Enhancing Nonlinear Optical Absorption in SnS <sub>2</sub> Through Electrostatic Doping for Optical Neural Network Applications

Abstract The development of high‐performance nonlinear optical (NLO) materials is crucial for advancing photoelectric devices, particularly optical nonlinear activation units in optical neural networks (ONNs), yet it remains a significant challenge. In this work, it is demonstrated that electrostatic doping offers a versatile strategy to enhance the NLO performance of two‐dimensional materials, with promising implications for ONN applications. As a proof of concept, we employed proton (H⁺) intercalation to dope SnS 2 . Spectroscopic characterizations, including Raman, X‐ray photoelectron spectroscopy, and electron paramagnetic resonance, confirm successful electrostatic doping with negligible lattice expansion or defect generation. The doped SnS 2 exhibits enhanced saturable absorption (SA), two‐photon absorption (2PA), or three‐photon absorption (3PA) under femtosecond laser excitation across a broad wavelength range (515–1550 nm). The enhancement in SA is attributed to increased electron population in the conduction band that strengthens the Pauli blocking effect, while the improvements in 2PA and 3PA arise from the internal electric field generated by intercalated H⁺ ions within the van der Waals gaps and accumulated electrons in SnS 2 . The application potential of H⁺‐intercalated SnS 2 is further validated in a modeled ONN, where it achieves digit recognition accuracy comparable to that of conventional electronic activation functions.

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Publication Details

Journal
Advanced Optical Materials
Published
2025-10-26
DOI
https://doi.org/10.1002/adom.202502300
Citations
1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
2.48
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article

Enhancing Nonlinear Optical Absorption in SnS 2 Through Electrostatic Doping for Optical Neural Network Applications

Mark Graeme Humphrey, Yuting Ke, Chi Zhang, Zhipeng Huang et al.
1 citations
Advanced Optical Materials
Neural Networks and Reservoir Computing
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article

Enhancing Nonlinear Optical Absorption in SnS 2 Through Electrostatic Doping for Optical Neural Network Applications

Mark Graeme Humphrey, Yuting Ke, Chi Zhang, Zhipeng Huang, Danil W. Boukhvalov
article en
1 citations

Abstract

Abstract The development of high‐performance nonlinear optical (NLO) materials is crucial for advancing photoelectric devices, particularly optical nonlinear activation units in optical neural networks (ONNs), yet it remains a significant challenge. In this work, it is demonstrated that electrostatic doping offers a versatile strategy to enhance the NLO performance of two‐dimensional materials, with promising implications for ONN applications. As a proof of concept, we employed proton (H⁺) intercalation to dope SnS 2 . Spectroscopic characterizations, including Raman, X‐ray photoelectron spectroscopy, and electron paramagnetic resonance, confirm successful electrostatic doping with negligible lattice expansion or defect generation. The doped SnS 2 exhibits enhanced saturable absorption (SA), two‐photon absorption (2PA), or three‐photon absorption (3PA) under femtosecond laser excitation across a broad wavelength range (515–1550 nm). The enhancement in SA is attributed to increased electron population in the conduction band that strengthens the Pauli blocking effect, while the improvements in 2PA and 3PA arise from the internal electric field generated by intercalated H⁺ ions within the van der Waals gaps and accumulated electrons in SnS 2 . The application potential of H⁺‐intercalated SnS 2 is further validated in a modeled ONN, where it achieves digit recognition accuracy comparable to that of conventional electronic activation functions.

Advanced Optical MaterialsVol. 13(35)
Tongji University (CN), Australian National University (AU), Ural Federal University (RU), Nanjing Forestry University (CN), Institute of Physics and Technology (RU)
Openalex Percentile: Top 8%
Neural Networks and Reservoir Computing
2.48
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