Ideal memristor based on the spin liquid state in magnetic heterostructures
基于磁性异质结构自旋液态的理想忆阻器
基本信息
- 批准号:2005786
- 负责人:
- 金额:$ 34.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-07-01 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Computers operating with digital representation of information and Boolean logic have revolutionized science and technology. However, they remain far inferior to human brain due to their inability to adapt and to process massive amounts of imprecise information. These capabilities can be accomplished with neuromorphic computing, which can be efficiently implemented at the hardware level by utilizing memristors - electronic devices whose resistance depends on their electrical history. The existing memristors operate mostly like on/off switches, lacking the ability to continuously vary the resistance in response to electric stimuli required for neuromorphic applications. These devices commonly rely on the physical motion of atoms, and as a result lack durability and reproducibility. The proposed project will develop a new class of memristors based on the special magnetic properties of ferromagnet/antiferromagnet bilayers. The operation of the proposed devices will rely on the magnetic frustration at the interfaces between ferromagnets and antiferromagnets, resulting from the incompatible magnetic ordering of the two materials, which will lead to the formation of a viscous spin liquid state in the antiferromagnets. The project will explore the most suitable materials and geometries, electronic mechanisms enabling device operation, and device functionality at nanoscale. The proposed research will be integrated with STEM education through the development of a comprehensive undergraduate Materials and Engineering Physics program, which will include a hands-on freshman seminar and a state-of-art research training course for undergraduate students. The plan is also to organize a Science club at the local elementary school.A theoretically envisioned ideal memristor is an electronic device whose resistance is proportional to the total charge that passes through it, with the coefficient of proportionality known as memristance. The proposed project will experimentally realize ideal memristor nanodevices, by utilizing bilayers of low-anisotropy ferromagnets, such as Permalloy, and thin films of antiferromagnets such as NiO, CoO, or Fe50Mn50. A spin liquid state is expected to be formed in the antiferromagnets, due to the magnetic frustration associated with the random exchange interaction at the magnetic interface. The proposed project will utilize a combination of material and heterostructure engineering, nanofabrication, measurements of time-domain magnetic dynamics and transverse ac susceptibility, to address questions related to physical mechanisms of device operation, and device design. The proposed research will explore the possibility to engineer frustrated thin-film magnetic heterostructures that exhibit a spin liquid state with a well-defined and tunable viscosity, resulting in ideal memristive functionality with controlled memristance. Additionally, the project will identify and characterize the magnetoelectronic mechanisms that can facilitate writing, reading, and resetting of the memristive devices based on viscous spin liquids. The relevant length scales for the memristive properties will be established, to determine whether the proposed devices are scalable to the technologically relevant nanoscale dimensions. By addressing these questions, the proposed project will provide a transformative contribution to the research and development of memristive devices characterized by high-endurance, scalability, and tunable memristive properties, which will facilitate the implementation of efficient neuromorphic networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
以数字表示信息和布尔逻辑操作的计算机已经彻底改变了科学和技术。然而,由于它们无法适应和处理大量不精确的信息,它们仍然远远不如人脑。这些能力可以通过神经形态计算来实现,神经形态计算可以通过利用忆阻器在硬件级别有效地实现,忆阻器是电阻取决于其电历史的电子设备。现有的忆阻器大多像开/关开关一样操作,缺乏响应于神经形态应用所需的电刺激而连续改变电阻的能力。这些设备通常依赖于原子的物理运动,因此缺乏耐用性和可重复性。该项目将基于铁磁/反铁磁双层膜的特殊磁性开发一类新的忆阻器。所提出的设备的操作将依赖于铁磁体和反铁磁体之间的界面处的磁阻挫,这是由两种材料的不相容的磁有序引起的,这将导致在反铁磁体中形成粘性自旋液体状态。该项目将探索最合适的材料和几何形状,使设备操作的电子机制,以及纳米级的设备功能。拟议的研究将通过开发一个全面的本科材料和工程物理课程与STEM教育相结合,该课程将包括一个动手的新生研讨会和一个面向本科生的最先进的研究培训课程。该计划还将在当地小学组织一个科学俱乐部。理论上设想的理想忆阻器是一种电子器件,其电阻与通过它的总电荷成比例,比例系数称为忆阻。拟议的项目将通过利用双层低各向异性铁磁体(如坡莫合金)和反铁磁体薄膜(如NiO、CoO或Fe 50 Mn 50),在实验上实现理想的忆阻器纳米器件。自旋液体状态预计将形成在反铁磁体,由于与随机交换相互作用在磁界面的磁挫折。拟议的项目将利用材料和异质结构工程,纳米纤维,时域磁动力学和横向交流磁化率的测量相结合,以解决与设备操作的物理机制和设备设计相关的问题。拟议的研究将探索工程挫败薄膜磁性异质结构的可能性,这些异质结构表现出具有明确定义和可调粘度的自旋液体状态,从而实现具有受控忆阻的理想忆阻功能。此外,该项目将确定和表征磁电子机制,可以促进写,阅读,和基于粘性自旋液体的忆阻器件的复位。将建立忆阻特性的相关长度尺度,以确定所提出的器件是否可扩展到技术相关的纳米尺度。 通过解决这些问题,拟议的项目将为忆阻器件的研究和开发提供变革性的贡献,其特点是高耐久性,可扩展性和可调忆阻特性,该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查进行评估,被认为值得支持的搜索.
