Algorithmically Designed Optoelectronic Devices
算法设计的光电器件
基本信息
- 批准号:RGPIN-2019-05130
- 负责人:
- 金额:$ 2.04万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2019
- 资助国家:加拿大
- 起止时间:2019-01-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The program described herein explores the algorithmic design, experimental fabrication, and characterisation of nanophotonic structures for optoelectronic devices. The long term objective is to utilise these processes to create 3D structured devices, including photonic siphons, spectral sorters, and hybrid antennas, which would allow revolutionary advances for the fields of quantum computing, solar energy conversion, and machine vision.***The major objectives of this program are threefold:******1Algorithmic design***At the nanoscale, light behaves both as a particle and a wave, complicating the design of structures with sub-wavelength features, to the point where even the function of a nanophotonic component cannot be determined intuitively. Algorithmic design addresses this, allowing full-wave optical simulations to dictate the geometry of the nanophotonic object. We previously demonstrated the use of an evolutionary algorithm to design ~2.5D dielectric structures. These design techniques will now be taken much furtherincorporation of artificial neural networks, automatic differentiation-based simulations, and inverse design, will allow structures to be designed faster and with larger degrees of freedom. This allows us to expand into fully 3D designs, and even multi-material systems, thereby not only achieving further improvements in performance, but also introducing a wide range of unprecedented optical and electronic functionalities.******2Fabrication in 3D***Cognisant of the limited 3D structure in optoelectronic devices, our second objective is the creation of ways to fabricate the complex multi-material systems our algorithms design. We have previously demonstrated the ability to utilise 3D multi-photon lithography techniques to produce nanophotonic structures with sub-wavelength features. This will continue to be developed, along with exploration into new techniques as well; we are currently collaborating to introduce 3D printing using electron beam-induced deposition for feature resolutions of tens of nanometers. This is currently being explored for glassy materials, but will be expanded to metals as well. Furthermore, we are collaborating to utilise self-assembly of complex 3D geometries to allow parallel deposition of structures over a large substrate, and even deposition of semiconductor materials.******2Nanophotonic characterisation***Characterisation at high resolution is essential to the development of new devices, particularly those with novel properties. Previously we applied a super-resolution localisation microscopy technique to probe the photonic environment around simple nanowire structures. This will be further developed to understand the performance of the much more complex devices created in this program. Furthermore, an integrated in situ fabrication and measurement system will allow for development of novel structures in an automated system, providing a physical accompaniment to the algorithmic design process of the first objective.
本文描述的程序探索了光电器件纳米光子结构的算法设计、实验制造和表征。长期目标是利用这些工艺来创建 3D 结构化设备,包括光子虹吸管、光谱分类器和混合天线,这将为量子计算、太阳能转换和机器视觉领域带来革命性的进步。***该计划的主要目标有三个:******1算法设计***在纳米尺度上,光既表现为粒子又表现为波,使具有亚波长特征的结构设计变得复杂,甚至到了纳米光子组件的功能无法凭直觉判断。算法设计解决了这个问题,允许全波光学模拟来决定纳米光子物体的几何形状。我们之前演示了如何使用进化算法来设计~2.5D 介电结构。这些设计技术现在将进一步结合人工神经网络、基于自动微分的模拟和逆向设计,从而使结构设计速度更快,自由度更大。这使我们能够扩展到完全 3D 设计,甚至多材料系统,从而不仅进一步提高性能,而且还引入了各种前所未有的光学和电子功能。******23D 制造** *认识到光电器件中 3D 结构的有限性,我们的第二个目标是创造方法来制造我们算法设计的复杂多材料系统。我们之前已经展示了利用 3D 多光子光刻技术来生产具有亚波长特征的纳米光子结构的能力。这将继续发展,同时也会探索新技术;我们目前正在合作推出使用电子束诱导沉积的 3D 打印,其特征分辨率可达数十纳米。目前正在针对玻璃材料进行探索,但也将扩展到金属。此外,我们正在合作利用复杂 3D 几何形状的自组装,以允许在大型基板上并行沉积结构,甚至沉积半导体材料。******2纳米光子表征***高分辨率表征对于新设备的开发,特别是那些具有新特性的设备。此前,我们应用超分辨率定位显微镜技术来探测简单纳米线结构周围的光子环境。这将得到进一步开发,以了解该程序中创建的更复杂设备的性能。此外,集成的原位制造和测量系统将允许在自动化系统中开发新颖的结构,为第一个目标的算法设计过程提供物理伴随。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Johlin, Eric其他文献
Machine Learning in Interpolation and Extrapolation for Nanophotonic Inverse Design.
- DOI:
10.1021/acsomega.2c04526 - 发表时间:
2022-09-20 - 期刊:
- 影响因子:4.1
- 作者:
Acharige, Didulani;Johlin, Eric - 通讯作者:
Johlin, Eric
3D multi-energy deconvolution electron microscopy
- DOI:
10.1039/c6nr07991a - 发表时间:
2017-01-14 - 期刊:
- 影响因子:6.7
- 作者:
de Goede, Michiel;Johlin, Eric;Garnett, Erik C. - 通讯作者:
Garnett, Erik C.
Johlin, Eric的其他文献
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{{ truncateString('Johlin, Eric', 18)}}的其他基金
Algorithmically Designed Optoelectronic Devices
算法设计的光电器件
- 批准号:
RGPIN-2019-05130 - 财政年份:2022
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Algorithmically Designed Optoelectronic Devices
算法设计的光电器件
- 批准号:
RGPIN-2019-05130 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
System for fabrication and characterisation of novel perovskite solar cells
新型钙钛矿太阳能电池的制造和表征系统
- 批准号:
RTI-2022-00635 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Research Tools and Instruments
Algorithmically Designed Optoelectronic Devices
算法设计的光电器件
- 批准号:
RGPIN-2019-05130 - 财政年份:2020
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Algorithmically Designed Optoelectronic Devices
算法设计的光电器件
- 批准号:
DGECR-2019-00223 - 财政年份:2019
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Launch Supplement
Algorithmic Fabrication of Nanophotonic Structures
纳米光子结构的算法制造
- 批准号:
RTI-2019-00287 - 财政年份:2018
- 资助金额:
$ 2.04万 - 项目类别:
Research Tools and Instruments
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