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.
Principal Investigator: Pradeep Kurup Co-Principal Investigators: Hongwei Sun, Jayant Kumar, Ramaswamy Nagarajan, Zhiyong Gu Intellectual Merit: The advent of new combinations of explosive materials over the past few decades necessitates the development of novel sensing systems for ultra-sensitive detection of these explosives. Most common explosives exhibit very low vapor pressures at room temperature and therefore the sensor technologies have to be extremely sensitive to detect/quantify trace quantities (in the parts per billion) of explosives. This level of sensitivity is often not achievable using a single type of sensor or sensing technology. This project involved the development of novel explosive sensing systems based on combinations of multiple, ultrasensitive detection technologies. This combination of multiple sensing techniques where each type of sensor operates based on clearly distinct sensing principle, can significantly improve sensitivity and probability of detection of explosives. Three types of sensing techniques were pursued during the course of the project. They include fluorescence quenching (fluorescent conjugated polymer sensors), chemiresistive sensing [doped metal oxide nanowire based sensors (MOS)], sensing based on mass or viscoelasticity modulation [polymer coated quartz crystal microbalance (QCM) and surface acoustic wave (SAW) based sensors]. This project resulted in the development of new sensor arrays for detecting common explosives such as dinitrotoluene (DNT), trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), ammonium nitrate and explosive precursors such as hydrogen peroxide [commonly used for the production of Triacetone tetriperoxide (TATP)], nitrotoluene, and nitrobenzene. Fluorescent polymer sensors: The fluorescence conjugated polymer sensors were able to achieve very high sensitivity and selectivity for the detection of DNT, TNT and RDX. The fluorescent sensors were either based on polythiophenes or modified curcumin. MOS: A new class of high surface area tinoxide based nanowires doped with copper, indium, nickel or platinum were evaluated as chemiresistive vapor sensors. MOS exhibited reproducible and reversible response to volatile organic compounds and explosive precursors. SAW and QCM-based sensors: Polymer coatings that can interact and trap explosive vapors were specifically designed to improve the sensitivity and selectivity of these sensors. These sensors exhibited good response to certain types of explosive and explosive precursors. Sensor integration and data fusion: Various sensing technologies (SAW, QCM and MOS) were integrated. The data acquired by the multiple sensors were analyzed using intelligent data fusion models. Data fusion refers to techniques that combine data from multiple sensors in order to achieve improved accuracy and more specific inferences than could be achieved by the use of a single sensor alone. This is because a combination of additional independent and/or redundant data usually has a synergistic effect and results in improved inferences. By identifying coincidences in the predictions made by the different sensors, this ‘intelligent’ explosives-detection system reduces uncertainties associated with the interpretation of data gathered by the individual sensing systems. Apart from significantly advancing the state-of-the-art in each type of sensor technology (fluorescent sensors, MOS, polymer coated QCM, SAW) through the development of new active sensing materials, this project has also resulted in advancements in their integration and in the use of ‘intelligent’ data fusion models. Broader Impact: This project provided research and educational experience for 9 graduate students, 2 undergraduate students, and a postdoctoral research associate. The researchers gained experience in developing sensors, data acquisition systems, conducting experiments, analyzing and interpreting data using pattern recognition techniques. They also interacted with researchers from different disciplines and acquired collaborative skills. One of the graduate students is currently pursuing graduate studies under the supervision of the PI at UMass Lowell. The postdoctoral researcher is currently working on another project funded by the National Science Foundation. Overall, the novel sensing technologies that have been developed in this project has significantly advanced the existing infrastructure for sensing, detection and data fusion at UML. The project team have already explored the possibility of working with ‘Smiths Detection’ and ‘MKS Instruments’ to explore commercialization or licensing of these technologies. Outreach: Training of undergraduate and high school students: Two undergraduate students have worked on this project. In addition, during summer each year, one high schools student was involved in the project. Publications and conference presentations: This project has resulted in 24 peer-reviewed (refereed) journal publications and one book chapter. The research was also presented at various national and international scientific conferences such as the IEEE – International conference – Technologies for Homeland Security, Materials Research Society meeting, American Chemical Society meeting, and the International Symposium on Olfaction and Electronic Nose. Benefits to Society: Efficient and timely detection and prediction of explosives can potentially save human lives and prevent damage to infrastructure. The sensors and the knowledge base developed during this project can be used to improve and transform the explosives detection technologies with a direct impact on the safety and security of the society.
