Optimizing Data Processing for Nanodiamond Based Relaxometry

Abstract

The nitrogen‐vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of the data is well established. However, due to relatively low brightness and reproducibility it is beneficial for biological experiments to use ensembles. While increasing the number of NV centers in a nanodiamond leads to more signal, a standardized method to extract information from relaxometry experiments is still missing. This article uses T1 relaxation curves acquired at different concentrations of gadolinium ions to calibrate and optimize the entire data processing flow, from the acquired raw data to the extracted T1. In particular, a bootstrap is used to derive a signal to noise ratio (SNR) that can be quantitatively compared from one method to another. At first, T1 curves are extracted from photoluminescence pulses. This work compares integrating their signal through an optimized window as performed conventionally, to fitting a known function on it. Fitting the decaying T1 curves leads to the relevant T1 value. This work compares here the three most commonly used fit models that are, single, bi, and stretched exponential. This work finally investigates the effect of the bootstrap itself on the precision of the result as well as the use of a rolling window to increase time resolution.

Quantum Sensing of Free Radical Generation in Mitochondria of Single Heart Muscle Cells during Hypoxia and Reoxygenation

“…These pulses were interrupted by dark times (τ) from 200 ns to 10 ms. To generate relaxometry curves, we plotted the brightness in the first 0.6 μs of each pulse against the dark time (shown in Figure b). From these curves we calculate T1 using a biexponential model (equation shown in Figure b), which is further explained in previous work. , For a better signal-to-noise ratio, the pulsing sequence was repeated 10,000 times per measurement.…”

“…From these curves we calculate T1 using a biexponential model (equation shown in Figure 1 b), which is further explained in previous work. 44 , 45 For a better signal-to-noise ratio, the pulsing sequence was repeated 10,000 times per measurement.…”

Quantum Sensing of Free Radicals in Primary Human Granulosa Cells with Nanoscale Resolution

“…24 A detailed discussion of the biexponential model as well as comparison with other models can be found. 44 This measurement reveals a signal that is equivalent to T1 in conventional MRI. However, since NV centers only detect their local environment (up to a few tens of nm), this method offers nanoscale resolution.…”