Collaborative Research: Characterization of Nanosensor Field-Assisted Detection of Biomarkers at Ultralow Concentration

1067502/1064574 Liu/HuThis proposal旨在量化生物标志物检测过程并解决超低浓度（毫微微摩尔或fM）下生物传感器检测的难题，这对于疾病的早期诊断至关重要。尽管近年来生物传感器的研究取得了很大进展，但人们对生物传感器检测过程和超低浓度下生物-纳米界面相互作用的基本认识还很有限，这阻碍了对实验结果的解释和传感器的设计。其中一个例子是硅纳米线传感器的实验演示和理论扩散反应模型之间的检测时间的巨大差异。本研究的目标是通过一种新的多物理计算模型解决超低浓度生物标志物检测过程中的难题，并通过超灵敏的bio-FET传感器验证，探索电动力学对检测速度加速的可能贡献.拟议的研究不仅将促进对生物标记物-纳米传感器界面的分子水平理解，而且还有助于设计用于分子运输和诊断的芯片实验室设备，例如，通过检测超低浓度的蛋白质进行早期癌症诊断。我们将提供物理和统计解释的fM纳米传感器的检测过程，并解释实验和理论预测的检测响应时间的三个数量级的差异。本文的主要工作如下：（1）建立生物标志物检测过程的布朗粘附动力学模型，并对实时检测结果进行随机分析. (2)表征内部或外部电动力学（如电渗流、电泳力和介电泳力）如何可能改变生物标志物扩散动力学，并增强超低浓度下的生物标志物检测。(3)基准四个纳米传感器平台的检测灵敏度和响应时间的限制，并建议新的传感器设计更快的检测。(4)通过具有单分子检测能力的新型bioFET纳米传感器设计的生物传感实验来验证模型预测。(5)提供一个预测和评估工具，以帮助设计纳米传感器的最佳性能。统计洞察纳米传感器检测过程将提供通过布朗粘附动力学方法，这不能实现常用的连续扩散反应方法。首次应用多物理场模型研究了各种内外场对探测过程的加速作用，为更快的探测提供了新的设计指导。新的设计和建模结果将通过新型硅纳米生物场效应晶体管进行评估，该晶体管具有单分子检测能力，首次能够在超低浓度下准确和稳定地定量结合动力学。拟议工作的最终目标是帮助开发新的场辅助方法来增强检测能力：将生物标记物集中在纳米传感器附近，提高结合率，提高灵敏度，缩短响应时间。更广泛的影响：提出的基于多物理场模拟的方法将提供一个严格的超低浓度生物传感模型。这项工作的结果将为新的生物传感器设计铺平道路。从拟议的研究中开发的计算工具将在研究界内共享，并随后帮助解决其他重要的生物传感问题，这些问题无法单独通过实验系统地探索。该教育计划将提高高中教师和学生对纳米技术潜在的生物医学应用的认识，促进各级学生对纳米生物界面现象的理解，并提高少数民族对科学和工程的参与。

1067502/1064574Liu/HuThis proposal aims to quantify the biomarker detection process and solve the puzzle ofbiosensor detection at ultralow concentration (femto molar or fM), which is of vital importance forearly diagnostics of diseases. Despite the significant progress achieved in biosensors in recentyears, the fundamental understanding of biosensor detection process and bio-nano interfacialinteraction at ultralow concentrations is very limited, which has hindered the interpretation ofexperimental results as well as sensor design. One example is the large discrepancy indetection time between experimental demonstration of Si nanowire sensor and the theoreticaldiffusion-reaction model. The goal of this proposal is to resolve the puzzles of biomarkerdetection process at ultralow concentrations and explore possible contributions fromelectrokinetics to detection speed acceleration through a novel multiphysicscomputational model with verification by an ultrasensitive bio-FET sensor. The proposedresearch will not only advance the molecular-level understanding of the biomarker-nanosensorinterface, but also help design lab-on-chip devices for molecular transportation and diagnosis,e.g., early cancer diagnosis by detecting protein at ultralow concentrations. We will provide aphysical and statistical interpretation of fM nanosensor detection process and explain the threeorders of magnitude difference in experimental and theoretically predicted detection responsetime. The objectives of the proposed work are:(1) Develop a Brownian adhesion dynamics model for biomarker detection process and performstochastic analysis of real-time detection results.(2) Characterize how internal or external electrokinetics such as electroosmosis flow,electrophoretic and dielectrophoretic force can potentially change biomarker diffusiondynamics, and enhance biomarker detection at ultralow concentrations.(3) Benchmark four nanosensor platforms in terms of limits on detection sensitivity andresponse time and suggest new sensor designs for faster detection.(4) Validate the model prediction through designed biosensing experiments by novel bioFETnanosensors with single molecule detection capability.(5) Provide a prediction and evaluation tool to help design nanosensors for optimal performance.Intellectual merits:1. Statistical insights to the nanosensor detection process will be provided through a Brownianadhesion dynamics approach, which cannot be achieved by the commonly used continuumdiffusion-reaction approach.2. Multiphysics modeling are applied for the first time to study how various inner and externalfields might accelerate the detection process, thus provide new design guidance for fasterdetection. The new design and modeling results will be evaluated through novel Si nanowirebio-FETs, which have single molecule detection capability that enables accurate and stablequantification of binding dynamics at ultralow concentration for the first time.The ultimate goal of the proposed work is to help develop novel field-assisted approach toenhance detection capability: concentrate biomarkers near nanosensor, increase binding rate,improve sensitivity, and shorten response time. An optimized testing platform will be the finaloutcome of this research.Broader impacts:The proposed multiphysics simulation-based method will provide a rigorous mathematicalmodel of biosensing at ultralow concentration. Results of this work will pave the way toward newbiosensor design. The computational tools developed from the proposed research will be sharedwithin the research community and subsequently aid in addressing other important bio-sensingissues that cannot be explored systematically by experiments alone. The education plan willincrease the awareness among high school teachers and students of the potential biomedicalapplications of nanotechnology, to advance understanding of nano-bio interfacial phenomena forstudents at all levels, and to increase minority participation in science and engineering.