臺灣大學: 應用力學研究所沈弘俊呂仁傑Lu, Jen-ChiehJen-ChiehLu2013-03-212018-06-292013-03-212018-06-292012http://ntur.lib.ntu.edu.tw//handle/246246/249717布朗運動檢測技術為一種新式仍在開發中的微型化生物感測元件，具有操作簡易不需利用微機電製程以及易整合於微流道元件中的優點。本研究針對微流道中的布朗運動現象作完整探討，包括濃度變化對布朗運動的影響、布朗運動受壁面的影響、粒徑大小關係以及表面改質後對布朗運動的影響，希望對開發中的感測技術進行最佳化設計。研究方法是使用與抗體抗原相同大小的奈米粒子來做為模擬抗體，實驗方法主要使用微粒子追蹤測速儀 (PTV)針對這些奈米粒子進行速度分析，從速度分佈圖中可看出，布朗運動本身會呈現高斯分佈，最終統計出布朗運動速度，其次部分實驗則使用到螢光相關光譜 (FCS)來進行研究分析，利用針孔(pinhole)來進行空間濾波提升觀測解析度並記錄光強度的變化，最終利用自相關函數來分析出量測樣本的擴散係數。 從實驗中可以看出粒子靠近邊界時受到邊界的影響，布朗運動速度會下降，粒徑增加會使布朗運動速度減慢，同時將邊界進行表面改質之後，由於滑移長度過小，與未經表面改質的對布朗運動速度並無顯著的差異，而當樣本中的粒子濃度提高後，微觀來看使得能量消散更多，巨觀來看就是等效黏滯力提升，造成布朗運動速度下降。未來在智慧型手機發達後應用手機本身的相機當作CCD，分析程式寫成應用程式(APP)希望將此技術應用於日常生活中，落實智慧生活科技。A quantitative immunosensing technique based on the measurement of nanoparticles’ Brownian motion is one of newly innovative bio-sensor chip on miniaturized devices and still in developing. There are some advantages of the technique such as highly compatible to any lab-on-chip device and easily fabricated without micro-electro-mechanical-system (MEMS) process. However, there are still some physical phenomena needed to research in order to optimize this technique. Boundary effect can no more be neglected in a micro system, therefore; this study aims to investigate Brownian motion behaviors in the micro channel, which combines effects of high concentrated nanoparticles, surface modification, different size of nanoparticles and very closed to boundary. The sizes of particles are chosen by simulating real virus and anti-virus. The measurements and analysis of Brownian motion are primarily set up by using micro Particle-Tracking-Velocimetry (μ-PTV) and secondly set up by Fluorescent Correlation Spectroscopy (FCS). By the velocity profiles, it could be easily found out that Brownian motion present as Gaussian distribution; still, Brownian velocity can be obtained by calculating the standard deviation of particles’ velocity. Another secondly method of measurement Brownian motion is FCS which records the intensity signal of particles and analyzes by autocorrelation function which measures the self-similarity of a time signal and obtains the diffusion coefficient. Whatever analyzed methods be used, the results present that Brownian motion gets slow when the particles close to the boundary due to the boundary effect and no slip condition. The radius of particles is proportional to inversely square Brownian velocity. As concentration of solution gets larger, the effective viscosity of solution gets larger, which makes the Brownian motion becomes slower. Surface modification makes the surface become hydrophobic, and Brownian motion is measured comparing with hydrophilic but the there is no apparently different Brownian velocity between two surfaces. Finally, as smart phone with high pixels camera become popular, analysis program could be written as application, therefore; this innovative technique can be bring into the daily life.2815475 bytesapplication/pdfen-US布朗運動生醫感測技術微粒子追蹤測速儀螢光相關光譜高斯分佈Brownian motiondiffusionmicro particle tracking velocimetry (μPTV)fluorescentGaussian distributionthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/249717/1/ntu-101-R99543029-1.pdf