Neuromorphic devices based on 2D layered materials heterostructures

基于二维层状材料异质结构的神经形态装置

基本信息

  • 批准号:
    2570030
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Studentship
  • 财政年份:
    2021
  • 资助国家:
    英国
  • 起止时间:
    2021 至 无数据
  • 项目状态:
    未结题

项目摘要

Artificial neural networks (ANNs) are at the core of artificial intelligence applications. However, ANN are usually implemented by "conventional" von Neumann architectures, where memory and logic are separated, requiring continuous data exchange which causes processing bottlenecks and large power consumption. An alternative approach to ANN is provided by neuromorphic computing, which takes inspiration from the human brain and is based on artificial neurons and synapses, where memory and logic are co-located. This PhD project focusses on design, simulation and testing of novel energy-efficient neuromorphic devices based on heterostructure formed by combining different 2D/layered materials (2DLM) such as graphene and transition metal dichalcogenides. With tens of 2DLM experimentally available and over 2,000 theoretically predicted and the possibility of stacking them in arbitrary order and mutual angle, such materials offer unprecedented flexibility in terms of combination of materials, atomically-precise interfaces and defect engineering. The project involves design, (nano)fabrication and electrical testing of different neuromorphic devices. The experimental activity will be completed by finite-element simulations.The project will explore different vertical device structures based on 2DLM heterostructures to be used for energy-efficient neuromorphic computing. Building on recent results on thermal and plasma oxidation of 2DLM such as HfS2, the project will initially focus on the investigation of two-dimensional insulators, aiming to understand of the oxidation process, the properties of the so-formed oxide and semiconductor/oxide interfaces. The focus will then shift towards device design and fabrication, and different structures and combinations of materials will be explored and the performance of individual devices will be tested and optimized. Finally, several devices will be combined to form arrays, which will be used to perform basic machine learning tasks such as pattern recognition or classification. Throughout the project, particular attention will be paid to scalability of materials and devices, as well as integration with existing silicon-based ICT technology. The project will be both experimental and computational. The experimental part of the project will consist in the fabrication of 2DLM heterostructures by using a state of the art, purposely-designed glovebox system which allows precise stacking of different 2DLM in an inert atmosphere, as well as control of interface contaminations, high-temperature annealing, precise introduction of defects and plasma etching. Fabrication of the neuromorphic devices will be completed using cleanroom-based microfabrication (optical and electron beam lithography, reactive ion etching, metal evaporation, etc). Device performance will be tested using a probe station coupled with an ensemble of testing equipment (source/measure units, pulse generators, impedance analysers, vector network analysers, oscilloscopes, lock-in amplifiers, etc.). Device testing will include DC sweeps, voltage pulses, retention and endurance tests. The computational part of the project will consist of finite-element simulations, achieved mainly via a Technology Computer Aided Design (TCAD) tool, Synopsys Sentaurus. TCAD simulations will be complemented by Comsol Multiphysics and CST Microwave Studio when needed. The project is well aligned to different EPSRC areas, encompassing multiple themes. In particular, the project is aligned with the "Artificial intelligence technologies", "Microelectronic device technology" and "Graphene and carbon technology" areas. The research will be conducted in close collaboration with Prof. Kenyon and Dr Mehonic (UCL Electronic and Electrical Engineering Dpt), leading experts in resistance-switching devices and founders and CSO/CTO of the "IntrinSic" spin-out company, which designs and manufactures state of the art silicon resistive random-access memories. The pr
人工神经网络(ANN)是人工智能应用的核心。然而,人工神经网络通常是由“传统的”冯诺依曼架构,其中存储器和逻辑是分离的,需要连续的数据交换,导致处理瓶颈和大功耗。神经形态计算提供了人工神经网络的另一种方法,它从人脑中汲取灵感,并基于人工神经元和突触,其中记忆和逻辑位于同一位置。这个博士项目的重点是设计,模拟和测试基于异质结构的新型节能神经形态设备,该异质结构通过结合不同的2D/层状材料(2DLM),如石墨烯和过渡金属二硫属化物形成。实验上有数十种2DLM,理论上预测有2,000多种,并且可以以任意顺序和相互角度堆叠它们,这些材料在材料组合,原子精确界面和缺陷工程方面提供了前所未有的灵活性。该项目涉及不同神经形态设备的设计,(纳米)制造和电气测试。实验活动将通过有限元模拟完成。该项目将探索基于2DLM异质结构的不同垂直器件结构,用于节能神经形态计算。基于2DLM(如HfS 2)的热氧化和等离子体氧化的最新结果,该项目最初将专注于二维绝缘体的研究,旨在了解氧化过程,因此形成的氧化物和半导体/氧化物界面的特性。然后,重点将转向器件设计和制造,并将探索不同的结构和材料组合,并测试和优化单个器件的性能。最后,几个设备将组合成阵列,用于执行基本的机器学习任务,如模式识别或分类。在整个项目中,将特别关注材料和设备的可扩展性,以及与现有硅基ICT技术的集成。该项目将是实验和计算。该项目的实验部分将包括通过使用最先进的,精心设计的手套箱系统制造2DLM异质结构,该系统允许在惰性气氛中精确堆叠不同的2DLM,以及控制界面污染,高温退火,精确引入缺陷和等离子体蚀刻。将使用基于洁净室的微加工(光学和电子束光刻、反应离子蚀刻、金属蒸发等)完成神经形态设备的制造。将使用探针台和一系列测试设备(源/测量单元、脉冲发生器、阻抗分析仪、矢量网络分析仪、示波器、锁定放大器等)对器械性能进行测试。器械测试将包括直流扫描、电压脉冲、保持力和耐久性测试。该项目的计算部分将包括有限元模拟,主要通过技术计算机辅助设计(TCAD)工具Synopsys Sentaurus实现。TCAD模拟将在需要时由Comsol Multiphysics和CST Microwave Studio进行补充。该项目与EPSRC的不同领域保持一致,涵盖多个主题。特别是,该项目与“人工智能技术”,“微电子器件技术”和“石墨烯和碳技术”领域保持一致。该研究将与Kenyon教授和Mehonic博士(UCL电子和电气工程Dpt)密切合作,他们是电阻开关器件的领先专家,也是“IntrinSic”分拆公司的创始人和CSO/CTO,该公司设计和制造最先进的硅电阻随机存取存储器。公关

项目成果

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其他文献

Internet-administered, low-intensity cognitive behavioral therapy for parents of children treated for cancer: A feasibility trial (ENGAGE).
针对癌症儿童父母的互联网管理、低强度认知行为疗法:可行性试验 (ENGAGE)。
  • DOI:
    10.1002/cam4.5377
  • 发表时间:
    2023-03
  • 期刊:
  • 影响因子:
    4
  • 作者:
  • 通讯作者:
Differences in child and adolescent exposure to unhealthy food and beverage advertising on television in a self-regulatory environment.
在自我监管的环境中,儿童和青少年在电视上接触不健康食品和饮料广告的情况存在差异。
  • DOI:
    10.1186/s12889-023-15027-w
  • 发表时间:
    2023-03-23
  • 期刊:
  • 影响因子:
    4.5
  • 作者:
  • 通讯作者:
The association between rheumatoid arthritis and reduced estimated cardiorespiratory fitness is mediated by physical symptoms and negative emotions: a cross-sectional study.
类风湿性关节炎与估计心肺健康降低之间的关联是由身体症状和负面情绪介导的:一项横断面研究。
  • DOI:
    10.1007/s10067-023-06584-x
  • 发表时间:
    2023-07
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
  • 通讯作者:
ElasticBLAST: accelerating sequence search via cloud computing.
ElasticBLAST:通过云计算加速序列搜索。
  • DOI:
    10.1186/s12859-023-05245-9
  • 发表时间:
    2023-03-26
  • 期刊:
  • 影响因子:
    3
  • 作者:
  • 通讯作者:
Amplified EQCM-D detection of extracellular vesicles using 2D gold nanostructured arrays fabricated by block copolymer self-assembly.
使用通过嵌段共聚物自组装制造的 2D 金纳米结构阵列放大 EQCM-D 检测细胞外囊泡。
  • DOI:
    10.1039/d2nh00424k
  • 发表时间:
    2023-03-27
  • 期刊:
  • 影响因子:
    9.7
  • 作者:
  • 通讯作者:

的其他文献

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{{ truncateString('', 18)}}的其他基金

An implantable biosensor microsystem for real-time measurement of circulating biomarkers
用于实时测量循环生物标志物的植入式生物传感器微系统
  • 批准号:
    2901954
  • 财政年份:
    2028
  • 资助金额:
    --
  • 项目类别:
    Studentship
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利用人类肠道微生物群的多糖分解能力来开发环境可持续的洗碗解决方案
  • 批准号:
    2896097
  • 财政年份:
    2027
  • 资助金额:
    --
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可以在颗粒材料中游动的机器人
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  • 资助金额:
    --
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    Studentship
Likelihood and impact of severe space weather events on the resilience of nuclear power and safeguards monitoring.
严重空间天气事件对核电和保障监督的恢复力的可能性和影响。
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    2908918
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
Proton, alpha and gamma irradiation assisted stress corrosion cracking: understanding the fuel-stainless steel interface
质子、α 和 γ 辐照辅助应力腐蚀开裂:了解燃料-不锈钢界面
  • 批准号:
    2908693
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
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Field Assisted Sintering of Nuclear Fuel Simulants
核燃料模拟物的现场辅助烧结
  • 批准号:
    2908917
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
Assessment of new fatigue capable titanium alloys for aerospace applications
评估用于航空航天应用的新型抗疲劳钛合金
  • 批准号:
    2879438
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
Developing a 3D printed skin model using a Dextran - Collagen hydrogel to analyse the cellular and epigenetic effects of interleukin-17 inhibitors in
使用右旋糖酐-胶原蛋白水凝胶开发 3D 打印皮肤模型,以分析白细胞介素 17 抑制剂的细胞和表观遗传效应
  • 批准号:
    2890513
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
CDT year 1 so TBC in Oct 2024
CDT 第 1 年,预计 2024 年 10 月
  • 批准号:
    2879865
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
Understanding the interplay between the gut microbiome, behavior and urbanisation in wild birds
了解野生鸟类肠道微生物组、行为和城市化之间的相互作用
  • 批准号:
    2876993
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship

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