Rapid detection and quantification of milk adulterants using a nanoclusters-based fluorescent optical tongue.

A paper-based sensor array consisting of eight nanoclusters (NCs) combined with multivariate analysis was used as a rapid method for the determination of animal sources of milk; goat, camel, sheep and cow. It was also used to detect and quantify three adulterants including sodium hypochlorite, hydrogen peroxide and formaldehyde in milk. The changes in fluorescence intensity of the NCs were quantified using a smartphone when the sensor array was immersed in the milk samples. The device generated a specific colorimetric signature for milk samples from different animals and for different adulterants. This allowed simultaneous identification of animal and adulterant sources with 100% accuracy. The device was found to be capable of accurately measuring the level of contaminants with a detection limit as low as 0.01% using partial least squares regression. In conclusion, a paper-based optical tongue device has been developed for the detection of adulterants in milk with point-of-need capability.

Paper and nylon based optical tongues with poly(p-phenyleneethynylene)-fluorophores efficiently discriminate nitroarene-based explosives and pollutants.

Discrimination of nitroarenes with hydrophobic dyes in a polar (H2O) environment is difficult but possible via a lab-on-chip, with polymeric dyes immobilized on paper or nylon membranes. Here arrays of 12 hydrophobic poly(p-phenyleneethynylene)s (PPEs), are assembled into a chemical tongue to detect/discriminate nitroarenes in water. The changes in fluorescence image of the PPEs when interacting with solutions of the nitroarenes were recorded and converted into color difference maps, followed by cluster analysis methods. The variable selection method for both paper and nylon devices selects a handful of PPEs at different pH-values that discriminate nitroaromatics reliably. The paper-based chemical tongue could accurately discriminate all studied nitroarenes whereas the nylon-based devices represented distinguishable optical signature for picric acid and 2,4,6-trinitrotoluene (TNT) with high accuracy.

Rapid determination of hippuric acid as an exposure biomarker of toluene using a colorimetric assay and comparison with high-performance liquid chromatography.

Occupational exposure to toluene is associated with health risks that require reliable monitoring methods. Hippuric acid (HA), a urinary metabolite of toluene, serves as a valuable biomarker for such exposure. Colorimetric methods for the quantitative determination of HA have gained prominence due to their simplicity, cost-effectiveness, and suitability for field application. In the present study, a simple colorimetric technique was optimized for the determination of HA in the urine sample, and compared with a usual HPLC technique. The central composite design (CCD) was applied to examine the effective parameters on the colorimetric determination of HA. The calibration curve for HA was established within the concentration range of 6 to 100 mg L-1 with R2 = 0.97. The detection limit (LOD) and quantification limit (LOQ) were determined to be 1.8 mg L-1 and 6 mg L-1 respectively. The relative standard deviation (RSD%) was less than 5%, and the recovery% (R%) was 90.5-100.1. The overall results showed good agreement between the colorimetric and HPLC results. There was a significant relationship between the results obtained from HPLC and colorimetric methods especially for higher concentration levels of HA (≥ 500 mg/g creatinine). In conclusion, our optimized colorimetric method is a simple, cost-effective, and rapid method for determination of HA in occupational exposure, which is comparable with the HPLC technique.

Pronounced effect of lamination on plasma separation from whole blood by microfluidic paper-based analytical devices.

Many diseases are detected through blood tests. Currently, most blood tests are done on plasma instead of whole blood because of the interference of blood cells on detection results. Here, we developed a laminated microfluidic paper-based analytical device (L-µPAD) for the separation of plasma from whole blood without using plasma separation membrane (PSM). A lateral flow design consisting of a circular sampling zone and rectangular detection zone was patterned on the paper substrate using laser printing technology. The µPAD was then laminated after impregnation with KCl solution. Lamination and electrolyte addition represented synergistic effects on the separation by controlling the pore size of the paper. In addition, by preventing evaporation on one hand and squeezing paper pores on the other hand, lamination caused longer movement of the separated plasma, the longest plasma path reported so far. The separation process was monitored using colorimetric reagent bromocresol green and scanning electron microscopy. The process of separation was completed in less than 90s without significant hemolysis and the separated plasma was far from the interfering effect of red blood cells. We used the device for the determination of serum albumin. However, it represents the potential for point-of-care testing in multi-assay experiments too.

