SENSORS: Collaborative Research: Biochemical Sensors and Data Processing for Security Applications

西北大学合作研究--传感器：生化传感器和安全数据处理这项研究解决了当前对可能威胁我们国家安全的生化攻击的担忧。 研究人员开发传感器和数据处理，用于检测生物制剂或有毒化学品的来源，并管理数据库。 该技术还可进一步应用于环境监测、污染控制、爆炸物检测等领域。研究人员开发了三种类型的传感器，用于检测与基底附着受体分子结合的生物靶分子。 第一种方法利用了由目标吸附引起的介电环境变化引起的光学谐振腔的频移。第二种方法利用光学谐振器的灵敏度来检测与吸附目标相关的拉曼光谱。 第三种是将荧光标记物附着在二级识别分子上，当它们与底物受体分子捕获的试剂结合时，检测它们的光发射。 创建探针阵列以筛选多个目标，与信号处理相互作用。 连续感测的策略被认为是。 信号处理部分分析来自化学传感器阵列网络的数据，受到资源限制。 研究人员推导出物质在地铁隧道、购物中心、城市街道、机场行李筛选等中分散的物理模型，包括通量密度传感器。 本计画分析演算法的效能，以最佳化设计阵列。 为了增加功能，研究人员考虑移动传感器（机器人，自动驾驶汽车）并开发运动技术，同时解决其他要求（覆盖范围，能量最小化）。 该研究涉及管理大型网络可能产生的高数据量和处理能力要求。

ABSTRACT0329957John KettersonNorthwestern UniversityTitle: Collaborative Research -- Sensors: Biochemical Sensors and Data Processing for SecurityThis research addresses current concerns about possible biochemical attacks threatening our national security. The investigators develop sensors and data processing for detecting sources of biological agents or toxic chemicals, and managing data-bases. This technology has further applications to environmental monitoring, controlling pollution, detecting explosives, and other scenarios.The investigators develop three categories of sensors for detecting bio-target molecules that bind to substrate-attached receptor molecules. The first exploits the frequency shift of an optical resonator from a change in its dielectric environment brought on by target adsorption. The second exploits the sensitivity of optical resonators to detect Raman spectra associated with the adsorbed targets. The third involves attaching fluorescent labels to secondary recognition molecules and detecting their light emissions when they bound to agents captured by substrate receptor molecules. Arrays of probes are created to screen for multiple targets, interacting with the signal processing. Strategies for making continuous sensing are considered. The signal processing part analyzes data from chemical sensor array networks, subject to resource constraints. The researchers derive physical models for substance dispersion in subway tunnels, shopping malls, city streets, airport bag screening, etc. Flux density sensors are included. This project analyzes the algorithms performance for optimally designing the arrays. To increase the functionality, the investigators consider moving sensors (robots, autonomous vehicles) and develop motion techniques while addressing other requirements (coverage, energy minimization.) The study involves managing high data volumes and processing power requirements that may arise from a large network.