Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.0
Journals
Micromachines
Special Issues
Devices in Silicon Photonics
share announcement

Devices in Silicon Photonics

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A：Physics".

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 2261

Special Issue Editor

Dr. Yin Xu

E-Mail Website
Guest Editor
School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215006, China
Interests: silicon photonics; photonic integrated circuits; on-chip frequency comb
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Compared with traditional optics, integrated optics caused a technological revolution once various optical devices could be integrated on chips with compact size, lower energy consumption, and high stability, solving the deficiencies of traditional optics. Based on the high refractive-index-contrast and CMOS-compatible processing of the silicon-on-insulator material, it has become a quite promising platform for integrated optics, allowing silicon photonics to emerge. Up to now, many functional devices have been developed to solve the issues of electro-optic modulation, wavelength/polarization/mode management, fiber-to-chip coupling, high-capacity transmission, signal processing, photo-electric detection, and others in the field of silicon photonics. Recently, new technologies (e.g., artificial intelligence algorithms) and materials (e.g., 2D materials, phase change materials, ferroelectric materials) have been introduced to silicon photonics to enhance device performance and explore some new applications.

This Special Issue focuses on the state-of-the-art achievements in silicon photonic devices, covering new device structures, new photonic materials, new fabrication techniques and new applications. With the unflagging efforts of the worldwide researchers, we believe silicon photonics will enter a new stage of development with powerful device functions, high integration densities, and cutting-edge applications.

Dr. Yin Xu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • high-performance electro-optic modulators
  • wavelength/polarization/mode management devices
  • fiber-to-chip coupling devices
  • on-chip high-capacity transmissions
  • signal processing for the photonic integrated circuits
  • efficient photo-electric detectors
  • new materials assisted photonic devices
  • integrated photonic neural network and optical computing
  • integrated quantum photonic devices
  • large-scale photonic integrated circuits

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

10 pages, 12545 KiB  
Article
Simulating an Integrated Photonic Image Classifier for Diffractive Neural Networks
by Huayi Sheng and Muhammad Shemyal Nisar
Micromachines 2024, 15(1), 50; https://doi.org/10.3390/mi15010050 - 26 Dec 2023
Cited by 2 | Viewed by 1736
Abstract
The slowdown of Moore’s law and the existence of the “von Neumann bottleneck” has led to electronic-based computing systems under von Neumann’s architecture being unable to meet the fast-growing demand for artificial intelligence computing. However, all-optical diffractive neural networks provide a possible solution [...] Read more.
The slowdown of Moore’s law and the existence of the “von Neumann bottleneck” has led to electronic-based computing systems under von Neumann’s architecture being unable to meet the fast-growing demand for artificial intelligence computing. However, all-optical diffractive neural networks provide a possible solution to this challenge. They can outperform conventional silicon-based electronic neural networks due to the significantly higher speed of the propagation of optical signals (≈108 m.s−1) compared to electrical signals (≈105 m.s−1), their parallelism in nature, and their low power consumption. The integrated diffractive deep neural network (ID2NN) uses an on-chip fully passive photonic approach to achieve the functionality of neural networks (matrix–vector operations) and can be fabricated via the CMOS process, which is technologically more amenable to implementing an artificial intelligence processor. In this paper, we present a detailed design framework for the integrated diffractive deep neural network and corresponding silicon-on-insulator integration implementation through Python-based simulations. The performance of our proposed ID2NN was evaluated by solving image classification problems using the MNIST dataset. Full article
(This article belongs to the Special Issue Devices in Silicon Photonics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop