CAREER: Understanding Dielectrophoretic Molecular Transport

职业:了解介电泳分子传输

基本信息

  • 批准号:
    2337878
  • 负责人:
  • 金额:
    $ 58.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2024
  • 资助国家:
    美国
  • 起止时间:
    2024-09-01 至 2029-08-31
  • 项目状态:
    未结题

项目摘要

Few small-scale separation methods are available to support critical applications like medical diagnostics or the sensing of dilute chemicals. Dielectrophoretic molecular transport (DMT), which works at small length scales, flexibly separates most solutes out of water but it is not used because current mathematical models are unable to accurately predict its behavior. This CAREER project seeks to develop and validate models of DMT equilibrium and transport behavior. These models and the improved understanding of DMT that will result from this project will enable its use and could result in, for example, lab-on-a-chip diagnostics which broaden access to important medical tests and improve well-being. This project will accomplish this while creating an equitable and inclusive pipeline to graduate education that will broaden and strengthen participation in scientific research.The primary research goal of this CAREER project is to develop and validate models for dielectrophoretic molecular transport (DMT). To accomplish this objective, a microfluidic device with transparent electrodes and insulation has been developed that permits real time, spatially resolved spectroscopy measurements of solution composition between and around electrodes while controlling initial concentrations, field strengths and gradients, and flow rates. Spatially and temporally resolved concentration data will be used to develop, improve, and validate mathematical models of field-dependent activity coefficients, which will be used to predict equilibrium states and coupled transport in complex solutions. Not only will these constitute the first accurate models of DMT but will also expand our understanding of this transport phenomenon by assessing the importance of structure-field interactions. Integrated with this research project is an undergraduate, research-oriented alternative to Senior Design, which will lead students from starting a research project through to creating and disseminating research products. The research component of this CAREER proposal will serve as a core, guaranteed research opportunity for students within the course. Incorporating research and mentoring into a familiar classroom setting significantly reduces cultural and institutional barriers while reducing uncertainty and time cost associated with undergraduate research. In doing so, this plan will increase participation in undergraduate research and ideally position students to continue and thrive in their future education and career.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.
很少有小规模的分离方法可用于支持关键应用,如医疗诊断或稀释化学品的传感。介电电泳分子传输(DMT),它在小的长度尺度上工作,灵活地分离出水中的大多数溶质,但它没有被使用,因为目前的数学模型无法准确地预测其行为。这个职业项目旨在开发和验证DMT平衡和运输行为的模型。这些模型以及该项目将产生的对DMT的更好理解将使其能够使用,并可能导致例如芯片实验室诊断,从而扩大重要医学测试的获得并改善福祉。该项目将实现这一目标,同时创造一个公平和包容性的管道,研究生教育,将扩大和加强参与科学研究。该CAREER项目的主要研究目标是开发和验证介电泳分子传输(DMT)模型。为了实现这一目标,已经开发了具有透明电极和绝缘体的微流体装置,其允许对电极之间和周围的溶液组成进行真实的时间、空间分辨的光谱测量,同时控制初始浓度、场强和梯度以及流速。空间和时间分辨的浓度数据将用于开发、改进和验证依赖于场的活度系数的数学模型,这些模型将用于预测复杂溶液中的平衡态和耦合运输。这些不仅将构成DMT的第一个准确的模型,但也将扩大我们对这种传输现象的理解,通过评估结构场相互作用的重要性。与这个研究项目相结合的是一个本科生,以研究为导向的替代高级设计,这将导致学生从开始一个研究项目,通过创建和传播研究产品。这个职业生涯的建议的研究部分将作为一个核心,保证研究的机会,为学生在课程内。将研究和指导融入熟悉的课堂环境中,可以大大减少文化和制度障碍,同时减少与本科研究相关的不确定性和时间成本。通过这样做,该计划将增加本科生研究的参与,并为学生在未来的教育和职业生涯中继续发展奠定理想的基础。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

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Craig Snoeyink其他文献

Imaging performance of Bessel beam microscopy.
  • DOI:
    10.1364/ol.38.002550
  • 发表时间:
    2013-07
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Craig Snoeyink
  • 通讯作者:
    Craig Snoeyink
Thermodynamic Study of the Electric Field Effect on Liquid-Vapor Mixture at Equilibrium: An Analysis on a Water-Ethanol Mixture.
平衡时液-气混合物电场效应的热力学研究:水-乙醇混合物的分析。
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Samira Safaripour;G. Anand;Craig Snoeyink
  • 通讯作者:
    Craig Snoeyink
Effect of structure-based training on 3D localization precision and quality
基于结构的训练对 3D 定位精度和质量的影响
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. Abdehkakha;Craig Snoeyink
  • 通讯作者:
    Craig Snoeyink
Accurate subpixel shifting of point spread functions.
点扩散函数的精确亚像素移位。
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    R. Parab;Alexander J Caponavi;Craig Snoeyink
  • 通讯作者:
    Craig Snoeyink
Optimizing CNN using Fast Fourier Transformation for Object Recognition
使用快速傅立叶变换优化 CNN 进行对象识别

Craig Snoeyink的其他文献

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