EAGER: Low-cost Sensors for real-time monitoring of environment using Mobile Devices

EAGER：使用移动设备实时监控环境的低成本传感器

• 批准号: 1840712
• 负责人: Mulpuri Rao
• 金额: $ 15万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1840712&HistoricalAwards=false
• 关键词: EAGER; Low; cost; Sensors; real

Measuring individual exposure in real-time can revolutionize air quality monitoring in communities everywhere. Such information would allow citizens to take preventive measures to reduce their exposures to air toxins, which would tremendously impact their health and quality of life. Mobile devices such as smart-phones and tablets represent a powerful infrastructure which could be leveraged to develop personal air monitors. However, traditional sensor technologies (such as electrochemical and photo-ionization detectors), commonly used for industrial safety monitoring, are big, power-hungry, and has limited sensitivity and life-time. The goal of this EAGER is to explore a highly-selective sensor architecture, utilizing nanoengineered gallium nitride (GaN) photoconductors functionalized with multicomponent nanoclusters of metal-oxides and metals. Innovation in photo-enabled sensing makes it possible to operate these sensors at room-temperature and resulting in significant reduction in operating power. The strength of this approach is that it uses all standard microfabrication techniques, for developing economical, multi-analyte, single-chip sensor solution. Due to the use of inert wide-bandgap semiconductor, metal-oxides, and noble metals, the environmental impact of these sensors during their life cycles is minimal. The proposed exploratory work will be done in collaboration with NIST and N5 Sensors Inc. Future prospects of such low-power, small form-factor sensors include embedded-chip or plug-in module with multi-analyte sensor arrays for the smart phones for citizens and soldiers for acquiring real-time environmental information. The research provides an excellent opportunity for a graduate student from an underrepresented group, undergraduate students, and students from Thomas Jefferson High School of Science and Technology to work on the project using state-of-art research facilities at NIST and N5 sensors Inc. Integration of the research with a graduate level course is also proposed.The main goal of this project is to develop a technology for mobile devices to rapidly trace and monitor air toxins in indoor and outdoor environments. To achieve different analyte selectivity, the GaN sub-micrometer photoconductors will be coated with different grain size and crystallographic phases of metals and metal oxides. Heated powder mixtures of TiO2 and WO3 will be tried to achieve high sensitivity to N2O. The basic scientific work includes simulations to gain fundamental understanding of the surface science associated with metal-oxide active site surface adsorption. First-principles Density Functional Theory (DFT) calculations using the Vienna Ab Initio Simulation Package (VASP) will be used to study NO2 and SO2 interactions with metal and metal-oxide surfaces of various morphologies. The SO2 and NO2 adsorption on ideal extended surfaces and defect sites of model metal and metal-oxides (WO3, Pt (111), TiO2, Fe (111)) will be studied. Based on DFT calculations metal-oxide nanoclusters for coating the GaN photoconductor backbone will be selected. The GaN photoconductor fabrication process and the nanoclusters deposition process will be optimized to obtain desired phase, morphology, surface defect structure for achieving the desired sensitivity and selectivity. Sensors will be thoroughly characterized for their sensing performance and reliability. Devices will be field tested for personal exposure monitoring.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

实时测量个人暴露可以彻底改变世界各地社区的空气质量监测。这些信息将使公民能够采取预防措施，减少接触空气毒素，这将极大地影响他们的健康和生活质量。智能手机和平板电脑等移动设备代表了一种强大的基础设施，可以用来开发个人空气监测仪。然而，通常用于工业安全监测的传统传感器技术（如电化学和光电离探测器）体积大，耗电大，灵敏度和使用寿命有限。该EAGER的目标是探索一种高选择性的传感器架构，利用纳米工程氮化镓（GaN）光导体与金属氧化物和金属的多组分纳米团簇功能化。光传感的创新使得在室温下操作这些传感器成为可能，从而大大降低了操作功率。这种方法的优势在于它使用了所有标准的微加工技术，用于开发经济、多分析物、单芯片传感器解决方案。由于使用惰性宽禁带半导体、金属氧化物和贵金属，这些传感器在其生命周期内对环境的影响最小。拟议的探索性工作将与NIST和N5 Sensors Inc.合作完成。这种低功耗，小尺寸传感器的未来前景包括嵌入式芯片或插件模块，具有多分析传感器阵列，用于公民和士兵的智能手机，用于获取实时环境信息。这项研究为来自代表性不足的群体的研究生、本科生和托马斯杰斐逊科学技术高中的学生提供了一个极好的机会，可以使用NIST和N5传感器公司的最先进的研究设施进行项目研究。并建议将研究与研究生课程相结合。该项目的主要目标是开发一种移动设备技术，以快速跟踪和监测室内和室外环境中的空气毒素。为了实现不同的分析物选择性，氮化镓亚微米光导体将被不同的晶粒尺寸和金属和金属氧化物的结晶相所覆盖。TiO2和WO3的加热粉末混合物将尝试实现对N2O的高灵敏度。基础科学工作包括模拟以获得与金属氧化物活性位点表面吸附相关的表面科学的基本理解。使用维也纳从头算模拟包（VASP）的第一性原理密度泛函理论（DFT）计算将用于研究NO2和SO2与各种形态的金属和金属氧化物表面的相互作用。研究了SO2和NO2在模型金属和金属氧化物(WO3, Pt （111), TiO2, Fe(111)）的理想扩展表面和缺陷位点上的吸附。基于DFT计算，选择金属氧化物纳米团簇用于涂层GaN光导体骨架。将优化GaN光导体的制备工艺和纳米团簇沉积工艺，以获得所需的相、形貌、表面缺陷结构，从而实现所需的灵敏度和选择性。传感器将全面表征其传感性能和可靠性。设备将进行现场测试，用于个人暴露监测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Accelerated Stress Tests and Statistical Reliability Analysis of Metal-Oxide/GaN Nanostructured Sensor Devices

• DOI: 10.1109/tdmr.2020.3028786
• 发表时间: 2020-12-01
• 期刊: IEEE TRANSACTIONS ON DEVICE AND MATERIALS RELIABILITY
• 影响因子: 2
• 作者: Khan, Md Ashfaque Hossain;Debnath, Ratan;Rao, Mulpuri V.
• 通讯作者: Rao, Mulpuri V.

Nanowire-Based Sensor Array for Detection of Cross-Sensitive Gases Using PCA and Machine Learning Algorithms

• DOI: 10.1109/jsen.2020.2972542
• 发表时间: 2020-06-01
• 期刊: IEEE SENSORS JOURNAL
• 影响因子: 4.3
• 作者: Khan, Md Ashfaque Hossain;Thomson, Brian;Rao, Mulpuri, V
• 通讯作者: Rao, Mulpuri, V

Scalable metal oxide functionalized GaN nanowire for precise SO2 detection

• DOI: 10.1016/j.snb.2020.128223
• 发表时间: 2020-09-01
• 期刊: SENSORS AND ACTUATORS B-CHEMICAL
• 影响因子: 8.4
• 作者: Khan, Md Ashfaque Hossain;Thomson, Brian;Rao, Mulpuri, V
• 通讯作者: Rao, Mulpuri, V

Functionalization of GaN Nanowire Sensors With Metal Oxides: An Experimental and DFT Investigation

• DOI: 10.1109/jsen.2020.2978221
• 发表时间: 2020-07-01
• 期刊: IEEE SENSORS JOURNAL
• 影响因子: 4.3
• 作者: Khan, Md Ashfaque Hossain;Thomson, Brian;Rao, Mulpuri, V
• 通讯作者: Rao, Mulpuri, V