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Ion Exchange

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Ion exchange chromatography separates charged molecules from a solution by reversibly exchanging them with mobile, or 'active', ions associated with the oppositely charged stationary phase. This method can be used to separate ions, soften and deionize water, and purify solutions. The polymers comprising the ion-exchange column are high-molecular-weight and chemically stable polymers, crosslinked to be porous and essentially insoluble. They are also functionalized with either acidic or...

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Manufacturing of a Nafion-coated, Reduced Graphene Oxide/Polyaniline Chemiresistive Sensor to Monitor pH in Real-time During Microbial Fermentation

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In-Materio Reservoir Computing in a Sulfonated Polyaniline Network.

Yuki Usami^1,2,3, Bram van de Ven⁴, Dilu G Mathew⁴

¹Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama, Toyonaka, Osaka, 5600043, Japan.

Advanced Materials (Deerfield Beach, Fla.)

|September 17, 2021

Summary

This summary is machine-generated.

Sulfonated polyaniline (SPAN) organic electrochemical network devices show humidity-dependent properties for reservoir computing. These SPAN devices achieve high accuracy in waveform generation and spoken-digit classification tasks.

Keywords:

in-materio reservoir computing organic electrochemical networks polyaniline spoken-digit classification

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Area of Science:

Materials Science
Computational Neuroscience
Organic Electronics

Background:

Organic electrochemical network devices (OENDs) offer potential for novel computing paradigms.
Sulfonated polyaniline (SPAN) is a conductive polymer with tunable electrical properties.

Purpose of the Study:

To fabricate and characterize a SPAN-based OEND for reservoir computing (RC).
To investigate the influence of humidity on the device's electrical properties and RC performance.

Main Methods:

Fabrication of SPAN OEND via drop-casting on gold electrodes.
Characterization of current-voltage (I-V) properties under varying humidity.
Evaluation of RC tasks including waveform generation and short-term memory.

Main Results:

Humidity significantly impacts SPAN OEND conduction, shifting from electronic to ionic at high humidity.
Nonlinearity and hysteresis in I-V characteristics increase with humidity.
High accuracy (90%) in waveform generation and memory capacity (33.9) achieved.
Successful spoken-digit classification (60% accuracy) demonstrated.

Conclusions:

SPAN OENDs exhibit rich dynamic and nonlinear properties suitable for time-series data processing in RC.
The disordered SPAN network and humidity-dependent behavior enhance RC performance.
SPAN-based electrochemical systems present a viable platform for material-based computing.