Nitrogen-vacancy characterization methodology

Optically detected magnetic resonance (ODMR) and optical T1 relaxation measurements are two important methods to assess the quality of NV centers for quantum sensing. These methods also serve as the basis of sensing methodologies enabled by NV.

Optically Detected Magnetic Resonance

Optically detected magnetic resonance (ODMR) of nanodiamonds with nitrogen-vacancy (NV) centers represents a cutting-edge technique in quantum sensing and materials characterization. NV centers, which are point defects within the diamond lattice, exhibit unique optical and magnetic properties that make them highly sensitive to their local environment. When exposed to microwave radiation, these NV centers experience changes in their fluorescence emission, which can be precisely measured to provide insights into various physical parameters.

The versatility of ODMR extends to probing the quality of the diamond crystal lattice, detecting lattice strain, and assessing environmental factors such as magnetic noise, temperature fluctuations, and external magnetic fields. This capability arises from the NV centers' robust fluorescence response and their dependence on quantum spin states. By applying continuous wave ODMR (CW-ODMR) techniques, researchers can obtain high-resolution spectra that reveal detailed information about the NV centers' spin dynamics and interactions with their surroundings. This makes ODMR nanodiamonds an invaluable tool for advanced quantum sensing applications and materials science.

A typical ODMR spectrum shown in Fig. 1 is centered around the NV zero field splitting parameter D at about 2.87 GHz. Recording the fluorescence intensity as a function of microwave frequency results in a drop in signal at this resonance frequency as compared to off-resonance frequencies. Due to strain and local charge splitting, two peak minima are observed with each being shifted from D symmetrically by a value E. Therefore, the distance between minima corresponds to 2 × E. The spectrum can be simulated by a superposition of two Lorentzian lines characterized by amplitude A, two centers D±E, and linewidth W. Using the formula: baseline – A × Σ 1 / [ 1+ ((frequency – (D±E))/W)²]. The linewidth W represents a half-width at half-peak maximum (HWHM). ODMR contrast can be extracted from the spectrum by normalization so that baseline corresponds to 100%. Then, contrast coincides with reduction of fluorescence to the minimum of normalized spectrum. More generally contrast = (baseline-minimum)/baseline 100 in %.

ODMR can be exploited for temperature and magnetic field measurements.

Fig. 1. A typical NV ODMR spectrum with labeled parameters.

Temperature Measurement

Changes in temperature alter the local symmetry of NV centers in diamond. This manifests on the ODMR spectrum as shifts in the center of the spectrum (the zero field splitting parameter, D). The D parameter depends on temperature at a coupling constant of about –80 kHz/K around 300 K. Therefore, if the temperature increases, the center of the ODMR spectrum will shift to lower frequencies, and if the temperature decreases, the center of the ODMR spectrum will shift to higher frequencies (Fig. 2). This temperature dependence can be used to measure temperature fluctuations on the order of 10 mK. Such sensitivity can be exploited for monitoring of intracellular temperature fluctuations.

Fig. 2. Shifting of the center of the NV ODMR spectra in response to changes in temperature. Temperature changes alter the zero field splitting parameter (D) away from 2.87 GHz.

Magnetic Field Measurement

Fig. 3 shows a magnetic field measurement utilizing randomly oriented NV centers in diamond nanoparticles. The magnetic field is measured through its contribution to the splitting in the ODMR spectra due to the Zeeman effect. In the absence of a magnetic field, the zero-field splitting 𝐷 defines the energy difference between the 𝑚𝑠=0 and 𝑚𝑠=±1 states. When an external magnetic field is applied, it further splits these 𝑚𝑠=±1 states through the Zeeman interaction. Due to the random orientation of the NV center axes in a distribution of nanodiamond particles (powder) with respect to the magnetic field, a distribution of splitting values is observed. The particles whose NV quantization axis is aligned with the magnetic field produce the largest splitting. The distance between extrema, indicated by the dots in the graph, is proportional to the magnetic field strength and the constant 2×γNV (56 Hz/mT).

Fig. 3. Example showing measurement of an external magnetic field applied to a distribution of nanodiamond particles with NV centers. Experimentally derived values are labeled as 𝐵meas​, while the nominally estimated values obtained from a gauss meter are denoted as 𝐵true.

T1 Relaxation

T1​ relaxation times represent the time scale over which the NV center(s) spin state returns to thermal equilibrium with its surroundings. This is also known as spin-lattice relaxation. This process is influenced by the local magnetic noise in the environment, which can be caused by unpaired electronic spins, paramagnetic impurities, or other defects in the diamond lattice. Such imperfections are often introduced during the manufacturing of diamond and the creation of NV centers. These interactions between the NV center and its noisy surroundings lead to energy dissipation, making T1 ​a valuable measure of the magnetic environment at the nanoscale. Fig. 4a and Fig. 4b shows the T1 protocol and a typical T1 decay trace, correspondingly. The T1 relaxation data acquisition protocol involves a series of light pulses structured as follows: an initialization pulse of length ∆tP is applied to establish a polarized state. This pulse is characterized by a rapid fluorescence signal jump, followed by a slower exponential build-up, typically occurring on a millisecond timescale. After a sufficiently long initialization period, typically 10 ms, a dark interval is introduced to allow for relaxation. Following the dark interval, a short detection pulse is applied with a controlled variable delay, typically ∆tD ranging from 100 μs to 200 μs. The signal is recorded during this period. The detection pulse signal undergoes processing through extrapolation fitting to a linear or exponential curve, enabling extraction of a signal value at the beginning of the pulse. This value represents a point in the T1 relaxation time at the specific detection pulse delay time. After a brief dark reset time, the sequence is repeated either for averaging purposes with the same delay time or to acquire the next relaxation point at successively increasing delay increments. There is a choice between keeping the reset time constant or the repetition period (T) constant between relaxation points. Keeping the reset time constant enables faster data collection by dynamically adjusting the repetition time short enough to accommodate the current delay sequence. Conversely, maintaining a constant repetition time requires accommodating all pulse sequences and is limited by the longest delay time. While keeping the repetition time constant necessitates long reset times even for short delays, it is the best approach to ensure that the initialization states reach the same level of polarization for each sequence. This method is often the best way to prevent unwanted baseline drifts in the relaxation curve.

A typical relaxation curve follows approximately an exponential decay dependence of fluorescence signal on delay time between initialization and detection pulses. The curve can be modeled using a stretched exponential function of the form A × exp[-(delay/T1)ᵖ] + offset. Here, offset is the fluorescence signal level in the relaxed state, i.e., delay → ∞, A is the maximum increase of fluorescence level due to light polarization at the end of the initialization pulse, i.e., at the delay time zero, T1 is the relaxation constant, and ρ is the stretching exponent. Parameters are obtained by fitting a series of discrete points. It is advantageous to collect these data points with a parametric sampling scheme, where distance is kept constant along the relaxation curve instead of equidistant sampling on the delay axes. Such sampling provides a more accurate representation of the decay process and saves data acquisition time. If data are normalized so that the signal maximum at delay zero equals 100%, then parameter A equals the T1 contrast. More generally T1 contrast = A / (A + offset) x 100 in %.

Fig. 4. Schematic of T1 relaxation pulse protocol (a) and a typical T1 relaxation decay trace demarked with characteristic parameters (b)