A paper-based chemical tongue based on the charge transfer complex of ninhydrin with an array of metal-doped carbon dots discriminates natural amino acids and several of their enantiomers.

Simultaneous detection of multiple amino acids (AAs) instead of individual AAs is inherently worthwhile for improving diagnostic accuracy in clinical applications. Here, a facile and reliable colorimetric microfluidic paper-based analytical device (µPAD) using carbon dots doped with transition metals (Cr3+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+, and Zn2+) has been provided to detect and discriminate 20 natural amino acids. To make the colourless metal-doped carbon dots suitable for colorimetric assays, they were mixed with ninhydrin to form a charge transfer complex. This optical tongue system, which was constructed by dropping mixtures of ninhydrin with a series of metal-doped carbon dots on a paper substrate in an array format, represented obvious but different colorimetric signatures for every examined amino acid. Since bovine serum albumin was used as a chiral selector reagent for synthesizing the CDs, the sensor device represented excellent selectivity to identify enantiomeric species of AAs. This is the first optical array device that can simultaneously discriminate AAs and several of their enantiomers. We employed various statistical and chemometric methods to analyze the digital data library collected by Image J software, including principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA). Twenty AAs could be well distinguished at various concentrations (10.00, 5.00, 2.50, and 1.25 mM). The colorimetric patterns were highly repeatable and were characteristic of individual AAs. Besides qualitative analysis, the designed µPAD-based optical tongue represented quantitative analysis ability, e.g., for lysine in the concentration ranges of 0.005-20.0 mM with a detection limit of 1.0 × 10-6 M and for arginine in the concentration range of 0.12-20.00 mM with a detection limit of 80.0 × 10-6 M. In addition, the binary, ternary, and quaternary mixtures of AAs could also be well recognized with this sensor.

A Paper-Based Biomimetic Sensing Device for the Discrimination of Original and Fraudulent Cigarette Brands Using Mixtures of MoS2 Quantum Dots and Organic Dyes.

In this study, we investigated the combined effects of MoS2 QDs' catalytic properties and the colorimetric responses of organic reagents to create a sniffing device based on the sensor array concept of the mammalian olfactory system. The aim was to differentiate the volatile organic compounds (VOCs) present in cigarette smoke. The designed optical nose device was utilized for the classification of various cigarette VOCs. Unsupervised Principal Component Analysis (PCA) and supervised Linear Discriminant Analysis (LDA) methods were employed for data analysis. The LDA analysis showed promising results, with 100% accuracy in both training and cross-validation. To validate the sensor's performance, we assessed its ability to discriminate between five cigarette brands, achieving 100% accuracy in the training set and 82% in the cross-validation set. Additionally, we focused on studying four popular Iranian cigarette brands (Bahman Kootah, Omega, Montana Gold, and Williams), including fraudulent samples. Impressively, the developed sensor array achieved a perfect 100% accuracy in distinguishing these brands and detecting fraud. We further analyzed a total of 126 cigarette samples, including both original and fraudulent ones, using LDA with a matrix size of (126 × 27). The resulting LDA model demonstrated an accuracy of 98%. Our proposed analytical procedure is characterized by its efficiency, affordability, user-friendliness, and reliability. The selectivity exhibited by the developed sensor array positions it as a valuable tool for differentiating between original and counterfeit cigarettes, thus aiding in border control efforts worldwide.

Microfluidic paper and thread-based separations: Chromatography and electrophoresis.

Paper and thread are widely used as the substrates for fabricating low-cost, disposable, and portable microfluidic analytical devices used in clinical, environmental, and food safety monitoring. Concerning separation methods including chromatography and electrophoresis, these substrates provide unique platforms for developing portable devices. This review focuses on summarizing recent research on the miniaturization of the separation techniques using paper and thread. Preconcentration, purification, desalination, and separation of various analytes are achievable using electrophoresis and chromatography methods integrated with modified or unmodified paper/thread wicking channels. A variety of 2D and 3D designs of paper/thread platforms for zone electrophoresis, capillary electrophoresis, and modified/unmodified chromatography are discussed with emphasis on their limitation and improvements. The current progress in the signal amplification strategies such as isoelectric focusing, isotachophoresis, ion concentration polarization, isoelectric focusing, and stacking methods in paper-based devices are reviewed. Different strategies for chromatographic separations based on paper/thread will be explained. The separation of target species from complex samples and their determination by integration with other analytical methods like spectroscopy and electrochemistry are well-listed. Furthermore, the innovations for plasma and cell separation from blood as an important human biofluid are presented, and the related paper/thread modification methods are explored.

