GRAPHENE-ENABLED CMOS RECONFIGURABLE OPTO-FLUIDICS: TOWARDS ON-CHIP ARCHITECTING OF METADEVICES

石墨烯 CMOS 可重构光流控:迈向元设备的片上架构

基本信息

  • 批准号:
    EP/N035569/1
  • 负责人:
  • 金额:
    $ 12.88万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2016
  • 资助国家:
    英国
  • 起止时间:
    2016 至 无数据
  • 项目状态:
    已结题

项目摘要

Today, innovation of novel reconfigurable materials, which can be integrated on Si chip and used for engineering devices, is the key driver for realization of future chip-scale multi-functional systems for applications impacting almost every aspect of life, from energy saving systems and high-speed internet to small consumer devices. This project proposes the novel concept for on-chip architecting of the dynamically reconfigurable systems on Si chip for many advanced optoelectronics device applications. This will be achieved using novel reconfigurable nanocomposites, based on nematic liquid crystals doped with graphene. For the first time, we propose the optofluidic technology for the infiltration of developed in this project nanocomposites into Si photonic platform and for their direct low-power controllable self-assembling into defined micro-structures and micro-devices. The approach to realize this ambitiouse aim in 24 motnhs of this project is (A) to develop novel nanocomosite material platform for integration on Si chip; (B) to demosntrate the first electrically/themrally driven reconfigurable device integrated into micro-photonic circuit on Si chip, i.e. an active metamaterial structure with an ability to filter, split, and switch polarized light in the plane of chip.
今天,新型可重构材料的创新,可以集成在硅片上并用于工程设备,是实现未来芯片级多功能系统的关键驱动因素,这些系统几乎影响生活的各个方面,从节能系统和高速互联网到小型消费设备。本项目为许多先进的光电子器件应用的硅片上动态可重构系统的片上架构提出了新的概念。这将通过使用新型可重构纳米复合材料来实现,该复合材料基于掺杂石墨烯的向列液晶。我们首次提出了将本课题开发的纳米复合材料渗透到硅光子平台中,并将其直接低功耗可控自组装成定义的微结构和微器件的光流技术。在本项目24个月内实现这一雄心勃勃的目标的方法是:(A)开发新型纳米复合材料集成在硅片上的平台;(B)展示了第一个集成在硅片微光子电路中的电/热驱动可重构器件,即具有在芯片平面上过滤、分裂和切换偏振光能力的有源超材料结构。

项目成果

期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
O-band N-rich silicon nitride MZI based on GST
  • DOI:
    10.1063/1.5140350
  • 发表时间:
    2020-03-02
  • 期刊:
  • 影响因子:
    4
  • 作者:
    Faneca, Joaquin;Bucio, Thalia Dominguez;Baldycheva, Anna
  • 通讯作者:
    Baldycheva, Anna
One-Dimensional Multi-Channel Photonic Crystal Resonators Based on Silicon-On-Insulator With High Quality Factor
  • DOI:
    10.3389/fphy.2018.00033
  • 发表时间:
    2018-05-08
  • 期刊:
  • 影响因子:
    3.1
  • 作者:
    Faneca, Joaquin;Perova, Tatiana S.;Baldycheva, Anna
  • 通讯作者:
    Baldycheva, Anna
A Comprehensive Model of Nitrogen-Free Ordered Carbon Quantum Dots
无氮有序碳量子点的综合模型
  • DOI:
    10.48550/arxiv.2211.15178
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Boukhvalov D
  • 通讯作者:
    Boukhvalov D
A comprehensive model of nitrogen-free ordered carbon quantum dots.
  • DOI:
    10.1186/s11671-023-03773-0
  • 发表时间:
    2023-01-31
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
Spatial tracking of individual fluid dispersed particles via Raman spectroscopy.
通过拉曼光谱对单个流体分散颗粒进行空间跟踪。
  • DOI:
    10.17863/cam.74884
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hogan B
  • 通讯作者:
    Hogan B
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Anna Baldycheva其他文献

Data-centric approach for instance segmentation in optical waste sorting
  • DOI:
    10.1016/j.wasman.2024.11.002
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Anna Iliushina;Gleb Mazanov;Sergey Nesteruk;Andrey Pimenov;Anton Stepanov;Nadezhda Mikhaylova;Anna Baldycheva;Andrey Somov
  • 通讯作者:
    Andrey Somov
Discrete Spectral Sensing System for Separation of Polyolefin Waste Plastics
用于分离聚烯烃废塑料的离散光谱传感系统

Anna Baldycheva的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似海外基金

M2DESCO - Computational Multimode Modelling Enabled Design of Safe & Sustainable Multi-Component High-Entropy Coatings
M2DESCO - 计算多模式建模支持安全设计
  • 批准号:
    10096988
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    EU-Funded
6G Goal-Oriented AI-enabled Learning and Semantic Communication Networks (6G Goals)
6G目标导向的人工智能学习和语义通信网络(6G目标)
  • 批准号:
    10110118
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    EU-Funded
Low Carbon Impact AI-Enabled Net Zero Advisory Solution
低碳影响人工智能支持的净零咨询解决方案
  • 批准号:
    10112272
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    SME Support
N2Vision+: A robot-enabled, data-driven machine vision tool for nitrogen diagnosis of arable soils
N2Vision:一种由机器人驱动、数据驱动的机器视觉工具,用于耕地土壤的氮诊断
  • 批准号:
    10091423
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Collaborative R&D
CBET-EPSRC: TECAN - Telemetry-Enabled Carbon Aware Networking
CBET-EPSRC:TECAN - 支持遥测的碳感知网络
  • 批准号:
    EP/X040828/1
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Research Grant
Collaborative Research: GEO OSE Track 2: Developing CI-enabled collaborative workflows to integrate data for the SZ4D (Subduction Zones in Four Dimensions) community
协作研究:GEO OSE 轨道 2:开发支持 CI 的协作工作流程以集成 SZ4D(四维俯冲带)社区的数据
  • 批准号:
    2324714
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Standard Grant
RII Track-4:NSF: Design of zeolite-encapsulated metal phthalocyanines catalysts enabled by insights from synchrotron-based X-ray techniques
RII Track-4:NSF:通过基于同步加速器的 X 射线技术的见解实现沸石封装金属酞菁催化剂的设计
  • 批准号:
    2327267
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Standard Grant
CAREER: Data-Enabled Neural Multi-Step Predictive Control (DeMuSPc): a Learning-Based Predictive and Adaptive Control Approach for Complex Nonlinear Systems
职业:数据支持的神经多步预测控制(DeMuSPc):一种用于复杂非线性系统的基于学习的预测和自适应控制方法
  • 批准号:
    2338749
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Standard Grant
Collaborative Research: Spintronics Enabled Stochastic Spiking Neural Networks with Temporal Information Encoding
合作研究:自旋电子学支持具有时间信息编码的随机尖峰神经网络
  • 批准号:
    2333881
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Standard Grant
Collaborative Research: Spintronics Enabled Stochastic Spiking Neural Networks with Temporal Information Encoding
合作研究:自旋电子学支持具有时间信息编码的随机尖峰神经网络
  • 批准号:
    2333882
  • 财政年份:
    2024
  • 资助金额:
    $ 12.88万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了