一种逐级提取分析气体催化发光信息的传感器研究

An important direction of sensors development is extracting analyte information as much as possible from a sensor to improve its' ability to differentiate and identify analyte. This project proposes a new idea that is extracting information of gaseous analyte hierarchically: Allow the gas to contact with sensing material to produce first -level cataluminescence reaction, then the exhaust contacts with sensitive material continuously to produce second-level(or more -level) cataluminescence reaction. One could extract luminescent signals of the analyte hierarchically by this way. The experiment showed that the first and second-level cataluminescence reactions of four types of alcoholic vapors were carried separately on the nano-magnesia, and each ratio of the two luminous intensities of the alcohols remained constant in a broader concentration range which was different from each other. It could be used as its characteristic value to distinguish between different kinds of alcohol molecules. The different gases which can hierarchically generate different cataluminescence phenomenon may be derived from the stepwise oxidation of different gas molecules to form different level products on the sensing materials. Therefore, the ratios of hierarchical luminous intensities of various gases can reflect the difference on the molecules structure. This project aims to design several kinds of sensor arrays. By hierarchically extracting multi-channel information from cataluminescence reaction between sensing material and analyte, we could achieve the goal to accurately discriminate and identify the similar nature of single-component or multi-component gases. The project will also study the reaction mechanism that gas molecules produce hierarchical luminous phenomenon.

在传感器中尽可能多的提取分析物信息来提高其区分和鉴别物质能力是传感器发展的重要方向。本课题提出一种逐级提取分析气体信息的新思路: 将分析气体与敏感材料接触产生一级催化发光反应后的尾气与敏感材料继续接触产生二级(或多级)催化发光反应,逐级提取分析物的发光信号。实验显示,四种醇蒸气分别在纳米氧化镁上进行一级和二级催化发光反应,每种醇两次产生的发光信号强度的比值在较宽浓度范围内为常数并与其它醇不同, 可作为其特征值来区分不同的醇分子。不同气体能够逐级产生强度不同的催化发光现象可能源于不同的气体分子在敏感材料上被逐级氧化时生成的各级产物的不同。因此不同气体的逐级发光强度比值能够反映其分子结构的不同。本项目拟设计几种传感器阵列,通过提取气敏材料与分析物之间逐级发生催化发光反应而产生的多通道信息,达到准确区分和鉴别性质相近的单组分或多组分气体的目的。本项目也将研究气体分子产生逐级发光现象的反应机理。

虽然传感器阵列可以做到识别不同气体或不同物质,但是由于存在各个传感器随时间的飘移而带来的不稳定性以及使用前各个传感器要进行校准的复杂性,因此其使用受到限制。本项目研究的简单传感器可以对有机气体同系物和同分异构体同时进行定性和定量分析。. 研究了基于两个敏感元件提取多维催化发光信号，并结合化学计量学模型，识别18种常见有害气体的传感器。通过变换气体流经两个敏感元件的方向，分别获得了18种有害气体的8个CTL反应信号，并组成了每种气体的特征信号图谱。应用主成分分析法（PCA）和线性判别分析（LDA）法处理实验数据，成功识别了相同浓度和不同浓度的18种气体，建立了一种鉴别气体的新方法。. 设计了一种带有密闭反应体系的单个催化发光传感器，用于酒和食醋等成分复杂的混合物的分析。在这个带有足够氧气的密闭反应器中，分析物与催化剂反复接触，反应时间延长。当以固定波长的滤光片为单色器时（波长固定测试模式），能获取分析物的“多峰响应曲线”；当以不同波长的滤光片为单色器时（波长扫描测试模式），能得到分析物的“光谱阵列模式”。此“多峰响应曲线”和“光谱阵列模式”发挥着指纹图谱的功能，可用于分析物的定性分析。. 本项目的预期目标为公开发表相关研究论文4篇。目前已达到预期目标,在SCI收录等刊物上发表相关研究论文4篇,其中一篇发表在高影响因子期刊《Analytica Chimica Acta》上。