Intercalative binding of two new five-coordinated anticancer Pt(II) complexes to DNA: experimental and computational approaches.

Binding interaction of two organoplatinum complexes, [Pt(C^N)Cl(dppa)], 1, and [Pt(C^N)Cl(dppm)], 2, (C^N = N(1), C(2')-chelated, deprotonated 2-phenylpyridine, dppa = bis(diphenylphosphino)amine, dppm = bis(diphenylphosphino)methane), as anti-tumor agents, with calf thymus DNA (CT-DNA) under pseudo-physiological conditions has been investigated using various biophysical techniques viz., UV-Vis and fluorescence spectroscopies, viscosity measurements, and thermal denaturation experiments. A hypochromic shift in UV-Vis absorption titration, fluorescence enhancement of Pt(II) complexes in the presence of CT-DNA, fluorescence quenching in competitive ethidium bromide displacement assay, and an uptrend in the viscosity (η) and melting temperature (Tm) indicated the existence of a tight intercalative interaction of Pt(II) complexes with CT-DNA. The fluorescence quenching of CT-DNA was a combined quenching of static and dynamic with Stern-Volmer quenching constants of 7.520 × 103 M-1 for complex 1 and 5.183 × 103 M-1 for complex 2, at low concentrations of Pt(II) complexes. Besides the experimental studies, computational studies were done. Molecular modeling studies confirmed the intercalation of the studied complexes by the phenyl groups of dppa and dppm, leading to π-π interactions but with a certain steric hindrance because of the size and shape of the considered complexes. The combination of experimental and computational data showed that reported Pt(II) complexes are promising structures and could be developed for cancer therapeutic applications.Communicated by Ramaswamy H. Sarma.

Colorimetric determination of peroxide value in vegetable oils using a paper based analytical device.

Peroxide value (PV) is one of the most typically used quality parameters to monitor lipid oxidation. Here, a simple paper-based analytical device (PAD) has been developed to determine PV in vegetable oils. The analysis is based on setting up the iodometric titration, where hydroperoxides in the oil are reacted with excess iodide ions to generate iodine molecules, on the paper substrate. The device is composed of two paper layers acting as reaction and detection zones, aligned in a metallic mold. A well-defined inverse logarithmic calibration curve was established between the measured PV by the official iodometric method (ISO;3960, 2017) and the color intensity of PAD. It offered a working range of 0.01-30.0 meq/Kg. The limit of detection of 0.015 meq/Kg demonstrated enough sensitivity of the method to estimate peroxide value in edible oils. On-site and visual detection, low cost, simplicity, and less solvent consumption are advantages of the proposed device.

A poly(arylene ethynylene)-based microfluidic fluorescence sensor array for discrimination of polycyclic aromatic hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are persistent contaminants in the environment. Several of them have carcinogenic properties. There is considerable interest in their sensitive low-cost detection and monitoring. We present a simple paper-based microfluidic sensor for the rapid detection of PAHs. Craft punch patterning generated multiple detection zones inhabited by fluorescent poly(arylene ethynylene)s (PAEs). Changes in fluorescence image and/or intensity of the sensor array were recorded using a smartphone camera. The RGB color values of the photographed images were extracted through ImageJ software. 10 different PAHs were correctly identified using Principal Component Analysis and discrimination analysis (PCA-DA). 100% classification accuracy was achieved for model training, whereas validating the PCA-DA model by cross-validation resulted in 93% classification accuracy for 5.0 mg L-1 analyte.

Paper-Based Optical Nose Made with Bimetallic Nanoparticles for Monitoring Ignitable Liquids in Gasoline.

