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Temporal Effect Analysis in an In-Sensor Computing System Enabled by Retention-Engineered Synaptic Devices

delete2025-10-01
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PRE
AI
S
Sung Hyeon Park
D
Dong Gue Roe
S
Sang Young Jeong
Y
Yoon Young Choi
D
Duho Jang
S
Sung Joon Cheon
M
Min Sub Kim
Y
Yeong Don Park
Y
Youngjae Yoo
D
Dong‐Hwan Kim *
H
Han Young Woo *
J
Jeong Ho Cho *
DOI:10.1021/acssensors.5c01495delete
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Abstract

Abstract

En 中文
In-sensor computing systems demonstrate significant potential for reducing system complexity and enhancing computational efficiency. However, current methodologies predominantly focus on monitoring and processing instantaneous sensor data, neglecting the crucial temporal aspects of sensor inputs. This limitation is particularly significant in healthcare applications, where the human body often exhibits delayed responses to external stimuli. Herein, we developed a synapse-based in-sensor computing system that comprises three retention-engineered synaptic devices connected in parallel to represent the temporal effects of external stimuli. In a proof-of-concept application, the synapse-based in-sensor computing system accurately evaluated the combined temporal risk of hazardous gases, presenting a novel method for assessing the synergistic hazardousness of multiple gases. The presented retention-engineered synapse-based in-sensor computing system offers an innovative solution to the challenges of traditional in-sensor computing, providing a pathway to reduce system complexity and enhance computational efficiency.

Journal

ACS Sensors cover
ACS Sensors
IF:
9.1
Papers:
976
Citations:
2.6W

Organization

S
sungkyunkwan university (skku)
Scholars:
3.6W
Papers: 3.6W
Citations: 49
K
Korea University
Scholars:
3.6W
Papers: 3.8W
Citations: 4.4W
I
incheon national university
Scholars:
3.9K
Papers: 4.3K
Citations: 4
C
Chung-Ang University
Scholars:
1.2K
Papers: 549
Citations: 1.3W
Y
Yonsei University
Scholars:
4.7W
Papers: 4.5W
Citations: 5.2W
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