研究目的
To demonstrate a method for high-throughput, precise, refractive-index (RI) sensing using the supercritical-angle fluorescence (SAF) effect, enabling ultrasensitive RI measurements and monitoring changes in biological systems such as bacterial growth.
研究成果
The study demonstrated ultrasensitive refractive-index measurements using supercritical-angle fluorescence analysis, achieving high precision and repeatability. The method's applicability for bio-detection was shown through the monitoring of bacterial growth, offering a label-free, high-throughput approach with potential for diagnostic tests and research applications.
研究不足
The precision of the device is limited by temperature fluctuations, requiring a temperature-stabilizing environmental chamber for measurements beyond ~10?5 RIU. Additionally, the method's sensitivity to system heterogeneity necessitates local calibration for each experiment.
1:Experimental Design and Method Selection:
The study utilized a microfluidic chamber with fluorophore-coated glass coverslips to measure RI changes via SAF effect. A fluorescence microscope with a high numerical aperture objective lens was used to capture the back focal plane (BFP) images.
2:Sample Selection and Data Sources:
Glycerol-water solutions of various concentrations were used for calibration. Escherichia coli bacteria were used as a biological model to demonstrate the system's applicability for bio-detection.
3:List of Experimental Equipment and Materials:
The setup included a microfluidic chamber, PDMS, fluorophore-coated glass coverslips, a fluorescence microscope (Ti Eclipse, Nikon), a 100X, 1.49 NA objective lens (Nikon), and an SCMOS camera (Prime95b, Photometrics).
4:49 NA objective lens (Nikon), and an SCMOS camera (Prime95b, Photometrics).
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The device was calibrated with glycerol-water solutions. Bacterial growth was monitored by measuring RI changes in the microfluidic chamber over time.
5:Data Analysis Methods:
A custom algorithm was developed for precise circle fitting to the BFP image to determine the RI, utilizing subpixel precision and outlier removal for robustness.
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