A paper-based optical nose was fabricated by dropping bimetallic silver and gold nanoparticles on a paper substrate. The nanoparticles were synthesized by both natural (lemon, pomegranate, and orange juices) and chemical (citrate, gallic acid, and ascorbic acid) reducing agents. The performance of the assay was evaluated for identifying gasoline and five ignitable liquids such as diesel, ethanol, methanol, kerosene, and thinner. The interaction of the sensor with sample vapors caused aggregation, consequently changing the color of nanoparticles. The color changes, which were captured by a scanner, represented a specified colorimetric map for each analyte, allowing one to identify the studied fuels. The visual results were confirmed using multivariate statistical analysis such as principal component analysis and hierarchical clustering analysis. Also, partial least-squares regression was used to assist the proposed assay for estimating the amount of studied ignitable liquids as counterfeit species in the gasoline sample. The root-mean-square errors for prediction were 3.4, 2.1, 1.9, 2.0, and 1.7% for diesel, thinner, kerosene, ethanol, and methanol, respectively. Finally, the fabricated sensor indicated high efficiency for the on-site detection of pure industrial gasoline samples from adulterated ones.

Detection and discrimination of antibiotics in food samples using a microfluidic paper-based optical tongue.

Antibiotics are used largely in agriculture and animal farming. As a result, antibiotic residues are found in food products as well as pharmaceutical industries and farming wastes. Since consumption of food products contaminated with antibiotic in excessive residuals causes severe environmental risks, our study here aims to detect the residues level of selected antibiotics in milk and egg. For monitoring of the antibiotic residues in various food diaries, low-cost, simple and rapid methods are required. This paper reports fabricating a disposable microfluidic paper-based analytical device for detection and discrimination of 8 antibiotics. This small but efficient device works based on combination of paper microfluidics, sensor array concept (an array of metallochromic complexes, which provides an optical tongue, and chemometrics data analysis. The discrimination is based on differential interaction of the antibiotics with 5 metal-indicator complexes and displacing the chromogenic indicators. This resulted in specific color changes for each antibiotic. The discriminant models obtained by employing linear discriminant analysis could discriminate antibiotics in real samples of milk and egg white and yolk at concentrations of as low as 5.0 mg L-1 with 100% accuracy. Also, semi-quantitative analysis was provided to detect trace amounts of the antibiotics (1.0 mg L-1).

Converting electronic nose into opto-electronic nose by mixing MoS2 quantum dots with organic reagents: Application to recognition of aldehydes and ketones and determination of formaldehyde in milk.

A new colorimetric sensor array based on mixing of Molybdenum disulfide quantum dots (MoS2 QDs) and organic reagents is introduced in this study. MoS2 QDs shows a specific and higher affinity to oxygen functionalized volatile compounds like aldehydes and ketones. Therefore, this designed sensor array is used for classification of eight different aldehydes and ketones based on Linear Discriminate Analysis (LDA) at first. The classification accuracy of 96% and 83% was obtained for training and prediction phases, respectively. Then the introduced colorimetric sensor array is used for the semi-quantitative and quantitative analysis of formaldehyde in milk samples. Formaldehyde is an adulteration that is added to the milk for increasing the storage time. Cow milk samples were provided directly from dairy farmer and from supermarkets and were spiked by formaldehyde in the concentration range of 1-25 ppm. The response of sensor array to these samples were analyzed by partial least squares regression (PLS-R) method and were calibrated for concentration of formaldehyde. The PLSR results (R2 = 0.94 and RMSEC = 2.36) shows that proposed sensor is useable in direct analysis of formaldehyde in milk as a complex matrix.

Evaluation of adulteration in distillate samples of Rosa damascena Mill using colorimetric sensor arrays, chemometric tools and dispersive liquid-liquid microextraction-GC-MS.

INTRODUCTION: Rosa damascena Mill distillate and its essential oil are widely used in cosmetics, perfumes and food industries. Therefore, the methods of detection for its authentication is an important issue. OBJECTIVES: We suggest colorimetric sensor array and chemometric methods to discriminate natural Rosa distillate from synthetic adulterates. MATERIAL AND METHODS: The colour responses of 20 indicators spotted on polyvinylidene fluoride (PVDF) substrate were monitored with a flatbed scanner; then their digital representation was analysed with principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA). RESULTS: Accurate discrimination of the diluted- and synthetic-mixture samples from the original ones was achieved by PLS-DA and SIMCA models with error rate of 0.01 and 0, specificity of 0.98 and 1, sensitivity of 1 and 1, and accuracy of 0.98 and 0.96, respectively. Discrimination of the synthetic adulterate from the original samples was achieved with error rate of 0.03 and 0.03, specificity of 0.94 and 0.93, sensitivity of 1 and 1, and accuracy of 0.93 and 0.71 with PLS-DA and SIMCA models, respectively. Moreover, the chemical constituents of the samples were analysed using dispersive liquid-liquid microextraction and gas chromatography-mass spectrometry (GC-MS). The main constituents of the distillate were geraniol, citronellol, and phenylethyl alcohol in different percentages, in both original and synthetic adulterate samples. CONCLUSION: These results point out the successful combination of colorimetric sensor array and PLS-DA and SIMCA as a fast, sensitive and inexpensive screening tool for discrimination of original samples of R. damascena Mill distillate from those prepared from synthetic Rosa essential oils.

