Neuromorphic Photoresponse in Ultrathin SnS<sub>2</sub>-Based Field Effect Transistor

As artificial intelligence continues to evolve, neuromorphic technologies, which emulate biological neural networks, are increasingly seen as a promising direction. Two-dimensional materials are considered promising for neuromorphic applications due to their tunable electrical and optoelectronic properties. In this work, a back-gated tin disulfide (SnS<sub>2</sub>) field-effect transistor (FET) is electrically and optoelectronically characterized at different temperatures (80, 295, and 380 K), pressures (ambient and 10<sup>-4</sup> mbar), and illumination conditions (dark and laser light from 420 to 800 nm). Responsivity peaks of up to ∼100 A/W are recorded. Persistent photoconductivity is observed, with current retention after illumination ranging from 0% to ∼30% of the initial dark current, depending on temperature and gate voltage. The underlying microscopic mechanisms are analyzed, revealing a key role for trap states and ambient adsorbates, and a qualitative model is proposed to explain the observed effects. Trap states within the bandgap, often considered detrimental, are exploited to induce synaptic plasticity, with synaptic weight changes tunable from 0.001 to 3000. Temperature and gate voltage are found to be effective parameters for modulating plasticity, enabling smooth transitions between short-term and long-term behavior. These results clarify the microscopic origin of plasticity in SnS<sub>2</sub>, demonstrate its robustness under realistic conditions, and lay the foundation for the integration of this two-dimensional material into next-generation neuromorphic architectures.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-08-26
DOI
https://doi.org/10.1021/acsami.5c11651
Citations
7
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
5.11

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article

Neuromorphic Photoresponse in Ultrathin SnS2-Based Field Effect Transistor

Anna Sessa, Enver Faella, Crispin Hetherington, C. S. Lue et al.
7 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
5.11
article

Neuromorphic Photoresponse in Ultrathin SnS2-Based Field Effect Transistor

Anna Sessa, Enver Faella, Crispin Hetherington, C. S. Lue, M. Passacantando, Martino Aldrigo, Gianluca D’Olimpio, Tsotne Dadiani, S. De Stefano, Cătălin Pârvulescu, O. Durante, Adrian Dinescu, Antonio Politano, Antonio Di Bartolomeo, Chia‐Nung Kuo
article en
7 citations

Abstract

As artificial intelligence continues to evolve, neuromorphic technologies, which emulate biological neural networks, are increasingly seen as a promising direction. Two-dimensional materials are considered promising for neuromorphic applications due to their tunable electrical and optoelectronic properties. In this work, a back-gated tin disulfide (SnS<sub>2</sub>) field-effect transistor (FET) is electrically and optoelectronically characterized at different temperatures (80, 295, and 380 K), pressures (ambient and 10<sup>-4</sup> mbar), and illumination conditions (dark and laser light from 420 to 800 nm). Responsivity peaks of up to ∼100 A/W are recorded. Persistent photoconductivity is observed, with current retention after illumination ranging from 0% to ∼30% of the initial dark current, depending on temperature and gate voltage. The underlying microscopic mechanisms are analyzed, revealing a key role for trap states and ambient adsorbates, and a qualitative model is proposed to explain the observed effects. Trap states within the bandgap, often considered detrimental, are exploited to induce synaptic plasticity, with synaptic weight changes tunable from 0.001 to 3000. Temperature and gate voltage are found to be effective parameters for modulating plasticity, enabling smooth transitions between short-term and long-term behavior. These results clarify the microscopic origin of plasticity in SnS<sub>2</sub>, demonstrate its robustness under realistic conditions, and lay the foundation for the integration of this two-dimensional material into next-generation neuromorphic architectures.

ACS Applied Materials & InterfacesVol. 17(36)
University of Salerno (IT), Lund University (SE), University of L'Aquila (IT), National Science and Technology Council (ZM), National Institute for Research and Development in Microtechnologies (RO), National Science and Technology Council (TW), National Evolutionary Synthesis Center (US), National Cheng Kung University (TW)
European Commission, Università degli Studi di Salerno, HORIZON EUROPE Framework Programme, European Regional Development Fund
Affordable and clean energy
Openalex Percentile: Top 4%
Advanced Memory and Neural Computing
5.11
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