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.

实时测量个人暴露量可以彻底改变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，减少接触空气中的毒素，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的设备代表了强大的基础设施，可以利用它来开发个人空气监测器。然而，通常用于工业安全监测的传统传感器技术（如电化学和光离子化检测器）体积大，耗电量大，灵敏度和寿命有限。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）光电导体功能化与多组分纳米簇的金属氧化物和金属。光传感技术的创新使得这些传感器可以在室温下工作，从而大大降低了工作功率。这种方法的优势在于它使用所有标准的微制造技术，用于开发经济的多分析物单芯片传感器解决方案。由于使用惰性宽带隙半导体、金属氧化物和贵金属，这些传感器在其生命周期中对环境的影响最小。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具有多分析物传感器阵列的嵌入式芯片或插入式模块，用于公民和士兵的智能手机，以获取实时环境信息。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技高中的学生提供了一个极好的机会，让他们利用NIST和N5传感器公司最先进的研究设施从事该项目。本计画的主要目标是发展一种移动的装置技术，以快速追踪及监测室内及室外环境中的空气毒素。为了实现不同的分析物选择性，GaN亚微米光电导体将涂覆有不同的金属和金属氧化物的晶粒尺寸和晶相。将尝试TiO2和WO3的加热粉末混合物以实现对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部位表面吸附相关的表面科学的基本理解。使用维也纳从头计算模拟包（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。本文研究了SO_2和NO_2在模型金属和金属氧化物（WO_3，Pt（111），TiO_2，Fe（111））的理想扩展表面和缺陷位上的吸附。基于DFT计算，将选择用于涂覆GaN光电导体骨架的金属氧化物纳米团簇。GaN光电导体制造工艺和纳米团簇沉积工艺将被优化以获得期望的相、形态、表面缺陷结构，以实现期望的灵敏度和选择性。传感器将全面表征其传感性能和可靠性。设备将进行个人暴露监测的现场测试。该奖项反映了NSF的法定使命，并且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