Porous silicon on paper-based optical biosensor for diagnostics

用于诊断的纸基光学生物传感器上的多孔硅

• 批准号: 2037673
• 负责人: Sharon Weiss
• 金额: $ 37.5万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2037673&HistoricalAwards=false
• 关键词: Porous; silicon; paper; based; optical

There is a critical need for the development of cost-effective, highly sensitive, widely deployable, rapid diagnostic testing systems that can be adapted for detecting a variety of pathogens. This type of testing system can give healthcare providers key information necessary to make educated treatment decisions, and also can facilitate epidemiological studies of disease distribution patterns. This project investigates whether incorporation of a high surface area porous nanomaterial on a paper substrate can enable a new, highly sensitive, quantitative, and reliable platform for rapid diagnostic testing. The porous nanomaterial serves as the active sensing region that produces a clear optical signal change when signature molecules are selectively captured inside the pores, while the paper substrate is a simple and cost-effective fluid delivery vehicle that enables active transport of a test solution to the porous nanomaterial. The proposed work will lead to advanced understanding of fluid flow dynamics and molecular attachment in porous nanomaterials integrated with paper as well as advanced knowledge related to interfacing nanomaterials with non-traditional substrate materials. Educationally, this program will expose students to interdisciplinary research at the intersections of optics, materials science, engineering, and chemistry. A hands-on optical biosensor demonstration kit will be developed and deployed to K-12 students through shareable videos, classroom visits, and on-campus outreach activities. The goal of this project is to demonstrate a porous silicon-on-paper optical biosensor capable of rapid, accurate, quantitative, and high sensitivity detection of protein biomarkers that will significantly advance the capabilities of rapid diagnostic testing. A comprehensive understanding of the achievable performance metrics, tolerances, and potential limitations of the porous silicon-on-paper optical biosensor platform will be attained. To accomplish this goal, key advances to realize porous silicon in a lateral flow configuration on paper and understand the fluid flow dynamics and molecular binding kinetics in such a configuration will be achieved. Specifically, this project seeks to: (1) develop a robust approach for integrating nanoscale porous films with paper-based microfluidic substrates; (2) understand molecular transport and binding kinetics in a porous film-on-paper platform as a function of the chemical and physical characteristics of the porous film and species infiltrated in the film; (3) establish the viability of using porous silicon optical thin films in a lateral flow rapid test framework; and (4) validate sensor through detection of SARS-CoV IgM and IgG antibodies.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.

迫切需要开发具有成本效益、高度敏感、可广泛部署、可适用于检测各种病原体的快速诊断检测系统。这种类型的检测系统可以为医疗保健提供者提供必要的关键信息，以做出明智的治疗决定，还可以促进对疾病分布模式的流行病学研究。该项目研究在纸基上加入高比表面积多孔纳米材料是否能够实现一种新的、高灵敏度、定量和可靠的快速诊断测试平台。当签名分子被选择性地捕获到孔内时，多孔性纳米材料充当主动传感区域，其产生清晰的光学信号变化，而纸基是一种简单且具有成本效益的流体输送载体，其使得能够将测试溶液主动输送到多孔性纳米材料。这项拟议的工作将导致对与纸张结合的多孔纳米材料中的流体流动动力学和分子附着的深入了解，以及与纳米材料与非传统衬底材料界面连接的高级知识。在教育方面，这个项目将使学生接触到光学、材料科学、工程学和化学的交叉学科研究。将开发一个动手光学生物传感器演示套件，并通过可分享的视频、课堂访问和校园外展活动部署到K-12学生。该项目的目标是展示一种多孔纸上硅光学生物传感器，能够快速、准确、定量和高灵敏度地检测蛋白质生物标记物，从而显著提高快速诊断测试的能力。将全面了解多孔纸上硅光学生物传感器平台的可实现的性能指标、公差和潜在的限制。为了实现这一目标，在纸上实现横向流动构型的多孔硅以及理解这种构型下的流体流动动力学和分子结合动力学将取得关键进展。具体地说，本项目旨在：(1)开发一种将纳米级多孔薄膜与纸基微流控衬底相结合的可靠方法；(2)了解多孔膜-纸上多孔膜平台中分子的传输和结合动力学作为多孔膜的化学和物理特性以及渗透在膜中的物种的函数；(3)建立在横向流动快速测试框架中使用多孔硅光学薄膜的可行性；以及(4)通过检测SARS-CoV IgM和Ig G抗体来验证传感器。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。