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

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.

Authors

Institutions

Publication Details

Journal
Microsystems & Nanoengineering
Published
2025-12-10
DOI
https://doi.org/10.1038/s41378-025-01076-1
Primary Topic
Diamond and Carbon-based Materials Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jinyu Tai, Weixuan Zhang, Huan Fei Wen, Jun Tang et al.
Microsystems & Nanoengineering
Diamond and Carbon-based Materials Research
article

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

Jinyu Tai, Weixuan Zhang, Huan Fei Wen, Jun Tang, Lili Wang, Yunbo Shi, Zongmin Ma, Zheng Lou, Xin Li, Hailong Wang, Hao Guo, Zhonghao Li, Zhiqiang Xiang, Wei Gao, Fēi Dèng, Jun Liu
article en

Abstract

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.

Microsystems & NanoengineeringVol. 11(1)
North University of China (CN), Shanxi University (CN), Chinese Academy of Sciences (CN), Institute of Semiconductors (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 68%
Diamond and Carbon-based Materials Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.