Pressure-gated microfluidic memristor for pulsatile information processing

A hitherto unexploited characteristic feature of emerging iontronic devices for information processing is the intrinsic mobility of the medium (water) of dissolved ions in aqueous electrolytes, which therefore respond not only to voltage but also to pressure. Here we study a microfluidic memristor, in the form of a conical channel, exposed to simultaneously applied time-dependent voltage and pressure drops, through numerical solutions of the Poisson-Nernst-Planck-Stokes equations for ion and fluid transport. We show that the channel's memristive properties can be enhanced, reduced, or instantaneously reset by appropriate pressure, and we leverage this finding with two examples of time series processing of simultaneously applied voltage and pressure pulses. We show not only that the distinction between different voltage time series can be improved by enhancing the conductance response with corresponding pressure pulses, but also that the bandwidth of information transfer through the channel can be doubled by letting the pressure pulses represent a second independent time series.

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Publication Details

Journal
Physical Review Applied
Published
2024-11-20
DOI
https://doi.org/10.1103/physrevapplied.22.054057
Citations
7
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

Pressure-gated microfluidic memristor for pulsatile information processing

R. van Roij, A. Barnaveli, Willem Q. Boon, T. M. Kamsma
7 citations
Physical Review Applied
Advanced Memory and Neural Computing
1.46
article

Pressure-gated microfluidic memristor for pulsatile information processing

R. van Roij, A. Barnaveli, Willem Q. Boon, T. M. Kamsma
article en
7 citations

Abstract

A hitherto unexploited characteristic feature of emerging iontronic devices for information processing is the intrinsic mobility of the medium (water) of dissolved ions in aqueous electrolytes, which therefore respond not only to voltage but also to pressure. Here we study a microfluidic memristor, in the form of a conical channel, exposed to simultaneously applied time-dependent voltage and pressure drops, through numerical solutions of the Poisson-Nernst-Planck-Stokes equations for ion and fluid transport. We show that the channel's memristive properties can be enhanced, reduced, or instantaneously reset by appropriate pressure, and we leverage this finding with two examples of time series processing of simultaneously applied voltage and pressure pulses. We show not only that the distinction between different voltage time series can be improved by enhancing the conductance response with corresponding pressure pulses, but also that the bandwidth of information transfer through the channel can be doubled by letting the pressure pulses represent a second independent time series.

Physical Review AppliedVol. 22(5)
Utrecht University (NL)
Affordable and clean energy
Openalex Percentile: Top 17%
Advanced Memory and Neural Computing
1.46
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