The hue or H component of the hue, saturation, value (HSV) color space has been studied as a quantitative analytical parameter for bitonal optical sensors. The robust nature of this parameter provides superior precision for the measurement of sensors which change colors with the speciation of some indicator molecule. This parameter has been compared to red, green, blue (RGB) intensity and RGB absorbance along with differences and ratios of both intensity and absorbance and has been demonstrated to be 2 to 3 times superior. The H value maintains this superior precision with variations in indicator concentration, membrane thickness, detector spectral responsivity, and illumination. Because this parameter is stable, simple to calculate, easily obtained from commercial devices such as scanners and digital cameras, continuous over the entire color gamut, and bound between values of 0 and 1, it shows great promise for use in a variety of sensing applications including imaging, automated analysis, pharmaceutical sensing, lab-on-a-chip devices, and quality control applications.
Localized surface plasmon resonance (LSPR) sensors are used in a broad range of detection applications across the chemical, biological, environmental, and medical disciplines. These types of sensors traditionally use the plasmon resonance wavelength of a nanoparticle array to detect changes in refractive index at the sensor surface and, therefore, require expensive spectroscopic instrumentation for readout. However, simple, portable, and low-cost LSPR sensors can be achieved by transitioning to colorimetric measurements, in which refractive index changes are quantified using the R, G, and B pixel intensities from digital nanoparticle images. In this study, we use R, G, and B pixel intensities to quantify color coordinates in the HSV, CIE L*a*b*, and rgb chromaticity color spaces. We show that for sensors comprising 115 nm diameter nanoparticles, hue (H) is the most sensitive color parameter, with a change per refractive index unit (Δhue/ΔRIU) of 0.71 and a figure of merit of 183 RIU–1. Furthermore, we compared hue figures of merit (FOM) for nanoparticles in four different diameters (34.1, 59.8, 81.5, and 115 nm) and showed that hue sensitivity peaks at a diameter of 81.5 nm, with a FOM of 222 RIU–1. In contrast, the spectroscopic sensitivity, quantified in units of Δnm/ΔRIU, increased continually with nanoparticle size. Therefore, the design requirements for colorimetric plasmonic sensors differ from those for spectroscopic plasmonic sensors. This difference in size dependence was explored further using Mie calculations to simulate nanoparticle extinction spectra. Our results revealed that, while λmax responds linearly to refractive index changes, hue responds in a sigmoidal fashion. As a result, the nanoparticle size used in colorimetric sensors relying on hue measurement should be carefully selected to achieve a linear sensor response. We provide general design rules for optimizing hue-based colorimetric sensors and demonstrate that our sensor can be used with a smartphone to detect antibody–antigen interactions.
A new spectrometer, here denoted the SLIM (simple, low-power, inexpensive, microcontroller-based) spectrometer, was developed that exploits the small size and low cost of solid-state electronic devices. In this device, light-emitting diodes (LED), single-chip integrated circuit photodetectors, embedded microcontrollers, and batteries replace traditional optoelectronic components, computers, and power supplies. This approach results in complete customizable spectrometers that are considerably less expensive and smaller than traditional instrumentation. The performance of the SLIM spectrometer, configured with a flow cell, was evaluated and compared to that of a commercial spectrophotometer. Thionine was the analyte, and the detection limit was approximately 0.2 microM with a 1.5-mm-path length flow cell. Nonlinearity due to the broad emission profile of the LED light sources is discussed.
Creatinine level in urine is a key factor to monitor kidney performance. The use of an alternative microfluidic platform based on cellulose substrates is an interesting option to integrate sample treatment, creatinine recognition by ionophore extraction chemistry and quantification by color measurement through consumer electronics imaging devices. The inclusion of ionophore extraction chemistry based on aryl-substituted calix[4]pyrrole synthetic receptor on 8.7 mm long cotton thread permit the sample treatment, optical recognition of creatinine and their quantification by smartphone running app in unfiltered urine samples diluted 1:100 ratio. The device shows a short response time, 30 s, to creatinine over a wide dynamic range (from 1.6×10-6 to 5×10-2 M) with reproducibility between 2.9-4.3%. The low interference level of representative species in urine is studied and justified by density functional theory (DFT) calculations.
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