钻石
Tikhonov正则化
空位缺陷
微波食品加热
微波成像
材料科学
光谱(功能分析)
光学
物理
核磁共振
数学
量子力学
数学分析
反问题
复合材料
作者
Yingfeng Li,Yue Qin,Qi Wang,Hao Guo,Jie Li,Zhonghao Li,Huan Fei Wen,Zhanfang Ma,Jun Tang,Jun Li
标识
DOI:10.1002/pssr.202200498
摘要
A machine learning‐based microwave spectrum detection method based on the nitrogen vacancy (NV) color centers in diamonds is proposed. The functional relationship between the fluorescence spectrum and standard microwave spectrum is established. The response matrix is calculated using the Tikhonov regularization technique, and an unknown microwave spectrum is reconstructed. Diamond particles with a size of only 5 × 5 μm 2 are placed in the microfluidic structures. Consequently, the frequency detection range of the microwave spectrum is from 2.892 to 6.214 GHz with a resolution of 22 kHz. The proposed research opens new paths for microwave spectrum detection and imaging at the microscopic scale.
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