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Phase-Engineered In2Se3 Ferroelectric P-N Junctions in Phototransistors for Ultra-Low Power and Multiscale Reservoir

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This study introduces a novel optoelectronic synapse using Indium Selenide/Tungsten Diselenide ferroelectric p-n junctions (FePNJs) for advanced neuromorphic computing. These devices enable ultralow-power in-sensor computing, handwritten digit recognition, and multiscale motion detection.

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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Nanotechnology

Background:

  • Two-dimensional (2D) ferroelectric field-effect transistors (Fe-FETs) are foundational for future neuromorphic hardware.
  • Indium Selenide (In2Se3) exhibits ferroelectric, photoelectric, and phase transition properties, making it promising for in-sensor computing.
  • Ferroelectric p-n junctions (FePNJs) based on In2Se3 are underexplored.

Purpose of the Study:

  • To develop and investigate an optoelectronic synapse based on α-In2Se3/WSe2 FePNJs.
  • To explore the potential of these FePNJs for ultralow-power in-sensor computing and multiscale signal processing.
  • To demonstrate an all-ferroelectric in-sensor reservoir computing system for handwritten digit recognition and motion detection.

Main Methods:

  • Fabrication of β'-In2Se3/WSe2 and α-In2Se3/WSe2 FePNJs using chemical vapor deposition (CVD) and phase transition.
  • Characterization of synaptic effects, including memory retention and multilevel current states.
  • Construction and testing of an all-ferroelectric in-sensor reservoir computing system and a multiscale reservoir computing system.

Main Results:

  • The α-In2Se3/WSe2 FePNJ exhibits enhanced and tunable synaptic effects with memory retention >2500 s and >8 multilevel states.
  • Achieved atto-joule level power consumption for synaptic operations.
  • Demonstrated ultralow-power handwritten digit recognition using an all-ferroelectric in-sensor reservoir computing system.
  • Successfully detected motions across a wide speed range (1-100 km h-1) using a multiscale reservoir computing system.

Conclusions:

  • The developed α-In2Se3/WSe2 FePNJ is a highly efficient optoelectronic synapse for neuromorphic applications.
  • The FePNJ technology enables ultralow-power in-sensor computing and advanced signal processing.
  • This work paves the way for next-generation intelligent hardware with integrated sensing and computing capabilities.