An All-in-One Solid State Thin-Layer Potentiometric Sensor and Biosensor Based on Three-Dimensional Origami Paper Microfluidics.

An origami three-dimensional design of a paper-based potentiometric sensor is described. In its simplest form, this electrochemical paper-based analytical device (ePAD) is made from three small parts of the paper. Paper layers are folded on each other for the integration of a solid contact ion selective electrode (here a carbon-paste composite electrode) and a solid-state pseudo-reference electrode (here writing pencil 6B on the paper), which are in contact with a hydrophilic channel fabricated on the middle part (third part) of the paper. In this case, the pseudo-reference and working electrodes are connected to the two sides of the hydrophilic channel and hence the distance between them is as low as the width of paper. The unmodified carbon paste electrode (UCPE) and modification with the crown ether benzo15-crown-5 (B15C5) represented a very high sensitivity to Cu (II) and Cd2+ ions, respectively. The sensor responded to H2O2 using MnO2-doped carbon paste electrode (CPE). Furthermore, a biosensor was achieved by the addition of glucose oxidase to the MnO2-doped CPE and hence made it selective to glucose with ultra-sensitivity. In addition to very high sensitivity, our device benefits from consuming a very low volume of sample (10.0 µL) and automatic sampling without need for sampling devices.

Fluorescent Carbon Dots Prepared from Hazelnut Kohl as an Affordable Probe for Determination of Dopamine.

In this investigation, a simple, green and facile fluorescence mrtod using carbon dots (CDs) of hazelnut kohl is described for selective detection of dopamine (DA). The sensing system is based on hazelnut kohl (the black soot of kohl) which is used as a carbon source. Generally, kohl is a traditional eye cosmetic that used in different parts of the world and synthesized by the combustion process like burning natural materials. Here, it has been proven that black soot (kohl) obtained from hazelnut has a carbon dot structure and can be used for sensory applications. Some characterization methods are carried out to reveal the kohl structure. Also, the photoluminescence properties of the prepared CDs of kohl are investigated. It is found that the size of CDs is 2-4 nm. Besides, under the optimal conditions, the fluorescence of CDs is used for DA determination. CDs fluorescence intensity is decreased linearly with the increase of DA concentration. By using the fluorescence dependency toward the DA concentration, DA can be determined in the range 0.5-30 µM with the limit of detection of 0.30 µM. Finally, this method is successfully applied to discriminate the DA in the real samples (healthy human serum and cerebrospinal fluid (CSF)) which shows acceptable efficiently for diagnostic purposes. The fluorescence of carbon dots, prepared from Hazelnut Kohl, is quenched in the presence of dopamine.

Chemometrics-based LC-UV-ESIMS analyses of 50 Salvia species for detecting their antioxidant constituents.

Iran is one of the main hubs for sage's diversity in Asia. Generally, prediction and characterization of the chemical structures of the specialized metabolites that have significant role in the bioactivity of a plant remains a significant challenge. In this study, 50 different accessions of 32 Salvia species in 2015 and 2017 were collected and extracted for their phenolics, using 80 % methanol. LC-PDA-ESIMS analyses was coupled with multivariate analysis to identify the specific metabolites in the plant extracts, responsible for the antioxidant activity. Based on the variable importance in projection (VIP) method on the Genetic algorithm combined with PLS (GA-PLS) models, eighteen peaks were detected as multifunctional compounds. The putative phenolic compounds were attributed to apigenin-O-diglucoside, rutin, cynaroside, luteolin-7-O-glucoronide, apigenin-7-O-glucoside, apigenin-7-O-glucuronide, hispidulin-7-O-glucuronide, hispidulin-7-O-glucoside, rosmarinic acid, salvianolic acid B derivative, cirsimaritin, eupatorin, and carnosol. This investigation showed that the Salvia's extract can facilitate an opportunity for rapid detection, isolation and development of antioxidant agents.

