Luo Jiahui, Xu Zhaojie, Jin Zhenhu, Wang Mixia, Cai Xinxia, Chen Jiamin
State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
ACS Appl Mater Interfaces. 2024 Jun 19;16(24):31677-31686. doi: 10.1021/acsami.4c01148. Epub 2024 Jun 4.
Due to their compact size and exceptional sensitivity at room temperature, magnetoresistance (MR) sensors have garnered considerable interest in numerous fields, particularly in the detection of weak magnetic signals in biological systems. The "magnetrodes", integrating MR sensors with needle-shaped Si-based substrates, are designed to be inserted into the brain for local magnetic field detection. Although recent research has predominantly focused on giant magnetoresistance (GMR) sensors, tunnel magnetoresistance (TMR) sensors exhibit a significantly higher sensitivity. In this study, we introduce TMR-based magnetrodes featuring TMR sensors at both the tip and midsection of the probe, enabling detection of local magnetic fields at varied spatial positions. To enhance detectivity, we designed and fabricated magnetrodes with varied aspect ratios of the free layer, incorporating diverse junction shapes, quantities, and serial arrangements. Utilizing a custom-built magnetotransport and noise measurement system for characterization, our TMR-based magnetrode demonstrates a limit of detection (LOD) of 300pT/ at 1 kHz. This implies that neuronal spikes can be distinguished with minimal averaging, thereby facilitating the elucidation of their magnetic properties.
由于其紧凑的尺寸和在室温下的卓越灵敏度,磁阻(MR)传感器在众多领域引起了相当大的关注,特别是在生物系统中检测微弱磁信号方面。“磁电极”将MR传感器与针状硅基衬底集成在一起,设计用于插入大脑进行局部磁场检测。尽管最近的研究主要集中在巨磁阻(GMR)传感器上,但隧道磁阻(TMR)传感器表现出显著更高的灵敏度。在本研究中,我们介绍了基于TMR的磁电极,其在探头的尖端和中部均配备TMR传感器,能够检测不同空间位置的局部磁场。为了提高检测能力,我们设计并制造了具有不同自由层纵横比的磁电极,采用了多种结形状、数量和串联排列。利用定制的磁输运和噪声测量系统进行表征,我们基于TMR的磁电极在1 kHz时的检测限(LOD)为300 pT/ 。这意味着可以通过最小化平均来区分神经元尖峰,从而有助于阐明其磁特性。