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Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
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石墨烯传感器内计算设备用于植物水化监测.

Utkarsh Misra1,2, Philip Varkey1,2, Ning Liu1

  • 1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.

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概括
此摘要是机器生成的。

基于石墨烯的传感器模仿大脑突触,用于植物水分监测. 这些超低功率的叶子集成设备可以实时跟踪水含量,而不损害植物.

关键词:
生物传感器生物传感器石墨烯是一种石墨烯.在传感器内进行计算.叶子水化传感器 叶子水化传感器神经形态计算是一种神经形态计算.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 生物技术是生物技术.
  • 神经形态工程的神经形态工程

背景情况:

  • 具有人工突触行为的模拟传感器件是可扩展,节能环境监测的关键.
  • 基于石墨烯的材料为先进的传感器应用提供了独特的电子特性.

研究的目的:

  • 开发和评估基于石墨烯的,叶子门的传感器内计算设备,用于植物水分监测.
  • 为了证明设备对感应水分和类似突触的导电量调节的能力.

主要方法:

  • 用于传感器内计算的基于石墨烯的叶式晶体管的制造.
  • 利用通道导电性趋势来测量植物的水含量和离子流动性.
  • 通过电刺激为神经形态应用程序编码类似记忆的状态.

主要成果:

  • 设备表现出类似突触的导电度调制,跟踪叶子中依赖水分的离子运动.
  • 证明了线性增强,抑郁和短期记忆的保留.
  • 在Monstera的叶子上实现了超低功率运行 (23 aJ/μS写能,0.23μW读能) 和最小重量 (9毫克),而不会造成生理干扰.

结论:

  • 基于石墨烯的传感器内计算设备为实时,长期的植物水分监测提供了一个有前途的平台.
  • 将计算和传感集成到一个生物兼容平台中可以最大限度地减少数据传输,并使边缘神经形态应用成为可能.
  • 该技术为精密农业和环境传感提供了可扩展和节能的解决方案.