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Automated multi-parametric sorting of micron-sized particles via multi-trap laser tweezers.

机译:通过多阱激光镊子对微米级颗粒进行自动多参数分选。

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摘要

The capabilities of laser tweezers have rapidly expanded since the first demonstration by Ashkin and co-workers in 1970 of the ability to trap particles using optical energy. Laser tweezers have been used to measure piconewton forces in many biological and material science application, sort bacteria, measure DNA bond strength, and even perform microsurgery. The laser tweezers system developed for this dissertation foreshadows the next generation of laser tweezer systems that provide automated particle sorted based upon multiple criteria.; Many laser tweezer sorting applications today entail the operator sorting cells from a bulk sample, one by one. This dissertation demonstrates the technologies of pattern recognition and image processing that allow for an entire microscope slide to be sorted without any operator intervention. We already live in an automated world where the cars we drive are built by machines instead of humans. The technology is there, and the only factors limiting the advancements of fully automated biological instrumentation is the lack of developers with the appropriate knowledge sets.; This dissertation introduces the concept of sorting particles via a multi-parametric approach where several parameters such as size, fluorescence, and Raman spectra are used as sorting criteria. Since the advent of laser tweezers, several groups have demonstrated the ability to sort cells and other particle by size, or by fluorescence, or by any other parameter, but to our knowledge there does not exist a laser tweezer sorting system that can sort particles based upon multiple parameters. Sorting via a single parameter can be a severe limitation as the method lacks the robustness and class specificity that exists when sorting based upon multiple parameters. Simply put, it makes more sense to determine the worth of a baseball card by considering it's condition as well as it's age, rather then solely upon its condition. By adding another parameter such as the name of the player in the card, one can start collecting Babe Ruth rookie cards instead of mint condition cards of bench warmers.; In the future, even better multi-parametric laser tweezer particle sorting systems will be developed that make use of pulsed radiation in order to stimulate nonlinear optical phenomena. This dissertation discusses the feasibility of combining a rapid, non-invasive chemical imaging technology called coherent anti-Stokes Raman scattering (CARS) with a laser tweezer sorting system. This would allow for the birth of a laser tweezer particle sorting system of unprecedented speed and chemical specificity the likes of which the world has not yet seen.
机译:自1970年Ashkin及其同事首次展示了利用光能捕获微粒的能力以来,激光镊子的能力已迅速扩展。激光镊子已在许多生物学和材料科学应用中用于测量微微力,对细菌进行分类,测量DNA键强度,甚至进行显微外科手术。为该论文开发的激光镊子系统预示了下一代激光镊子系统,该系统可根据多个标准对颗粒进行自动分类。如今,许多激光镊子分选应用都需要操作员一对一地分选散装样品中的细胞。本文论证了模式识别和图像处理技术,无需操作员干预即可对整个显微镜载玻片进行分类。我们已经生活在一个自动化的世界中,我们驾驶的汽车是由机器而不是人类制造的。技术在那里存在,限制全自动生物仪器发展的唯一因素是缺乏具有适当知识集的开发人员。本文介绍了一种通过多参数方法对颗粒进行分选的概念,其中使用大小,荧光和拉曼光谱等几个参数作为分选标准。自从激光镊子问世以来,几组研究人员已经证明能够按大小,荧光或其他任何参数对细胞和其他颗粒进行分选,但据我们所知,尚不存在可以对基于颗粒的颗粒进行分选的激光镊子分选系统。在多个参数上。通过单个参数进行排序可能会受到严重限制,因为该方法缺乏基于多个参数进行排序时存在的鲁棒性和类特异性。简而言之,通过考虑棒球的状况和年龄来确定棒球卡的价值,而不是仅仅根据其状况来确定其价值更为有意义。通过在卡中添加另一个参数(例如玩家的名字),人们可以开始收集Babe Ruth新秀卡,而不是取暖台上的薄荷状态卡。将来,将开发出更好的多参数激光镊子颗粒分选系统,该系统利用脉冲辐射来激发非线性光学现象。本文讨论了将快速无创化学成像技术(称为相干反斯托克斯拉曼散射(CARS))与激光镊子分拣系统相结合的可行性。这将催生出前所未有的速度和化学特异性的激光镊子颗粒分选系统,这是全世界尚未见过的。

著录项

  • 作者

    Kaputa, Daniel S.;

  • 作者单位

    State University of New York at Buffalo.$bElectrical Engineering.;

  • 授予单位 State University of New York at Buffalo.$bElectrical Engineering.;
  • 学科 Engineering Electronics and Electrical.; Physics Optics.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;光学;
  • 关键词

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