Mimicking somatic behavior of neurons using the integrate and fire model of 2D SnS memristive switching characteristics

This Letter presents the fabrication and characterization of a 2D SnS memristor, proposing its integrate and fire (I&F) model as a potential hardware implementation of neuronal somatic behavior. The memristor comprises a thin layer of tin (II) sulfide (SnS) sandwiched between copper (Cu) electrodes on a silicon (Si) substrate. This structure exhibits an impressive Roff:Ron ratio of 103 at a read voltage Vrd of 0.25 V with exceptionally low switching Vsw and set Vset voltages of 0.3 and 0.35 V, respectively, with ∼3 order variation between the maximum Rmax and Rmin resistances offered during single voltage sweep cycle. We have explained the memristive behavior using the dual ionic conduction mechanism in the SnS active layer. We extracted the real-time band diagram of SnS using ultraviolet photoelectron spectroscopy, explaining the low Vsw observed. We propose that the emulation of the I&F artificial neuron model exhibited by the fabricated device could serve as a promising application in the field of artificial neuron spiking.

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Publication Details

Journal
Applied Physics Letters
Published
2024-11-04
DOI
https://doi.org/10.1063/5.0226599
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.83
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article

Mimicking somatic behavior of neurons using the integrate and fire model of 2D SnS memristive switching characteristics

Vivek Adepu, Parikshit Sahatiya, Soumi Saha, Surya Shankar Dan
4 citations
Applied Physics Letters
Advanced Memory and Neural Computing
0.83
article

Mimicking somatic behavior of neurons using the integrate and fire model of 2D SnS memristive switching characteristics

Vivek Adepu, Parikshit Sahatiya, Soumi Saha, Surya Shankar Dan
article en
4 citations

Abstract

This Letter presents the fabrication and characterization of a 2D SnS memristor, proposing its integrate and fire (I&F) model as a potential hardware implementation of neuronal somatic behavior. The memristor comprises a thin layer of tin (II) sulfide (SnS) sandwiched between copper (Cu) electrodes on a silicon (Si) substrate. This structure exhibits an impressive Roff:Ron ratio of 103 at a read voltage Vrd of 0.25 V with exceptionally low switching Vsw and set Vset voltages of 0.3 and 0.35 V, respectively, with ∼3 order variation between the maximum Rmax and Rmin resistances offered during single voltage sweep cycle. We have explained the memristive behavior using the dual ionic conduction mechanism in the SnS active layer. We extracted the real-time band diagram of SnS using ultraviolet photoelectron spectroscopy, explaining the low Vsw observed. We propose that the emulation of the I&F artificial neuron model exhibited by the fabricated device could serve as a promising application in the field of artificial neuron spiking.

Applied Physics LettersVol. 125(19)
Birla Institute of Technology and Science - Hyderabad Campus (IN), Birla Institute of Technology and Science, Pilani (IN)
Affordable and clean energy
Openalex Percentile: Top 26%
Advanced Memory and Neural Computing
0.83
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