Optimization of Carbon Nanotube Based Chemical Sensors Through Micro-Raman Enabled Defect Analysis

摘要：本研究的目的是开发高效的碳纳米管（CNT）为基础的化学传感器，通过在原位识别和操纵的CNT导电通道中的缺陷。这些缺陷在CNT电化学灵敏度中起着核心作用，但还没有严格的研究特定的缺陷类型和/或分布如何影响实际的基于CNT的器件。该方法是基于一个独特的和高度集成的过程，涉及显微拉曼光谱，电子显微镜，数值模拟和微环境的电气characterization.This研究解决了一个原则的障碍，以碳纳米管为基础的化学传感器的巨大潜力。智力上的优点包括：（1）开发和评估具有改进的分析物灵敏度、效率和选择性的低成本CNT基化学传感器;以及（2）通过将基本材料和器件表征技术与数值建模相结合来推进纳米计量学。这种全面的三管齐下的方法从未被用于系统地检查实际工作设备中的CNT传导通道。拟议的研究将深入了解这些缺陷如何影响工作纳米器件的性能，并实现表征纳米电子学的新方法。该项目的各种研究活动将涉及当地K-12学校的少数民族本科生和女孩，通过NSF赞助的LSAMP/REU和俄勒冈州星期六学院计划，使学生能够学习研究技能，并在未来加入一个有竞争力的劳动力。研究结果将通过期刊出版物、会议报告、研讨会和PI广泛传播。网站.

Abstract: The objective of this research is to develop highly efficient carbon nanotube (CNT) based chemical sensors through in-situ identification and manipulation of defects in the CNT conduction channel. These defects play a central role in CNT electrochemical sensitivity but there has been no rigorous study of how specific defect types and/or distributions affect actual CNT-based devices. The approach is based on a unique and highly integrated process involving micro-Raman spectroscopy, electron microscopy, numeric modeling and microenvironment electrical characterization.This research tackles one of the principle roadblocks to the enormous potential of CNT-based chemical sensors. The intellectual merit includes: (1) the development and evaluation of low-cost CNT-based chemical sensors with improved analyte sensitivity, efficiency and selectivity; and (2) the advancement of nanometrology by combining both fundamental material and device characterization techniques with numerical modeling. This comprehensive three-pronged approach has never been employed to systematically examine CNT conduction channels in actual working devices. The proposed research will provide an in-depth understanding of how these defects affect the performance of working nanodevices and enable a new methodology for characterizing nanoelectronics.The various research activities of this project will involve minority undergraduate students and girls from local K-12 schools through NSF-sponsored LSAMP/REU and Oregon Saturday Academy programs to enable students to learn research skills and to join a competitive workforce in the future. The research findings will be disseminated broadly through journal publications, conference presentations, seminars, and the PIs? websites.