Prediction of Arsenic Concentration in Water Samples Using Digital Imaging Colorimetry and Multi‐Variable Regression

Sajed, Samira; Kolahdouz, Mohammadreza; Sadeghi, Maryam

doi:10.1002/slct.202201376

Cited by 4 publications

(1 citation statement)

References 36 publications

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“…In the recent few decades, researchers have used smartphones as an effective and convenient sensing device for the detection of ion concentration in some organic samples or some food samples, chemical analysis, color analysis, and so forth. [14][15][16] Variation of the color of a material during a process provides useful information for the detection of many of its physical and chemical properties through colorimetric analysis [17][18][19][20] Thus, we proceed to use smartphones as an efficient tool for detecting variations of some colorimetric parameters during the synthesis of polymer-based materials. Recently, smartphone-based colorimetric sensors have been widely used by researchers as they are advantageous because of their cost-effectiveness, portability, real-time detection, and environment-friendly nature.…”

Section: Introductionmentioning

confidence: 99%

Smartphone‐based colorimetric determination of some physicochemical properties of polyaniline on flexible cellulose substrate

Das,

Bhattacharya,

Das

et al. 2024

Polymer Engineering & Sci

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Polymer‐based materials are of high potential for application as active materials in contemporary electronic gadgets. The functionality of such materials is highly dependent on their oxidation state and requires fine control during their synthesis. Owing to that, we have designed a cost‐effective, simple, portable, system for calibration and the detection of the optical and electrical properties of polyaniline loaded on a paper substrate using a smartphone‐based colorimetric sensor. The vapor phase polymerization technique was adopted for preparing polyaniline. Colorimetric measurements of polyaniline‐loaded papers were achieved by estimating the hue, saturation and value (HSV) color parameter values using an open‐source smartphone application called “Color Grab (Color Detection)” during synthesis at different time intervals. The proposed sensor relies on the principle of Beer–Lambert law. The rear camera of the smartphone acts as a sensor and captures the light signal from the samples and provides information to the colorimetric app. The colorimetric results showed a promising correlation between the color parameter values with their electrical properties. The optical absorbance results of all polyaniline‐loaded papers are also in accordance with the H parameter values. The proposed sensor can be used as a portable smartphone‐based point‐of‐care testing kit to bring in‐situ control during synthesis.Highlights Conducting polymer on flexible cellulose substrate. Smartphone‐based visual colorimetric sensor. Biodegradable and environment‐friendly electronic material. Variation of electrical properties in terms of hue values. Cheap, portable sensor for point‐of‐care testing.

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Section: Introductionmentioning

confidence: 99%

Smartphone‐based colorimetric determination of some physicochemical properties of polyaniline on flexible cellulose substrate

Das,

Bhattacharya,

Das

et al. 2024

Polymer Engineering & Sci

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Smartphone‐Embedded Artificial Intelligence‐Based Regression for Colorimetric Quantification of Multiple Analytes with a Microfluidic Paper‐Based Analytical Device in Synthetic Tears

Baştürk,

Yüzer,

Şen

et al. 2024

Advanced Intelligent Systems

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Artificial intelligence (AI) and smartphones have attracted significant interest in microfluidic paper‐based colorimetric sensing due to their convenience and robustness. Recently, AI‐based classification of colorimetric assays has been increasingly reported. However, quantitative evaluation remains a challenge, as classification aims to categorize the color change into discrete class labels rather than a quantity. Therefore, in this study, an AI‐based regression model with enhanced accuracy is developed and integrated into a microfluidic paper‐based analytical device for simultaneous colorimetric measurements of glucose, cholesterol, and pH. The model is also embedded into a smartphone via a custom‐designed Android application named ChemiCheck to complete on‐site colorimetric quantification without internet access in under 1 s. The results demonstrate that the integrated system is able to sensitively detect both glucose (limit of detection [LOD]: 131 ) and cholesterol (LOD: 217 ), concluding the entire analysis within minutes while maintaining a maximum root mean square error of 0.386. Overall, the integrated platform holds great promise for point‐of‐care testing and offers numerous advantages, including easy‐to‐use operation, rapid response, low‐cost, high selectivity, and consistent repeatability, particularly in nonlaboratory and resource‐limited environments.

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Feasibility of digital image colorimetric methods for iron determination in river sediment

Fernanda Ferreira Lovato,

Sidinei Chaves,

Nassif Vidal

et al. 2024

International Journal of Sediment Research

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Prediction of Arsenic Concentration in Water Samples Using Digital Imaging Colorimetry and Multi‐Variable Regression

Cited by 4 publications

References 36 publications

Smartphone‐based colorimetric determination of some physicochemical properties of polyaniline on flexible cellulose substrate

Smartphone‐based colorimetric determination of some physicochemical properties of polyaniline on flexible cellulose substrate

Smartphone‐Embedded Artificial Intelligence‐Based Regression for Colorimetric Quantification of Multiple Analytes with a Microfluidic Paper‐Based Analytical Device in Synthetic Tears

Feasibility of digital image colorimetric methods for iron determination in river sediment

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