A non-invasive tool for early detection of acute leukemia in children using a paper-based optoelectronic nose based on an array of metallic nanoparticles.

Volatile organic compounds (VOCs) in blood samples can be used as useful biomarkers to diagnose various human diseases. This study describes the potential of a paper-based sensor array for detecting leukemia using blood VOCs. Blood samples were collected from 59 new leukemia cases and 47 healthy cases as a control group. Each blood sample was divided into two parts; one for a laboratory test and the other was used in our study. Samples were mixed with heparin and then transferred to a sterile container, and a sensor was stacked on its cap. This sensor array contains 16 nanoparticles deposited on a sheet of hydrophobic paper in a 4 × 4 array format. Containers were stored in an oven at 60 °C for 4.5 h. Then, the image of sensors was recorded by a scanner and compared to the image before exposing the blood vapor. The sensor responses were subjected to different multivariate statistical methods to develop models that discriminate between control and leukemia samples. The interaction of nanoparticles with the volatile metabolome of blood caused aggregation and consequently changing in the color of nanoparticles. The color changes resulted in a specific pattern for blood samples with leukemia, which is different from those obtained from healthy specimens. The discrimination analysis was approved by pattern recognition methods such as principal component analysis with 97% accuracy. Among 59 patients, the mean age was 6.02 ± 4.55 years (range 1-16 y). The mean total response was 652.83 ± 117.02. The rock curve showed an accuracy of 96% for classifying patients from the control group. The logistic regression model showed that 93.6% of healthy and 93.2% of patients were classified correctly by using this method. These statistics agree with the classification results obtained by principal component analysis. For every 5000-unit increase in platelet count, the chance of leukemia decreased by 9%. Additionally, the chance of being categorized as a patient decreased by 10% for every 20-unit increase in total response. The electronic nose using VOC's of blood is a non-invasive and inexpensive tool for detecting new cases of leukemia with high sensitivity and specificity. Platelet count is an essential para-clinical parameter determining the total response of the sensors. Follow up studies with a larger sample size are warranted to elucidate its clinical applicability.

A paper-based colorimetric sensor array for discrimination of monofloral European honeys based on gold nanoparticles and chemometrics data analysis.

A sensitive and simple nanomaterial based colorimetric sensor array (NBCSA) was developed for discrimination of monofloral honey from various European countries based on three botanical origins as Acacia, Canola and Honeydew. The NBCSA was designed by spotting gold (AuNPs) and silver (AgNPs) nanoparticles synthesized using six different reducing and/or capping agents. The colour intensity of AuNPs represented differential changes when interacting with volatile organic compounds appeared in the headspace of the honey samples. The color difference maps, which are calculated as the difference between color intensity of the sensor before and after exposing to the sample vapors, were used as a fingerprint to discriminate the honey samples based on botanical origin. Classification was achieved utilizing data pre-processing and chemometrics data analysis. Fitting accuracies of 88% and 86% were obtained by partial least squares discriminant analysis and linear discriminant analysis whereas 100% was achieved using support vector machine.

A 3D origami paper-based analytical device combined with PVC membrane for colorimetric assay of heavy metal ions: Application to determination of Cu(II) in water samples.

Microfluidic paper-based analytical devices (µPADs) as a potentially powerful analytical platform have recently gained significant attention for on-site monitoring of heavy metal ions, which are one of the most significant environmental concern because of non-degradability and high toxicity. The commonly applied µPADs suffers from some defects, such as heterogeneous deposition of reagent, resulting in poor detection limits and low sensitivity. So, in this work, a three-dimensional origami µPAD combined with PVC Membrane was developed, which can manage problems of movement of colored products or leaching out the dye and leading to color heterogeneity in the detection zones. Furthermore, a waste layer was added to µPAD for loading of more amounts of the analyte, which results in improvement of detection limit. As a proof of concept, the µPAD was used for the analysis of Cu2+ ion. For this purpose, pyrocatechol violet and chrome azurol S as colorimetric reagents were doped into PVC membrane and injected in the detection zone. The proposed µPAD was presented good linearity in the ranges of 5.0-1400.0 and 5.0-200.0 mg L-1, and the limits of detections of 1.7 and 1.9 mg L-1 in presence of chrome azurol S and pyrocatechol violet, respectively.