CAREER: Giant Tunability through Piezoelectric Resonant Acoustic Metamaterials for Radio Frequency Adaptive Integrated Electronics

职业:通过压电谐振声学超材料实现射频自适应集成电子器件的巨大可调性

基本信息

  • 批准号:
    2034948
  • 负责人:
  • 金额:
    $ 50万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-02-01 至 2026-01-31
  • 项目状态:
    未结题

项目摘要

Our well-being and livelihood, our education, our social interactions, and our knowledge of the fundamental sciences depend, more and more, on a host of advanced technologies, such as cloud-storage, edge-computing, machine learning, artificial intelligence (AI) and fifth-generation (5G) wireless communication. However, to allow these technologies to succeed, new hardware components such as more stable frequency synthesizers (FSs) based on novel materials and techniques will be critical and need to be developed. Similarly, the Internet-of-Things (IoT) has created a growing number of wireless nodes within an already congested spectrum. Therefore, new lower-power tunable front-end architectures that are capable of filtering interference signals and adapting to changing electromagnetic scenarios are needed to grant higher communication throughputs and longer battery lifetimes. To meet these challenges, this CAREER proposes to develop a new class of passive, tunable, and high-performance integrated resonant devices, namely the Piezoelectric Resonant Acoustic Metamaterials (pRAMs). Thanks to their unique, artificially produced and reconfigurable modal features, the development of pRAMs will enable new stable FSs, adaptive front ends for IoT radios and many other on-chip transducers for sensing and communication. The project team will collaborate with the Northeastern University’s Center for STEM Education to organize on-campus activities, as well as outreach visits to connect with underrepresented groups in local schools and communities. The project achievements will enrich both the undergraduate and the graduate courses that the Principal Investigator teaches on circuit theory and on advanced acoustic-based technologies for communication and sensing. The pRAMs will rely on the distinctive propagation features of acoustic metamaterials, built out of CMOS-compatible Aluminum Nitride (AlN) or Aluminum Scandium Nitride (AlScN) thin-films and embodying a periodic arrangement of magnetostrictive rods. Thanks to their unique, artificially produced and reconfigurable modal characteristics, pRAMs will surpass the material limitations that have prevented the achievement of low-loss acoustic resonant technologies, even with moderate frequency tuning ranges. This will allow the creation of new on-chip acoustic-based passives and will provide the means to achieve significantly more stable FSs for future networking components. Furthermore, pRAMs will allow the development of a new class of tunable channel-select-filters enabling future generations of IoT wireless nodes resilient to interference and consuming lower power. It is envisioned that by exploiting their new magnetosensitive behavior responsible for their large tuning range, pRAMs will likely pave the way towards a new class of chip-scale magnetometers, achieving the low limits of detection compatible to the challenging needs of critical biomagnetic and environmental applications, yet not requiring to be biased or cooled.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.
我们的福祉和生计,我们的教育,我们的社会互动以及我们对基础科学的了解越来越依赖于一系列先进技术,如云存储,边缘计算,机器学习,人工智能(AI)和第五代(5G)无线通信。然而,为了使这些技术取得成功,新的硬件组件,如基于新材料和技术的更稳定的频率合成器(FS)将是至关重要的,需要开发。 类似地,物联网(IoT)在已经拥塞的频谱内创建了越来越多的无线节点。因此,需要能够过滤干扰信号并适应不断变化的电磁场景的新的低功耗可调谐前端架构,以实现更高的通信吞吐量和更长的电池寿命。为了应对这些挑战,本职业生涯提出开发一类新的无源,可调谐和高性能的集成谐振器件,即压电谐振声学超材料(pRAM)。由于其独特的人工生产和可重新配置的模态特性,pRAM的开发将实现新的稳定FS,物联网无线电的自适应前端以及许多其他用于传感和通信的片上传感器。该项目团队将与东北大学STEM教育中心合作,组织校园活动,以及外展访问,与当地学校和社区中代表性不足的群体建立联系。该项目的成果将丰富本科生和研究生课程,主要研究员教授电路理论和先进的声学通信和传感技术。pRAM将依赖于声学超材料的独特传播特性,由CMOS兼容的氮化铝(AlN)或氮化铝钪(AlScN)薄膜制成,并体现了磁致伸缩棒的周期性排列。由于其独特的、人工制造的和可重构的模态特性,pRAM将超越阻碍低损耗声学谐振技术实现的材料限制,即使在中等频率调谐范围内也是如此。这将允许创建新的片上基于声学的无源器件,并将为未来的网络组件提供实现更稳定的FS的方法。 此外,pRAM将允许开发一类新的可调谐信道选择滤波器,使未来几代物联网无线节点能够抵御干扰并消耗更低的功率。据设想,通过利用其新的磁敏行为,负责其大的调谐范围,pRAM将可能铺平道路,以一类新的芯片级磁力计,实现低限度的检测兼容的关键生物磁性和环境应用的挑战性需求,该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识产权进行评估来支持。优点和更广泛的影响审查标准。

