Non-linear 2D-material integrated photonics
Lead Research Organisation:
University of Manchester
Department Name: Electrical and Electronic Engineering
Abstract
Light-based information processing possesses the potential for beyond-Moore computational architectures and complementing or even replacing traditional approaches such as the von Neumann architecture. However, equivalent to the transistor as a fundamental building block in electrical circuits and chips, photonic circuits require controllable non-linear elements and devices to process data.
The student will study the feasibility of co-integrating CMOS-technology based photonic structures such as waveguides, modulators and photonic crystals with 2D-materials to investigate, exploit and enhance the inherently large non-linear properties of 2D-materials for active photonic devices. Starting from theoretical investigations (simulations) of potential device architectures, the student will fabricate and characterize these structures and evaluate their potential as building blocks for optical computing.
The research will contribute to further understanding and suitability of photonic structures for novel information processing architectures. In particular, the exponentially growing demand in computing power for artificial intelligence (AI) requires novel neuromorphic hardware architectures, which can potentially be addressed by optical computing.
The student will study the feasibility of co-integrating CMOS-technology based photonic structures such as waveguides, modulators and photonic crystals with 2D-materials to investigate, exploit and enhance the inherently large non-linear properties of 2D-materials for active photonic devices. Starting from theoretical investigations (simulations) of potential device architectures, the student will fabricate and characterize these structures and evaluate their potential as building blocks for optical computing.
The research will contribute to further understanding and suitability of photonic structures for novel information processing architectures. In particular, the exponentially growing demand in computing power for artificial intelligence (AI) requires novel neuromorphic hardware architectures, which can potentially be addressed by optical computing.
Organisations
People |
ORCID iD |
Tim Echtermeyer (Primary Supervisor) | |
William Wren (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R513131/1 | 30/09/2018 | 29/09/2023 | |||
2503837 | Studentship | EP/R513131/1 | 30/09/2020 | 30/07/2024 | William Wren |
EP/T517823/1 | 30/09/2020 | 29/09/2025 | |||
2503837 | Studentship | EP/T517823/1 | 30/09/2020 | 30/07/2024 | William Wren |