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

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• Neuromorphic computing requires efficient temporal information processing.
• Memristor switching dynamics are crucial for neuromorphic systems.
• Controlling memristor switching via electrolyte properties is key for advanced data processing.

Purpose of the Study:

• To synthesize mesoporous silica (mSiO2) films for tunable memristor switching dynamics.
• To investigate the effect of controllable porosity on memristor performance.
• To establish mSiO2 as a platform for precise control in diffusive memristors.

Main Methods:

• Sol-gel process for synthesizing mSiO2 films with controlled porosity.
• Fabrication of diffusive memristors utilizing mSiO2 as electrolyte layers.
• Characterization of memristor switching dynamics, operating currents, facilitation ratios, and relaxation times.

Main Results:

• mSiO2 memristors exhibit short-term plasticity, vital for temporal signal processing.
• Increasing mSiO2 porosity leads to observable changes in operating currents, facilitation ratios, and relaxation times.
• Systematic control of switching dynamics is achieved by modulating hydrogen-bonded networks in the silica layer.

Conclusions:

• Mesoporous silica offers a versatile platform for precisely controlling neuromorphic switching dynamics in diffusive memristors.
• The porosity of mSiO2 films directly influences ion migration and anodic oxidation, thereby tuning device behavior.
• This work advances the development of memristors for enhanced temporal information processing in neuromorphic applications.