Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing

Area of Science:

• Nanotechnology
• Plasmonics
• Biochemical Sensing

Background:

• Colorimetric sensors face challenges due to variations in light sources and camera sensitivity.
• Existing methods often lack the sensitivity required for early disease detection.

Purpose of the Study:

• To develop a self-referenced, portable smartphone-based plasmonic sensing platform.
• To enhance colorimetric sensing accuracy and sensitivity using nanoplasmonics.
• To demonstrate applications in biochemical sensing and disease diagnostics.

Main Methods:

• Utilized a nanostructured plasmonic sensor (nano Lycurgus cup array) integrated with a smartphone.
• Employed two sensing principles: liquid refractive index sensing and optical absorbance enhancement.
• Developed an image processing method with an internal reference sample for self-referencing.

Main Results:

• Achieved accurate refractive index measurements of liquids via smartphone imaging.
• Demonstrated a 100-fold improvement in limit of detection (LoD) using absorbance enhancement in a microplate reader format.
• Showcased a 30-fold LoD improvement compared to traditional urine testing strips using the smartphone platform.

Conclusions:

• The smartphone plasmonic sensing platform offers a robust and sensitive solution for colorimetric biochemical sensing.
• The technology shows significant potential for point-of-care diagnostics, including early kidney disease detection.
• Self-referencing and image processing mitigate common sensor errors, enhancing reliability.