Oral Presentation 23rd International Society of Magnetic Resonance Conference 2023

Improving quantum heterodyne sensing techniques for NMR spectroscopy (#180)

Di Wang 1 , Sepehr Ahmadi 2 , Trent G Ralph 1 , Fernando Meneses 1 , Nikolai Dontschuk 1 , David A Simpson 1 , Liam T Hall 2
  1. School of Physics, University of Melbourne, Melbourne, Victoria, Australia
  2. CSIRO Manufacturing, Clayton, Victoria, Australia

Signal detection based on induction coils in an NMR spectrometer suffers from poor sensitivity due to size constraints, stand-off distance, and Johnson noise. In this poster, we present new directions for an alternative NMR detection method that utilises an atomic size quantum sensor in diamond, the nitrogen vacancy (NV) centre, to bypass these problems.

The NV centre has a suite of inherent NMR detection advantages that render it well suited to sensing at the nanoscale:

1. It can be polarised and read out using visible wavelength photons. In the NMR context, the Johnson noise limitation is replaced by photon shot noise, which is not temperature dependent. This also enables direct diffraction-limited widefield microscopy.

2. The diamond interface is also chemically inert and manipulatable, which allows the analyte solution to be in direct contact with the host of the atomic sized sensor, reducing interaction distance and sensing volume to the microscale and even nanoscale, it is also a platform for tethering biological targets of interests to the sensor.

These advantages can be utilised in a quantum heterodyne sensing protocol that allows the NV to perform NMR signal detection with chemical spectral resolution that is not limited by the NV coherence properties [1]. Here we detail an in situ time dependent NMR spectroscopy system using a microfluidic chip on the diamond surface, which can enable real time chemical reaction monitoring and catalysis analysis. We also present solutions to some challenges that are unique to the quantum heterodyne scheme; including improving optical collection, NV spin polarisation for high density samples, data transfer and digitisation at GHz rates and readout fidelity using machine learning for post-processing. We then discuss future avenues for this technology, including further sensitivity enhancement.

  1. Glenn, D., Bucher, D., Lee, J. et al. High-resolution magnetic resonance spectroscopy using a solid-state spin sensor. Nature 555, 351–354 (2018)