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IEEE Sensors Journal

Ultra-Sensitive Two-Dimensional Integrated Quantum Thermometer Module Based on the Optical Detection of Magnetic Resonance Using Nitrogen-Vacancy Centers

Ranran Xü, Zichuan Zhang, Baixi Du, Yupeng Zhang, Kun Huang, Lin Cheng

Published May 18, 2022• 15 citations
Publisher

Abstract

In this paper, we propose a two-dimensional thermometer module based on the Nitrogen-Vacancy (NV) centers in diamonds. The thermometer integrates four modules on one Printed Circuit Board (PCB) including a laser module and a corresponding voltage regulator circuit, a microwave module, a focusing module, and an acquisition module, and it has a constructed area of 6.4${\textit {cm}}^{{2}}$. In the process of integrating equipment, we made a signal amplifier module to improve the signal-to-noise ratio (SNR). Through the amplifier module, we realize a$\sim 25$-fold increase in the fluorescence, and it successfully improved the SNR by$\sim 8.9$-fold. Fixed Frequency Optical Detection of Magnetic Resonance (FF-ODMR) measures the relationship between temperature (T) and photoluminescence (PL) by scanning the temperature field at 2.84GHz. Which is the most direct display of the thermometer. We developed an algorithm for analyzing the thermometer sensitivity based on PL the SNR analysis. The thermometer temperature-field sensitivity of approximately${19}\textit {nk}/{\textit {Hz}}^{{1}/{2}}$.

DOI
10.1109/jsen.2022.3176355

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In this paper, we propose a two-dimensional thermometer module based on the Nitrogen-Vacancy (NV) centers in diamonds. The thermometer integrates four modules on one Printed Circuit Board (PCB) including a laser module and a corresponding voltage regulator circuit, a microwave module, a focusing module, and an acquisition module, and it has a constructed area of 6.4cm2{\textit {cm}}^{{2}}cm2. In the process of integrating equipment, we made a signal amplifier module to improve the signal-to-noise ratio (SNR). Through the amplifier module, we realize a∼25\sim 25∼25-fold increase in the fluorescence, and it successfully improved the SNR by∼8.9\sim 8.9∼8.9-fold. Fixed Frequency Optical Detection of Magnetic Resonance (FF-ODMR) measures the relationship between temperature (T) and photoluminescence (PL) by scanning the temperature field at 2.84GHz. Which is the most direct display of the thermometer. We developed an algorithm for analyzing the thermometer sensitivity based on PL the SNR analysis. The thermometer temperature-field sensitivity of approximately19nk/Hz1/2{19}\textit {nk}/{\textit {Hz}}^{{1}/{2}}19nk/Hz1/2.
The nitrogen-vacancy center in diamond has been broadly applied in quantum sensing since it is sensitive to different physical quantities. Meanwhile, it is difficult to isolate disturbances from unwanted physical quantities in practical applications. Here, we present a fiber-based quantum thermometer by tracking the sharp-dip in the zero-field optically detected magnetic resonance spectrum in a high-density nitrogen-vacancy ensemble. Such a scheme can not only significantly isolate the magnetic field and microwave power drift but also improve the temperature sensitivity. Thanks to its simplicity and compatibility in implementation and robustness, this quantum thermometer is then applied to the surface temperature imaging of an electronic chip with a sensitivity of 18mK/Hz. It thus paves the way to high sensitive temperature measurements in ambiguous environments.
Abstract We demonstrate a method for thermal detection that is the sensitivity 6.2 mK Hz −1 2 , which uses the frequency lock closed-loop scheme to track Zeeman-split resonance of nitrogen-vacancy (NV) centers in diamond. The NV diamond surface acts as a temperature measurement sensor to transfer the temperature variation as D ( T ) parameter change to lead to the movement of the energy levels to detect the temperature. By frequency modulation technology and closed-loop feedback locking technology, automatic temperature detection and step signal reading are realized, with a resolution of 7.6 mK. It is found that the closed-loop output is basically unchanged, while the open-loop output has an error signal proportional to the laser fluctuation. The closed-loop feedback technique can improve the stability and resolution of the system and provides a method for measuring the actual temperature detection. Such a demonstration marks a vital advance in transitioning the NV thermometer from a laboratory system to a functional device for detecting temperature fields in a practical environment.
Abstract We developed a compact, portable quantum sensor module for pulsed measurements using diamond nitrogen-vacancy (NV) centers, an excitation laser diode of 3 mW and a microwave source of 15 dBm. This module allowed the evaluation of ensemble diamond NV centers for measuring magnetic fields by continuous wave— optically detected magnetic resonance (ODMR), Rabi oscillation, pulsed ODMR, Ramsey measurement and spin-echo measurement. The sensitivity through pulsed measurements reached 40 nT/ Hz at 1 Hz, which achieved higher sensitivity by one order, especially at a frequency around 1 Hz compared with previously reported compact modules using diamond NV centers.
Nitrogen-vacancy (NV) centers in diamond are a versatile quantum sensing platform for high sensitivity measurements of magnetic fields, temperature and strain with nanoscale spatial resolution. A common bottleneck is the analysis of optically detected magnetic resonance (ODMR) spectra, where target quantities are encoded in resonance features. Conventional nonlinear fitting is often computationally expensive, sensitive to initialization, and prone to failure at low signal-to-noise ratio (SNR). Here we introduce a robust, efficient machine learning (ML) framework for real-time ODMR analysis based on a one-dimensional convolutional neural network (1D-CNN). The model performs direct parameter inference without initial guesses or iterative optimization, and is naturally parallelizable on graphics processing units (GPU) for high-throughput processing. We validate the approach on both synthetic and experimental datasets, showing improved throughput, accuracy and robustness than standard nonlinear fitting, with the largest gains in the low-SNR regime. We further validate our methods in two representative sensing applications: diagnosing intracellular temperature changes using nanodiamond probes and widefield magnetic imaging of superconducting vortices in a high-temperature superconductor. This deep-learning inference framework enables fast and reliable extraction of physical parameters from complex ODMR data and provides a scalable route to real-time quantum sensing and imaging.
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In this work we present a compact and portable tabletop magnetometer that utilizes negatively charged nitrogen-vacancy (NV) centers in diamond. The magnetometer is operated using a dual microwave resonance detection approach in combination with an optically detected magnetic resonance (ODMR) technique (mitigating drifts in results due to changes of the diamond temperature), capable of simultaneously exciting and registering two ODMR transitions. The experimentally measured magnetic field noise-floor is ≈2.3 nTHz\approx 2.3~\textrm{nT}\sqrt{\textrm{Hz}}≈2.3 nTHz​ while the calculated shot-noise-limited magnetic field sensitivity is ≈585 pTHz\approx 585~\textrm{pT}\sqrt{\textrm{Hz}}≈585 pTHz​ when excited with a continuous wave laser at 0.5~W. These results pave the way for realizing a simple set-up magnetometer for precise single axis magnetic field measurements for example for accurate electric current measurements for stabilization purposes and magnetic communication applications.