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Orbital correlations in ultrathin films of late transition metals
后过渡金属超薄膜中的轨道相关性
- DOI:10.1103/physrevmaterials.7.014404
- 发表时间:2023
- 期刊:
- 影响因子:3.4
- 作者:Ivanov, Sergei;Peacock, Joshua;Urazhdin, Sergei
- 通讯作者:Urazhdin, Sergei
Effects of spin-orbit interaction and electron correlations in strontium titanate
钛酸锶中自旋轨道相互作用和电子相关性的影响
- DOI:10.1103/physrevb.106.224519
- 发表时间:2022
- 期刊:
- 影响因子:3.7
- 作者:Urazhdin, Sergei;Towsif, Ekram;Mitrofanov, Alexander
- 通讯作者:Mitrofanov, Alexander
Exchange bias without directional anisotropy in permalloy/CoO bilayers
- DOI:10.1103/physrevb.104.144413
- 发表时间:2021-10-14
- 期刊:
- 影响因子:3.7
- 作者:Mitrofanov, Alexander;Chen, Guanxiong;Urazhdin, Sergei
- 通讯作者:Urazhdin, Sergei
Memristive functionality based on viscous magnetization dynamics
基于粘性磁化动力学的忆阻功能
- DOI:10.1063/5.0092641
- 发表时间:2022
- 期刊:
- 影响因子:3.2
- 作者:Ivanov, Sergei;Urazhdin, Sergei
- 通讯作者:Urazhdin, Sergei
Ultrafast electron dynamics in platinum and gold thin films driven by optical and terahertz fields
- DOI:10.1063/5.0068086
- 发表时间:2021-06
- 期刊:
- 影响因子:4
- 作者:V. Unikandanunni;F. Rigoni;M. Hoffmann;P. Vavassori;S. Urazhdin;S. Bonetti
- 通讯作者:V. Unikandanunni;F. Rigoni;M. Hoffmann;P. Vavassori;S. Urazhdin;S. Bonetti
{{
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 }}
Sergei Urazhdin其他文献
Stability criterion for critical points of a model in micromagnetics
- DOI:
10.1134/s0081543812060168 - 发表时间:
2012-10-12 - 期刊:
- 影响因子:0.400
- 作者:
Lydia Novozhilova;Sergei Urazhdin - 通讯作者:
Sergei Urazhdin
Dynamical Coupling Between Ferromagnets Due to Spin Transfer Torque
- DOI:
10.1103/physrevb.78.060405 - 发表时间:
2008-02 - 期刊:
- 影响因子:0
- 作者:
Sergei Urazhdin - 通讯作者:
Sergei Urazhdin
Sergei Urazhdin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 }}
{{ truncateString('Sergei Urazhdin', 18)}}的其他基金
Thermodynamics of nanomagnetic devices driven by spin currents
自旋电流驱动的纳米磁性器件的热力学
- 批准号:
1804198 - 财政年份:2018
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
Active microwave nanodevices based on nonlocal spin injection
基于非局域自旋注入的有源微波纳米器件
- 批准号:
1503878 - 财政年份:2015
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
Electrical control of nontrivial textures in magnetic nanostructures
磁性纳米结构中重要纹理的电控制
- 批准号:
1504449 - 财政年份:2015
- 资助金额:
$ 34.5万 - 项目类别:
Continuing Grant
Collaborative Research: Microwave Auto-Oscillators Driven by Pure Spin Currents
合作研究:纯自旋电流驱动的微波自动振荡器
- 批准号:
1305586 - 财政年份:2013
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
Development of tunable nanomagnetic microwave oscillators and circuits
可调谐纳米磁性微波振荡器和电路的开发
