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Funding Information: The work was performed in the School of Chemical Engineering at Aalto University. The profilometry measurements were performed in Nanotalo which is a part of the Department of Applied Physics in the School of Science at Aalto University. The work was supported by Academy of Finland SUPER-WEAR project (decision number: 322214). The raw/processed data required to reproduce these findings cannot be shared at this time due to technical or time limitations. Funding Information: The work was performed in the School of Chemical Engineering at Aalto University. The profilometry measurements were performed in Nanotalo which is a part of the Department of Applied Physics in the School of Science at Aalto University. The work was supported by Academy of Finland SUPER-WEAR project (decision number: 322214). Publisher Copyright: © 2021 The Authors Mechanochromic materials, when exposed to mechanical deformation, undergo a modification of optical properties. This behaviour can stem from either conformational rearrangements, disruptions of intermolecular interactions, or molecular structure changes affecting absorption, emission, or reflection abilities. Here reversible colour change of Disperse Red 1/polyvinylpyrrolidone films resulting from humidity annealing and subsequent stretching is reported. Due to the humidity-induced blue shift of the absorbance peak related to exciton coupling of the chromophores, the tone of films abruptly changes from red to orange. Upon stretching, the gradual disaggregation of the chromophores takes place and therefore the colour switches back to red in a stepless manner. Using either red–green–blue analysis of time lapse photography or UV–Visible measurements, this transformation, which is also well visible by the naked eye, can be followed with high accuracy. This work offers the opportunity to apply the strain sensor inhumid environments to prevent the mechanical failures by showing a colour change in areas subjected to undesired stress. Moreover, dip-coating yarns with mechanochromic coating allows fabrication of functional yarns that change their colour based on their stretching state – thus enabling preparation of colour-changing stretchable textiles was demonstrated.

The present work reports the development of a biologically inspired analytical system known as Electronic Eye (EE), capable of qualitatively discriminating different tequila categories. The reported system is a low-cost and portable instrumentation based on a Raspberry Pi single-board computer and an 8 Megapixel CMOS image sensor, which allow the collection of images of Silver, Aged, and Extra-aged tequila samples. Image processing is performed mimicking the trichromatic theory of color vision using an analysis of Red, Green, and Blue components (RGB) for each image’s pixel. Consequently, RGB absorbances of images were evaluated and preprocessed, employing Principal Component Analysis (PCA) to visualize data clustering. The resulting PCA scores were modeled with a Linear Discriminant Analysis (LDA) that accomplished the qualitative classification of tequilas. A Leave-One-Out Cross-Validation (LOOCV) procedure was performed to evaluate classifiers’ performance. The proposed system allowed the identification of real tequila samples achieving an overall classification rate of 90.02%, average sensitivity, and specificity of 0.90 and 0.96, respectively, while Cohen’s kappa coefficient was 0.87. In this case, the EE has demonstrated a favorable capability to correctly discriminated and classified the different tequila samples according to their categories.

Activated sludge process is the most common method for biological treatment of industrial and municipal wastewater. One of the most important parameters in performance of activated sludge systems is quantitative monitoring of biomass to keep the cell concentration in an optimum range. In this study, a novel method for activated sludge quantification based on image processing and RGB analysis is proposed. According to the results, the intensity of blue color in the macroscopic image of activated sludge culture can be a very accurate index for cell concentration measurement and R2 coefficient, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) which are 0.990, 2.000, 0.323, and 13.848, respectively, prove this claim. Besides, in order to avoid the difficulties of working in the three-parameter space of RGB, converting to grayscale space has been applied which can estimate cell concentration with R 2 = 0.99. Ultimately, an exponential correlation between RGB values and cell concentrations in lower amounts of biomass has been proposed based on Beer-Lambert law which can estimate activated sludge biomass concentration with R 2 = 0.97 based on B index.

Colorimetric measurements by image analysis, giving RGB or HSV data, have become commonplace with optical indicator-based assays and as a readout for paper-based analytical devices (PADs). Yet, most works on PADs tend to ignore the quantitative relationship between color data and concentration, which may hamper their establishment as analytical devices and make it difficult to properly understand chemical or biological reactions on the paper substrate. This Perspective Article discusses how image color data are computed into colorimetric absorbance values that correlate linearly to dye concentration and compare well to traditional spectrophotometry. Thioflavin T (ThT), Neutral Red (NR), and Orange IV are used here as model systems. Absorbance measurements in solution correlate well to image data (and Beer's law) from the color channel of relevance if the gamma correction normally used to render the picture more natural to the human eye is removed. This approach also allows one to correct for color cast and variable background color, which may otherwise limit quantitation in field measurements. Reflectance measurements on paper color spots are equally found to correlate quantitatively between spectroscopy and imaging devices. In this way, deviations from Beer's law are identified that are explained with dye interactions on the paper substrate.

Paper-based analytical devices are an emerging class of lightweight and simple-to-use analytical platform. However, challenges such as instrumental requirements and chemical reagents durability, represent a barrier for less-developed countries and markets. Herein, we report an advanced laminated device using red emitting copper nanocluster and RGB digital analysis for signal improvement. Upon RGB system assistance, the device signal-to-background ratio and the calibration sensitivity are highly enhanced under a filter-free setup. In addition, the calibration sensitivity, limit of detection, and coefficient of determination are on par with those determined by instrumental fluorescence analysis. Moreover, the limitation of using oxidation-susceptible fluorescent nanomaterials is overcome by the introduction of protecting tape barriers, antioxidative sheets, and lamination enclosing. The robustness of device is highly advanced, and the durability is prolonged to more than tenfold.

DETECHIP® is a detection system made of various sensors that has been shown to detect and discriminate between small molecules of interest, including various illicit and over-the-counter drugs. Previously, detection was normalized to a single concentration of analyte. Now this detection assay can detect concentration differences in analytes via red, green, and blue color value changes and shifts in the UV-Vis spectra of the assay. To determine the concentrations differences, the exposed assays were scanned on a flatbed scanner and the images were analyzed for individual RGB values with a custom macro in ImageJ, an image analysis program. Increasing concentrations of the analyte resulted in greater differences in color values between control and analyte wells. These differences showed a linear relationship to concentration change, some with correlation coefficients greater than 98%. This work expands the capability of DETECHIP to give information about the concentration of analyte when the analyte identity is known.