Grants and Contributions:

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Title:

Optimization of component robustness using AI-based digital twin of silicon photonic component fabrication

Agreement Number:

1003782

Agreement Value:

$666,600.00

Agreement Date:

Mar 31, 2023 - Mar 31, 2026

Description:

This project exploits machine learning algorithms in the design of the next generation photonic circuits with enhanced performance. Taking the approach further, machine learning is also exploited in creating a digital twin of silicon photonic fabrication, so that fabrication induced variations can be accurately captured and pre-emptively corrected. Photonic integrated circuits render optical system ideas more practical with increased performance along with reduced size and cost. Silicon photonics, in particular, exploiting the ubiquitous microelectronic miniaturization infrastructure, enables complex optical modules that can be fit into an iPhone, with applications from optical and quantum communications to medical diagnostics. Future applications demand further size reduction and increased functionality. Among the major challenges to achieving these goals, one is to create optical functionalities beyond classical optics. Another is the miniaturization leads to variability in their performance after fabrication.

Organization:

National Research Council Canada

Expected Results:

In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.

Location:

Montreal, Quebec, CA H2X 0A8

Reference Number:

172-2022-2023-Q4-1003782

Agreement Type:

Grant

Report Type:

Grants and Contributions

Recipient Business Number:

119128981

Recipient Type:

Academia

Recipient's Legal Name:

THE ROYAL INSTITUTION FOR THE ADVANCEMENT OF LEARNING / MCGILL UNIVERSITY

Federal Riding Name:

Ville-Marie–Le Sud-Ouest–Île-des-Sœurs

Federal Riding Number:

24077

Program:

Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Program Purpose:

Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.

NAICS Code:

541710