Here, we demonstrate a microwave (MW) cavity interference enhancement method to image nano-defects on the surface of metal waveguide. The MW cavity interference system mainly consisted of a MW coaxial resonant cavity with a nano-probe. The MW signals have been evenly divided into two channels. One was the reference signal inputted into the MW waveguide and coupled into the MW cavity via the probe. Also, the coupling strength depends on the distance between the probe and the MW waveguide. Another one was directly inputted the MW cavity to interfere with the reference signal, and was enhanced in the cavity. Then, the surface topography of the metal waveguide was mapped by calculating the enhanced signals. In our experiment, a weak signal of ∼1 pW coupled from the waveguide can be detected by a MW cavity with the quality factor of ∼209. As a proof of application, the topography of nano-defects on the surface of metal waveguide in an MW chip has been mapped with a resolution of ∼15 nm. We have proved that this is a high-resolution, easy-to-manufacture, low-cost, and real-time online monitoring approach for online assessment and screening chips. This potentially has broad applications in the fields of chip manufacturing, chip inspection, nano-structure detection, and so on.

A new principle MOEMS accelerometer based on the magneto-optical rotation effect is developed. The design of the magnetic film integrates with the proof mass, using a magneto-optic crystal to detect the magnetic field changes induced by the external acceleration to produce the magneto-optical rotation effect. By detecting the optical rotation angle, the high precision measurement of the acceleration is realized. The structure of the accelerometer was fabricated through structural design, simulation and micro-nano processing technology. The test results show that the noise spectral density of the MOEMS accelerometer is $10.5\mu \text{g}/\surd $ Hz at 1Hz, the bias instability is $37.6\mu \text{g}$ and the output sensitivity is 330.2mV/g.

In this work, we propose a 10 μ m-scale spin-based sensor structure, which mainly consists of a nanowire (NW) ring resonator laser, nitrogen-vacancy (NV) defects in a nanodiamond (ND) and a microwave (MW) antenna. The NW laser was bent into a ring with a gap to pump the NV defects in the ND which was assembled in the gap with the diameter of ∼8 μ m. And the fluorescent light of NV defects was enhanced by the NW ring resonator about 8 times. Furthermore, the NW laser pulse was produced by the optical switch and a simple plus-sequences was designed to get the Rabi oscillation signal. Based on the Rabi oscillation, a Ramsey-type sequence was used to detect the magnetic field with the sensitivity of 83 nT √Hz ⁻¹ for our 10 μ m-scale spin-based sensor structure. It proves the spin state in our structure allows for coherent spin manipulation for more complex quantum control schemes. And our structure fulfills the fundamental requirements to develop chip-scale spin-based sensors.

We propose a method for microwave target source localization based on the diamond nitrogen vacancy color center. We use coherent population oscillation effect and modulation and demodulation techniques to achieve the detection of microwave intensity of microwave target sources, with a minimum detection intensity of 0.59 µW. Positioning of the microwave source was achieved within 50×100cm² distance from the system 1 m away using the cubic spline interpolation algorithm and minimum mean squared error. The maximum positioning error was 3.5 cm. This method provides a new, to the best of our knowledge, idea for the passive localization of microwave targets.

In this study, we established a passive direction-finding scheme based on microwave power measurement: Microwave intensity was detected using microwave-frequency proportion integration differentiation control and coherent population oscillation effect converting the change in microwave resonance peak intensity into a shift of the microwave frequency spectrum, for which the minimum microwave intensity resolution was −20 dBm. The direction angle of the microwave source was calculated using the weighted global least squares method of microwave field distribution. This lay in the 12~26 dBm microwave emission intensity range, and the measurement position was in the range of (−15°~15°). The average angle error of the angle measurement was 0.24°, and the maximum angle error was 0.48°. In this study, we established a microwave passive direction-finding scheme based on quantum precision sensing, which measures the microwave frequency, intensity, and angle in a small space and has a simple system structure, small equipment size, and low system power consumption. In this study, we provide a basis for the future application of quantum sensors in microwave direction measurements.