual PSC current change showing SRDP behavior: among samples with different porosity:(a) 7.1%, (b) 27.1%, (c) 34.5%, (d) 41.8%, (e) 45.3%. (f) The facilitation ratio concerning spike frequency is determined after the second pulse.

Figure 8 The retention loss data and fitting results of memristors with different porosity after the mentioned pulse trains. Porosity (a) 7.1%, (b) 27.1%, (c) 34.5%, (d) 41.8%, (e) 45.3%. (f) Fitted relaxation time contrast among 5 different samples in a series of 6 pulse trains.

Figure 9 XPS profiles of the O 1s core level of the films with different porosity:(a) 7.1%, (b) 27.1%, (c) 34.5%, (d) 41.8%, (e) 45.3%; (f) Composition ratio of O–Si and O-H bonding in O1s XPS spectra.

Figure 11 In-pulse measurement detecting current response under 1 V, 50 ms duration pulse for mSiO2-based memristors with varying porosities.



Licence: No

Related projects: This work is part of the ADEPT project funded by a Programme Grant from the EPSRC (EP/N035437/1). 


Date that the file was created: Apr 2024