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)
Frequency Reprogrammable Al 0.7 Sc 0.3 N Acoustic Delay Line with up to 13.5 % Bandwidth
频率%20可重编程%20Al%200.7%20Sc%200.3%20N%20声学%20延迟%20线路%20with%20up%20to%2013.5%20%%20带宽
  • DOI:
    10.1109/eftf/ifcs54560.2022.9850681
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kaya, Onurcan;Zhao, Xuanyi;Cassella, Cristian
  • 通讯作者:
    Cassella, Cristian
An Aluminum Scandium Nitride (Al 0.64 Sc 0.36 N) Two-Dimensional-Resonant-Rods Delay Line with 7.5% Bandwidth and 1.8 dB Loss
An%20铝%20钪%20氮化物%20(Al%200.64%20Sc%200.36%20N)%20二维谐振棒%20延迟%20线%20和%207.5%%20带宽%20和%201.8%20dB%20损耗
  • DOI:
    10.1109/mems51670.2022.9699475
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kaya, Onurcan;Zhao, Xuanyi;Cassella, Cristian
  • 通讯作者:
    Cassella, Cristian
Improving Thermal Linearity and Quality Factor of Al 72 Sc 28 N Contour Mode Resonators Using Acoustic Metamaterials based Lateral Anchors
使用基于声学超材料的横向锚改善 Al 72 Sc 28 N 轮廓模式谐振器的热线性度和品质因数
An Ultra-Low Impedance 4.8 GHz Al 72 Sc 28 N Resonant Rods Resonator With a Record k t 2 of 21.2%
An%20超低%20阻抗%204.8%20GHz%20Al%2072%20Sc%2028%20N%20谐振%20Rods%20Resonator%20With%20a%20Record%20k%20t%202%20of%2021.2%
  • DOI:
    10.1109/imfw49589.2021.9642286
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhao, Xuanyi;Kaya, Onurcan;Pirro, Michele;Michetti, Giuseppe;Colombo, Luca;Cassella, Cristian
  • 通讯作者:
    Cassella, Cristian
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Cristian Cassella其他文献

Programmable threshold sensing in wireless devices using Ising dynamics
使用伊辛动力学在无线设备中进行可编程阈值感知
  • DOI:
    10.1038/s41928-025-01392-4
  • 发表时间:
    2025-06-02
  • 期刊:
  • 影响因子:
    40.900
  • 作者:
    Nicolas Casilli;Seunghwi Kim;Hussein M. E. Hussein;Ryan Tetro;Luca Colombo;Matteo Rinaldi;Philip X.-L. Feng;Andrea Alù;Cristian Cassella
  • 通讯作者:
    Cristian Cassella

Cristian Cassella的其他文献

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{{ truncateString('Cristian Cassella', 18)}}的其他基金

Collaborative Research: FET: Small: Massive Scale Computing and Optimization through On-chip ParameTric Ising MAchines (OPTIMA)
合作研究:FET:小型:通过片上 ParameTric Ising 机器进行大规模计算和优化 (OPTIMA)
  • 批准号:
    2103351
  • 财政年份:
    2021
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
Fully Integrated Parametric Filters for Extensive Phase-Noise Reduction in Low-Power RF Front-Ends and Resonant Sensing Platforms
全集成参数滤波器可在低功耗射频前端和谐振传感平台中广泛降低相位噪声
  • 批准号:
    1854573
  • 财政年份:
    2019
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant

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