Imaging-based intelligent spectrometer on a plasmonic rainbow chip.
Dylan TuaRuiying LiuWenhong YangLyu ZhouHaomin SongLeslie YingQiaoqiang GanPublished in: Nature communications (2023)
Compact, lightweight, and on-chip spectrometers are required to develop portable and handheld sensing and analysis applications. However, the performance of these miniaturized systems is usually much lower than their benchtop laboratory counterparts due to oversimplified optical architectures. Here, we develop a compact plasmonic "rainbow" chip for rapid, accurate dual-functional spectroscopic sensing that can surpass conventional portable spectrometers under selected conditions. The nanostructure consists of one-dimensional or two-dimensional graded metallic gratings. By using a single image obtained by an ordinary camera, this compact system can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum. Assisted by suitably trained deep learning algorithms, we demonstrate the characterization of optical rotatory dispersion of glucose solutions at two-peak and three-peak narrowband illumination across the visible spectrum using just a single image. This system holds the potential for integration with smartphones and lab-on-a-chip systems to develop applications for in situ analysis.
Keyphrases
- deep learning
- high resolution
- high throughput
- circulating tumor cells
- low cost
- machine learning
- molecular docking
- high speed
- convolutional neural network
- type diabetes
- mass spectrometry
- healthcare
- social media
- human health
- health information
- blood glucose
- resistance training
- skeletal muscle
- risk assessment
- blood pressure
- climate change
- glycemic control
- sensitive detection
- weight loss
- body composition
- photodynamic therapy
- visible light