Optimal design of graphene-based plasmonic enhanced photodetector using PSO

Area of Science:

• Optoelectronics and Nanotechnology
• Plasmonics and Photodetection

Background:

• Photodetectors often face limitations due to complex parameter optimization and fabrication challenges.
• Existing models may oversimplify photodetector performance due to practical constraints on variable adjustment.
• Graphene and titanium nitride (TiN) offer unique properties for plasmonic excitation and CMOS compatibility.

Purpose of the Study:

• To introduce a novel graphene-based plasmonic photodetector optimized using the particle swarm optimization (PSO) algorithm.
• To design a photodetector structure that minimizes fabrication complexity and production costs.
• To achieve high performance metrics including responsivity and specific detectivity.

Main Methods:

• Utilized particle swarm optimization (PSO) to optimize photodetector parameters.
• Employed graphene for its unique detection properties and titanium nitride (TiN) as a CMOS-compatible plasmonic material.
• Investigated the photothermoelectric effect (PTE) for device operation at zero bias.

Main Results:

• Achieved high voltage responsivity (210.6215 V/W) and current responsivity (3.7213 A/W) at 1550 nm.
• Obtained ultra-compressed device length (< 3 μm) and specific detectivity (2.566 × 10^12 Jones).
• Demonstrated zero dark current and a very low noise equivalent power (NEP) of 4.5361 × 10^-13 W/√Hz.

Conclusions:

• The PSO-optimized graphene-based plasmonic photodetector represents a significant advancement in optoelectronic devices.
• The device's CMOS compatibility, high performance, and low noise characteristics make it suitable for various applications.
• The photothermoelectric effect (PTE) at zero bias contributes to the device's excellent performance and low NEP.