1
Return

Temperature field ultrafast detection and identification quantum sensor based on diamond array

delete2025-12-10
delete0
delete
OA
AI
W
Wei Gao
J
Jinyu Tai
Z
Zhiqiang Xiang
Y
Yunbo Shi
李欣 (Xin Li)
H
Huan Fei Wen
F
Fēi Dèng
Z
Zhonghao Li
Z
Zongmin Ma
H
Hailong Wang
张蔚暄 (Weixuan Zhang)
Z
Zheng Lou
H
Hao Guo *
汤钧 (Jun Tang) *
王丽丽 cover
王丽丽 (Lili Wang) *
刘俊 (Jun Liu) *
DOI:10.1038/s41378-025-01076-1delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Ultrafast temperature field detection and identification is crucial for applications ranging from environmental sensing and biomedical monitoring to thermal management in advanced energy systems. Conventional temperature sensors—comprising discrete sensing arrays, data storage units, and external processors—suffer from high latency due to slow sensor response, repeated analog-to-digital conversions, and extensive data transmission inherent to von Neumann architectures. Here, we report a diamond array-based quantum sensor that integrates temperature sensing and real-time processing within a unified in-sensor computing (ISC) architecture. Exploiting the strong linear correlation between temperature and the zero-field splitting of nitrogen-vacancy (NV) color center centers in diamond, we realize a fixed-frequency temperature sensor with ultrafast response and tunable responsivity, enabled by multi-parameter microwave modulate. Matrix-vector multiplication of temperature intensity and responsivity, combined with Kirchhoff’s current summation, enables direct execution of neural-network-style computations on sensed data. The proposed system achieves a single-shot detection and identification latency of just 196.8 μs, as experimentally validated. This work demonstrates a scalable ISC-enabled quantum sensing paradigm, offering a promising route toward high-speed, low-power intelligent temperature field detection.
Keywords:
Electrical and electronic engineering
Sensors
Engineering
general
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

M
Microsystems and Nanoengineering
IF:
9.9
Papers:
1.3K
Citations:
6.7K

Organization

Cited Papers

Cited Papers

Citing Papers

Citing Papers