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Manufacturing scalable semiconductor quantum light sources

Manufacturing scalable semiconductor quantum light sources
制造可扩展的半导体量子光源
批准号:
EP/T017813/1
负责人:
Anthony Bennett
金额:
$133.96万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
Semiconductors have already revolutionised the world around us through the inventions of the transistor, diode lasers, integrated circuits and sensors. A new wave of semiconductor quantum technologies are finding commercial applications in ultra-secure communications, enhanced imaging, sensing, and possibly even computing and simulations. In all these cases the "quantum advantage" is theoretically proven and experimentally demonstrated, but there is a strong need for a scalable, practical and efficient source of quantum light. Naturally occurring point-like light sources called "colour centres" act as quantum light sources in wide bandgap semiconductors such as diamond, Silicon Carbide, Boron Nitride and Gallium Nitride (GaN) at room temperature. Commercially, GaN now dominates the market for solid state lighting, because it is an efficient and manufacturable material, leading to costs of less than one dollar per LED. However, Gallium-Nitride is also a promising material for quantum light sources as the colour centres within it emit from the ultra-violet to the near infra-red. This wide range means the emission overlaps with minima in the absorption curves of optical fibres (1310 and 1550 nm), transitions in the best atomic quantum memories (near 800nm) and low loss free-space communications in the blue. Furthermore, by engineering heterostructures within the semiconductor it is possible to electrically drive the emitter, rapidly switch the device and design efficiency-enhancing structures. This fellowship will apply manufacturing techniques widespread in the compound semiconductor manufacturing field, such as large area epitaxy and wafer scale processing, to deliver a bright and room temperature quantum light-emitting diode based on GaN. I will use laser lithography, standardised packaging and quality control to ensure the end device is produced in a manner that enables scale up to mass-production, with the full supply chain within the UK. Collaboration with the UK semiconductor industry for growth and packaging of devices, and use of processing facilities installed at Cardiff University, will foster two-way knowledge exchange between industry and academia. My experience of this type of collaboration at Imperial-Agilent and at Toshiba-Cambridge, makes me uniquely well-qualified to manage this interaction. By funding me to devote a significant amount of my time to research for the next 5 years this project will deliver high impact research and build a platform for future UK prosperity and technological know-how.
期刊论文(10)
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会议论文
DOI: 10.1063/5.0085257
发表时间: 2022-02
期刊: Applied Physics Letters
影响因子: 4
作者: [S. Bishop;J. Hadden;R. Hekmati;J. K. Cannon;W. Langbein;A. Bennett]
通讯作者: S. Bishop;J. Hadden;R. Hekmati;J. K. Cannon;W. Langbein;A. Bennett
DOI: 10.1063/5.0155968
发表时间: 2023-03
期刊: Applied Physics Letters
影响因子: 4
作者: [P. Androvitsaneas;R. Clark;M. Jordan;Miguel Alvarez Perez;T. Peach;Stuart N. Thomas;Saleem Shabbir;A. Sobiesierski;A. Trapalis;I. Farrer;W. Langbein;A. Bennett]
通讯作者: P. Androvitsaneas;R. Clark;M. Jordan;Miguel Alvarez Perez;T. Peach;Stuart N. Thomas;Saleem Shabbir;A. Sobiesierski;A. Trapalis;I. Farrer;W. Langbein;A. Bennett
Evanescent-field assisted photon collection from quantum emitters under a solid immersion lens
固体浸没透镜下的倏逝场辅助量子发射器收集光子
DOI: 10.1088/1367-2630/ac9697
发表时间: 2022
期刊: New Journal of Physics
影响因子: 3.3
作者: [Bishop S]
通讯作者: Bishop S
DOI: 10.1063/5.0080348
发表时间: 2022-01-10
期刊: APPLIED PHYSICS LETTERS
影响因子: 4
作者: [Giakoumaki, A. N., Coccia, G., Eaton, S. M.]
通讯作者: Eaton, S. M.
8
    Quantum GaN-O-Photonics
    • 批准号:
      EP/X03982X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $67.56万
    • 财政年份:
      2024
    • 负责人:
      Anthony Bennett
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis