EXP-LA: High Precision Detection and Prediction of Explosives Based on Multiple Sensing Systems and Data Fusion

爆炸物的复杂程度和种类迅速增加，因此有必要开发传感系统，将多种超灵敏探测技术战略性地结合起来，以显著提高探测的灵敏度和概率。通过多学科的合作，研究人员提出将基于不同传感原理的新型传感器阵列与多传感器数据融合(MSDF)技术相结合，以高精度地检测和预测爆炸物威胁。智力优势：拟议的方法解决了使用几种战略探测爆炸物方面的一些基本挑战。首先，通过集成同时运行的多种类型的检测器[荧光聚合物纳米纤维传感器、纳米线传感器、表面声波传感器(SAW)]，大大提高了检测的可能性。其次，每个传感器都将经过专门设计，以最大限度地提高分析物与受体的相互作用，从而提高灵敏度。超高比表面积的聚合物纳米纤维和金属氧化物纳米线由于分析物-受体相互作用的增强将获得极高的灵敏度。具有化学选择性聚合物涂层的声表面波传感器将提供互补的检测能力。最后，为了分析由多个传感系统获取的数据，我们计划开发基于认知的MSDF模型，并执行仅靠单个传感系统可能无法进行的推理。这种方法将通过识别重合来减少与解释单个传感系统收集的数据相关的不确定性，从而使整个检测系统非常精确，并显著降低错误警报的发生率。更广泛的影响：几名研究生和本科生将积极参与拟议研究的多学科任务。教育活动还包括在现有课程中增加新的模块，参加会议，与研究人员和行业专业人士互动，以及高中学生和教师参与的K-12扩展(通过UMassK-12扩展计划、科学的暑期机会和洛厄尔地区物理联盟)。该项目将开发的新型传感技术将大大增加现有的研究和教育基础设施。与业界合作(Foster-Miller Inc.和Linden Photonics Inc.)将促进技术转让和商业化。该项目的成果将广泛传播，造福于广大受众，增进他们对科学技术的了解，并提高他们对安全和安保问题的认识。

The rapid increase in the level of sophistication and types of explosives necessitate the development of sensing systems that strategically combine multiple, ultra-sensitive detection technologies to significantly improve sensitivity and probability of detection. Through a multidisciplinary collaborative effort the researchers propose to develop and integrate novel sensor arrays based on different sensing principles with multi sensor data fusion (MSDF) techniques for detecting and predicting explosives threat with high precision. Intellectual Merit:The proposed methodology addresses some of the fundamental challenges in sensing of explosives using several strategies. First, the probability of detection is significantly enhanced by integration of multiple types of detectors [fluorescent polymer nanofibrous sensors, nanowire sensors, surface acoustic wave sensors (SAW)] that operate simultaneously. Secondly, each of these sensors will be specifically designed to maximize analyte-receptor interaction, thus improving the sensitivity. Ultra-high surface area polymeric nanofibers and metal oxide nanowires will achieve extremely high sensitivity due to enhanced analyte-receptor interaction. SAW sensors with chemoselective polymer coatings will provide complementary detection capabilities. Finally, for analyzing data acquired by multiple sensing systems we plan to develop cognitive-based MSDF models and perform inferences that may not be possible from a single sensing system alone. This approach will reduce the uncertainties associated with the interpretation of data gathered by the individual sensing systems by identifying coincidences, thus making the overall detection system extremely precise, and significantly lower the incidence of false alarms. Broader Impacts:Several graduate and undergraduate students will be actively involved in the multidisciplinary tasks of the proposed research. Educational activities also include the addition of new modules into existing courses, participation in conferences, interaction with researchers and industry professionals, and K-12 outreach involving high school students and teachers (through the UMass K-12 outreach program, Summer Opportunities in Sciences, and the Lowell Regional Physics Alliance). The novel sensing technologies that will be developed in this project will significantly add to the existing infrastructure for research and education. Partnerships with industry (Foster-Miller Inc., and Linden Photonics Inc.) will facilitate technology transfer and commercialization. The results from this project will be broadly disseminated to benefit a large audience, enhancing their scientific and technological understanding, and increasing their awareness on safety and security issues.