A simple cellphone can be transformed into a scientific instrument that identifies drugs, chemicals, and pathogens with just $50 components.
Texas A&M scientists have created an extension for an ordinary cellphone to detect chemicals, drugs, and biological molecules. This breakthrough is published in Reviews of Scientific Instruments by AIP Publishing.
Modern smartphones include high-quality cameras that can detect low light levels and eliminate digital noise using software to process the images. This sensitivity has been used in recent research to create cellphone cameras that can be used for heart rate detection and portable microscopes.
Two types of spectroscopy are used to make the current breakthrough. Fluorescence spectroscopy measures the fluorescence light emitted from a sample. Raman spectroscopy is used to detect molecules such as DNA or RNA that emit very low intensities of light. This cellphone detector was developed using both types.
As a light source, the system also includes a cheap diode laser oriented at right angles with the line connecting the sample to the cellphone camera. This arrangement blocks back-reflected light from entering the camera.
Peter Rentzepis, the author, said that right-angle excitation geometry is also easier to use to analyze samples where bulk properties are to be measured.
They examined a range of samples with their built cellphone detector. This included common solvents like ethanol, acetone, and isopropyl alcohol. The investigators recorded Raman spectra for solid objects such as carrots or bacteria pellets.
Because carrots contain carotene, they were chosen for this study. Their laser light has a wavelength that is easily absorbed by the orange pigment and by the pigments in bacteria.
Investigators compared their system’s sensitivity to some of the most sensitive industrial Raman spectrometers. The commercial instrument had a signal-to-noise ratio that was ten times greater than the cellphone system.
However, the cellphone detector’s sensitivity could be increased using one RGB analysis channel. Although the system has a limited dynamic range, investigators point out this can easily be overcome using multiple HDR (or High Dynamic Range) applications that combine images from multiple exposures.
This system is inexpensive and accurate, with the addition of the laser.