CAREER: Multiplexed and Selective Molecular Sensing Based on Raman Enhancement Through 2D Materials

职业：基于 2D 材料拉曼增强的多重和选择性分子传感

• 批准号: 2246564
• 负责人: Shengxi Huang
• 金额: $ 50万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2246564&HistoricalAwards=false
• 关键词: CAREER; Multiplexed; Selective; Molecular; Sensing

Nontechnical Description: The sensing of biochemical molecules has growing importance in various fields including Internet of Things (IoT), big data- and machine learning-enabled health monitoring, disease diagnosis, environmental monitoring, and food safety. An ideal molecular sensing platform should be highly sensitive, selective, label-free, generating reproducible signal, and able to detect multiple analytes simultaneously (multiplexity). Nowadays, advanced sensors can achieve high sensitivity and stability using electronic, optical or electrochemical mechanisms. With the assistance of receptors (meaning prior knowledge of the analytes is required), high selectivity of analytes can also be realized. However, high multiplexity within short measurement time and without prior knowledge is still beyond maturity. In this context, Raman spectroscopy, which probes the molecular vibrational modes through the measurement of light scattering, stands out as a promising method to achieve all the above requirements, in particular multiplexity and label-free, due to the multiple, extremely narrow and fingerprinting peaks in Raman spectra. While the main drawback of Raman spectroscopy is the weak signal, surface-enhanced Raman spectroscopy has been developed to mediate this issue with even single-molecule sensitivity using structured metal substrates, yet it has suffered from signal non-uniformity and noise. An alternative, Raman enhancement through two-dimensional materials (RE2D), replaces metallic substrates with 2D materials, a type of material only one atom or a few atoms thick. RE2D has exhibited significantly improved signal uniformity and low noise with the added advantage of tunability. This project will explore the fundamental science and techniques to further enhance the sensitivity and multiplexity of RE2D technology, by fabricating various types of 2D material substrates, combining 2D materials with metallic substrates, and applying electrical voltage to tune the enhancement. The research outcome will also be used as educational tools for research-like undergraduate and graduate courses. In addition, the PI will initiate a mentoring program for female graduate students, which will broadly benefit Penn State female students in their research, study, work-life balance and career development. Technical Description: This project aims to generate new fundamental understanding of the novel phenomenon of Raman enhancement through two-dimensional materials (RE2D), i.e. the enhancement of Raman signals of organic analyte molecules when placed on 2D material surfaces. This new knowledge will pave the way for an entirely new family of sensors that combine a number of desired features: high multiplexity, molecular selectivity, unprecedented signal reliability, and tunability. By further integrating plasmonic structures with 2D materials, high sensitivity will be achieved. The project is organized around two main thrusts: (1) analysis of the effects of 2D material-analyte molecule pairing on RE2D, as well as the tunability of molecular selection in RE2D; and (2) determination of the combined effects of chemical and electromagnetic mechanisms on Raman enhancement in a 2D-plasmonic integrated substrate. The fundamental science revealed and the prototype devices demonstrated will effectively guide the design and fabrication of sensitive and multiplexed RE2D sensors. The research outcomes will be integrated into the education and outreach activities: creating research-like courses and Research Experience for Undergraduate programs on Raman-based nanosensors and 2D material optoelectronics, which cultivate students’ abilities of critical thinking and motivate them to find solutions to societal problems using advanced technologies. The PI will also initiate a women graduate student mentoring program, and pair female Penn State alumnae mentors with female graduate students to support their long-term success.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.

