Reconfigurable multiwavelength nanophotonic circuit based on a low-voltage, optically readable engineered resistive switch

Nanoscale optical functionalities show promise for unconventional computing, including neuromorphic and quantum information processing. Resistive switching devices with optical readability have drawn significant research interest for high-density non-volatile memory and unconventional computing. We proposed a multiwavelength nanophotonic circuit consisting of resistive switches based on Ag-SiO<sub>2</sub>-ITO on a silicon rib structure, with the capability to electrically remove any wavelength channel(s) at will. The device featured a four-layered structure with a SiO<sub>2</sub> region positioned between an Ag top electrode and an ITO bottom electrode on p-Si, confining the hybrid plasmonic mode within the SiO<sub>2</sub> region. The application of an external voltage caused the formation/rupture of conductive filaments in the SiO<sub>2</sub> layer, affecting optical absorption through hybrid mode interactions. Experimental results showed a 27 dB extinction ratio for a 10 μm × 500 nm active device operated at ±2 V. Additionally, the circuit achieved multiwavelength functionality using identical sources and 2 × 1 couplers, enhancing reconfigurability. The higher work function of ITO helped in reducing the energy barrier for ion migration, overcoming the intrinsic resistance of the SiO<sub>2</sub> layer. This engineered nanophotonic circuit, with its high extinction ratio, excellent retention, low-voltage operation, and rapid switching speed, is suitable for advanced memory devices, high-speed optical communication, neuromorphic and quantum computation, and programmable photonic circuits.

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Publication Details

Journal
Nanoscale
Published
2025-01-01
DOI
https://doi.org/10.1039/d5nr00463b
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Reconfigurable multiwavelength nanophotonic circuit based on a low-voltage, optically readable engineered resistive switch

Rahul Dev Mishra, Prem Babu, Suresh Kumar Pandey, Mukesh Kumar et al.
1 citations
Nanoscale
Advanced Memory and Neural Computing
0.73
article

Reconfigurable multiwavelength nanophotonic circuit based on a low-voltage, optically readable engineered resistive switch

Rahul Dev Mishra, Prem Babu, Suresh Kumar Pandey, Mukesh Kumar, Santosh Kumar, Ashutosh Kumar
article en
1 citations

Abstract

Nanoscale optical functionalities show promise for unconventional computing, including neuromorphic and quantum information processing. Resistive switching devices with optical readability have drawn significant research interest for high-density non-volatile memory and unconventional computing. We proposed a multiwavelength nanophotonic circuit consisting of resistive switches based on Ag-SiO<sub>2</sub>-ITO on a silicon rib structure, with the capability to electrically remove any wavelength channel(s) at will. The device featured a four-layered structure with a SiO<sub>2</sub> region positioned between an Ag top electrode and an ITO bottom electrode on p-Si, confining the hybrid plasmonic mode within the SiO<sub>2</sub> region. The application of an external voltage caused the formation/rupture of conductive filaments in the SiO<sub>2</sub> layer, affecting optical absorption through hybrid mode interactions. Experimental results showed a 27 dB extinction ratio for a 10 μm × 500 nm active device operated at ±2 V. Additionally, the circuit achieved multiwavelength functionality using identical sources and 2 × 1 couplers, enhancing reconfigurability. The higher work function of ITO helped in reducing the energy barrier for ion migration, overcoming the intrinsic resistance of the SiO<sub>2</sub> layer. This engineered nanophotonic circuit, with its high extinction ratio, excellent retention, low-voltage operation, and rapid switching speed, is suitable for advanced memory devices, high-speed optical communication, neuromorphic and quantum computation, and programmable photonic circuits.

NanoscaleVol. 17(17)
Indian Institute of Technology Indore (IN)
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.73
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