Sensitive diamond-based magnetometry toward magnetoencephalography of a living animal
ORAL
Abstract
Diamond quantum magnetometer based on negatively charged nitrogen–vacancy (NV) centers has attracted much attentions for biomedical applications because of its robustness and good field sensitivity under an ambient condition. Magnetoencephalography (MEG) using a diamond quantum magnetometer is a major goal of the application. However, MEG requires a minimum detectable field of the order of picotesla and has not been realized with a diamond quantum sensor.
We develop a sensitive diamond quantum magnetometer with a dc sensitivity below 10 pT Hz-1/2 toward MEG of a living rat. The sensor is compatible with MEG and allows a minimum measurement distance of about 1 mm from the sensing region. Based on an Allan deviation analysis, we demonstrate that the sensor is stable with the remarkable sensitivity for at least 200 minutes and that a sub-picotesla field of 0.3 pT is detectable by interrogating the magnetic field for a few thousand seconds. Therefore, our sensor is capable of detecting a repetitive biomagnetic field, for example, a stimulus-evoked field, with a strength on the order of 1 pT by accumulating the signals.
We develop a sensitive diamond quantum magnetometer with a dc sensitivity below 10 pT Hz-1/2 toward MEG of a living rat. The sensor is compatible with MEG and allows a minimum measurement distance of about 1 mm from the sensing region. Based on an Allan deviation analysis, we demonstrate that the sensor is stable with the remarkable sensitivity for at least 200 minutes and that a sub-picotesla field of 0.3 pT is detectable by interrogating the magnetic field for a few thousand seconds. Therefore, our sensor is capable of detecting a repetitive biomagnetic field, for example, a stimulus-evoked field, with a strength on the order of 1 pT by accumulating the signals.
*This work was supported by the MEXT Quantum Leap Flagship Program (MEXT Q-LEAP) Grant No. JP- MXS0118067395 and JPMXS0118068379.
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Publication: N. Sekiguchi, M. Fushimi, A. Yoshimura, C. Shinei, M. Miyakawa, T. Taniguchi, T. Teraji, H. Abe, S. Onoda, T. Ohshima, M. Hatano, M. Sekino, T. Iwasaki, arXiv:2309.04093 (2023).
Presenters
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Naota Sekiguchi
- Tokyo Institute of Technology