- 批准号:
1218419 - 财政年份:2011
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
CAREER: Current-Induced Effects in Magnetic Nanostructures and Development of Science Education
职业:磁性纳米结构的电流感应效应和科学教育的发展
- 批准号:
1218414 - 财政年份:2011
- 资助金额:
$ 34.5万 - 项目类别:
Continuing Grant
Development of tunable nanomagnetic microwave oscillators and circuits
可调谐纳米磁性微波振荡器和电路的开发
- 批准号:
0967195 - 财政年份:2010
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
CAREER: Current-Induced Effects in Magnetic Nanostructures and Development of Science Education
职业:磁性纳米结构的电流感应效应和科学教育的发展
- 批准号:
0747609 - 财政年份:2008
- 资助金额:
$ 34.5万 - 项目类别:
Continuing Grant
相似海外基金
ERI: Memristor-based Neuromorphic Circuit Design for Closed-Loop Deep Brain Stimulation
ERI:基于忆阻器的闭环深部脑刺激神经形态电路设计
- 批准号:
2301589 - 财政年份:2023
- 资助金额:
$ 34.5万 - 项目类别:
Standard Grant
Novel Filament-based Memristor Devices
新型基于灯丝的忆阻器器件
- 批准号:
572682-2022 - 财政年份:2022
- 资助金额:
$ 34.5万 - 项目类别:
University Undergraduate Student Research Awards
Memristor-based Architectures for Neuromorphic Computing
用于神经形态计算的基于忆阻器的架构
- 批准号:
RGPIN-2020-06613 - 财政年份:2022
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual
Enabling large-scale silicon spin qubit platform using memristor-based neuromorphic circuits for quantum dots auto-tuning
使用基于忆阻器的神经形态电路实现量子点自动调节的大规模硅自旋量子位平台
- 批准号:
RGPIN-2019-06183 - 财政年份:2022
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual
Enabling large-scale silicon spin qubit platform using memristor-based neuromorphic circuits for quantum dots auto-tuning
使用基于忆阻器的神经形态电路实现量子点自动调节的大规模硅自旋量子位平台
- 批准号:
RGPIN-2019-06183 - 财政年份:2021
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual
Memristor-based Architectures for Neuromorphic Computing
用于神经形态计算的基于忆阻器的架构
- 批准号:
RGPIN-2020-06613 - 财政年份:2021
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual
Memristor-based neural interface for massively parallel recording and modulation of neural activity
基于忆阻器的神经接口,用于大规模并行记录和调节神经活动
- 批准号:
2897911 - 财政年份:2021
- 资助金额:
$ 34.5万 - 项目类别:
Studentship
Enabling large-scale silicon spin qubit platform using memristor-based neuromorphic circuits for quantum dots auto-tuning
使用基于忆阻器的神经形态电路实现量子点自动调节的大规模硅自旋量子位平台
- 批准号:
RGPIN-2019-06183 - 财政年份:2020
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual
Advanced Memristor Devices Based on Nitrides
基于氮化物的先进忆阻器器件
- 批准号:
560719-2020 - 财政年份:2020
- 资助金额:
$ 34.5万 - 项目类别:
University Undergraduate Student Research Awards
Memristor-based Architectures for Neuromorphic Computing
用于神经形态计算的基于忆阻器的架构
- 批准号:
RGPIN-2020-06613 - 财政年份:2020
- 资助金额:
$ 34.5万 - 项目类别:
Discovery Grants Program - Individual