二维SERS传感器阵列用于识别和可视化两个不同的气味源的气体空间分布
Lin Chen1, Hao Guo2, Cong Wang2
1Department of Information Science, Joint Graduate School of Mathematics for Innovation, Kyushu University, Fukuoka 819-0395, Japan.
Sensors (Basel, Switzerland)
|February 10, 2024
概括
这项研究开发了一个表面增强的拉曼散射 (SERS) 气体传感器阵列,以可视化气味的空间分布. 该系统成功地使用先进的算法识别和绘制了甲和4-乙甲气味来源.
科学领域:
- 化学传感器 化学传感器
- 频谱学是一种光谱学.
- 数据分析 数据分析
背景情况:
- 气味源的空间分布提供了对成分,大小和位置的洞察.
- 表面增强的拉曼散射 (SERS) 气体传感器提供高灵敏度,特异性和快速检测.
- 视觉化气体分布对于气味来源分析至关重要.
研究的目的:
- 开发一种SERS气体传感器阵列,用于可视化空间气体分布.
- 定位和估计气味来源的大小.
- 使用卷积神经网络识别和区分气味化合物.
主要方法:
- 使用SERS气体传感器阵列进行光谱数据采集.
- 用于特征和度提取的非负矩阵分解.
- 应用高斯合适用于气味源定位和尺寸估计.
- 实现了用于光谱识别的卷积神经网络.
主要成果:
- 成功可视化了甲和4-乙烯甲的空间分布.
- 精确地定位和估计气味来源的大小.
- 使用卷积神经网络识别气味化合物和混合物的准确率达到了98.21%.
结论:
- 该SERS气体传感器阵列有效地可视化了气味的空间分布.
- 开发的系统可以定位气味来源,大小估计和识别.
- 潜在的应用包括环境监测,医疗保健和气味来源分析.
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