非技术描述：生物化学分子的传感在包括物联网（IoT）、大数据和机器学习支持的健康监测、疾病诊断、环境监测和食品安全在内的各个领域中越来越重要。一个理想的分子传感平台应该是高灵敏度，选择性，无标记，产生可重复的信号，并能够同时检测多种分析物（多重性）。如今，先进的传感器可以通过电子、光学或电化学机制实现高灵敏度和稳定性。在受体的帮助下（意味着需要分析物的先验知识），也可以实现分析物的高选择性。然而，在短的测量时间内，没有先验知识的高复用性仍然是不成熟的。在这种情况下，通过光散射的测量探测分子振动模式的拉曼光谱法作为实现所有上述要求的有前景的方法而脱颖而出，特别是由于拉曼光谱中的多个、极窄和指纹峰而实现多路性和无标记。虽然拉曼光谱法的主要缺点是信号弱，但是已经开发了表面增强拉曼光谱法来使用结构化的金属基底以甚至单分子灵敏度来调解该问题，然而其遭受信号不均匀性和噪声。另一种选择是通过二维材料（RE 2D）的拉曼增强，用二维材料代替金属基底，二维材料是一种只有一个原子或几个原子厚的材料。RE 2D具有显著改善的信号均匀性和低噪声，并具有可调谐性的附加优势。该项目将探索基础科学和技术，以进一步提高RE 2D技术的灵敏度和多样性，通过制造各种类型的2D材料基板，将2D材料与金属基板结合，并施加电压来调整增强。研究成果也将被用作研究类本科和研究生课程的教育工具。此外，PI还将启动一项针对女研究生的辅导计划，这将使宾夕法尼亚州立大学的女学生在研究、学习、工作与生活的平衡和职业发展方面广泛受益。 技术说明：该项目旨在通过二维材料（RE 2D）产生对拉曼增强的新现象的新的基本理解，即当放置在二维材料表面上时，有机分析物分子的拉曼信号的增强。这一新知识将为一个全新的传感器家族铺平道路，该传感器家族结合了联合收割机许多所需的特性：高度的多重性、分子选择性、前所未有的信号可靠性和可调谐性。通过进一步将等离子体结构与2D材料集成，将实现高灵敏度。该项目围绕两个主要目标进行组织：（1）分析二维材料-分析物分子配对对RE 2D的影响，以及RE 2D中分子选择的可调性;（2）确定化学和电磁机制对二维等离子体基片中拉曼增强的综合影响。揭示的基础科学和展示的原型器件将有效地指导敏感和多路复用RE 2D传感器的设计和制造。研究成果将融入教育和外展活动中：为基于拉曼的纳米传感器和二维材料光电子学的本科项目创建研究型课程和研究经验，培养学生的批判性思维能力，激励他们寻找解决方案使用先进技术解决社会问题。PI还将启动一项女性研究生导师计划，并将宾夕法尼亚州立大学的女校友导师与女研究生配对，以支持她们的长期成功。该奖项反映了NSF的法定使命，并通过使用基金会的智力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

Measuring complex refractive index through deep-learning-enabled optical reflectometry

• DOI: 10.1088/2053-1583/acc59b
• 发表时间: 2023-03
• 期刊: 2D Materials
• 影响因子: 5.5
• 作者: Ziyang Wang;Y. Lin;Kunyan Zhang;Wenjing Wu;Shengxi Huang

Strain-Level Identification and Analysis of Avian Coronavirus Using Raman Spectroscopy and Interpretable Machine Learning

• DOI: 10.1109/isbi53787.2023.10230416
• 发表时间: 2023-04
• 期刊: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
• 作者: Peng Jin;Y. Yeh;Jiarong Ye;Ziyang Wang;Yuan Xue;Na Zhang;Shengxi Huang;E. Ghedin;Huaguang Lu-H

Exploring Topological Semi-Metals for Interconnects

探索互连的拓扑半金属

• DOI: 10.3390/jlpea13010016
• 发表时间: 2023
• 期刊: Journal of Low Power Electronics and Applications
• 影响因子: 2.1
• 作者: Kundu, Satwik;Roy, Rupshali;Rahman, M. Saifur;Upadhyay, Suryansh;Topaloglu, Rasit Onur;Mohney, Suzanne E.;Huang, Shengxi;Ghosh, Swaroop
• 通讯作者: Ghosh, Swaroop

Computational Screening and Multiscale Simulation of Barrier-Free Contacts for 2D Semiconductor pFETs

2D 半导体 pFET 无障碍接触的计算筛选和多尺度仿真

• DOI: 10.1109/iedm45625.2022.10019377
• 发表时间: 2022
• 期刊: 2022 International Electron Devices Meeting (IEDM
• 作者: Yang, Ning;Lin, Yuxuan Cosmi;Chuu, Chih-Piao;Rahman, Saifur;Wu, Tong;Chou, Ang-Sheng;Liew, San-Lin;Fujiwara, Kohei;Chen, Hung-Yu;Ikeda, Junya
• 通讯作者: Ikeda, Junya