Utilising NV based quantum sensing for velocimetry at the nanoscale

Daniel Cohen*, Ramil Nigmatullin, Oded Kenneth, Fedor Jelezko, Maxim Khodas, Alex Retzker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Nitrogen-Vacancy (NV) centers in diamonds have been shown in recent years to be excellent magnetometers on the nanoscale. One of the recent applications of the quantum sensor is retrieving the Nuclear Magnetic Resonance (NMR) spectrum of a minute sample, whose net polarization is well below the Signal-to-Noise Ratio (SNR) of classic devices. The information in the magnetic noise of diffusing particles has also been shown in decoherence spectroscopy approaches to provide a method for measuring different physical parameters. Similar noise is induced on the NV center by a flowing liquid. However, when the noise created by diffusion effects is more dominant than the noise of the drift, it is unclear whether the velocity can be efficiently estimated. Here we propose a non-intrusive setup for measuring the drift velocity near the surface of a flow channel based on magnetic field quantum sensing using NV centers. We provide a detailed analysis of the sensitivity for different measurement protocols, and we show that our nanoscale velocimetry scheme outperforms current fluorescence based approaches even when diffusion noise is dominant. Our scheme can be applied for the investigation of microfluidic channels, where the drift velocity is usually low and the flow properties are currently unclear. A better understanding of these properties is essential for the future development of microfluidic and nanofluidic infrastructures.

Original languageEnglish
Article number5298
JournalScientific Reports
Volume10
Issue number1
DOIs
StatePublished - 1 Dec 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

Fingerprint

Dive into the research topics of 'Utilising NV based quantum sensing for velocimetry at the nanoscale'. Together they form a unique fingerprint.

Cite this