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Three-dimensional nanoscale structure of novel nitride materials and devices

Three-dimensional nanoscale structure of novel nitride materials and devices
新型氮化物材料与器件的三维纳米结构
批准号:
2278538
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
翻译
剑桥氮化镓中心正在开发一系列具有复杂三维结构的光子器件。其中包括用于限制光和探索光与物质相互作用的微腔和纳米腔。此外,我们正在开发纳米多孔氮化镓,并将其纳入一系列光子结构。为了使这些光子器件的发展取得成功,我们必须充分了解这些材料和器件在纳米尺度上的三维(3D)结构,这是一个令人兴奋和具有挑战性的显微镜问题。结构见解将被纳入材料和器件特性模型中,以了解哪些结构因素增强或限制了光子器件的性能,并推动改进制造技术的未来发展。博士项目的总体目标是开发和应用显微镜技术,允许纳米结构半导体样品的三维表征,不仅包括介孔半导体,还包括光刻定义的光子和电子微观和纳米结构,如光子晶体。电子断层扫描(在透射电子显微镜)和切片和视图成像(在聚焦离子束扫描电子显微镜)将探讨。三维成像数据将与有限元模型相结合,以预测观察到的纳米结构对材料性能和/或器件性能的影响。
英文摘要
The Cambridge Centre for Gallium Nitride is developing a range of photonic devices which exhibit complex three-dimensional structure. These include micro- and nano-cavities for the confinement of light and the exploration of light matter interactions. Furthermore, we are developing nanoporous gallium nitride and incorporating it into a range of photonic architectures.For these photonic device developments to succeed, it is vital that we fully understand the three-dimensional (3D) structure of these materials and devices at the nanoscale, and this represents an exciting and challenging microscopy problem. Structural insights will be incorporated into models of materials and device properties to understand what structural factors enhance or limit the performance of photonic devices and to drive the future development of improved fabrication techniques.The overall aim of the PhD project is to develop and apply microscopy techniques which allow the three-dimensional characterisation of nanostructured semiconductor samples including not only meso-porous semiconductors, but also lithographically defined photonic and electronic micro- and nanostructures, such as photonic crystals. Both electron tomography (in the transmission electron microscope) and slice-and-view imaging (in the focussed ion beam scanning electron microscope) will be explored. Three-dimensional imaging data will be combined with finite element modelling to predict the impact of the observed nanostructure on materials properties and/or device performance.
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