Optoelectronic nose based on an origami paper sensor for selective detection of pesticide aerosols

Nanoplasmonic biosensors for environmental sustainability and human health

Monitoring the health conditions of the environment and humans is essential for ensuring human well-being, promoting global health, and achieving sustainability. Innovative biosensors are crucial in accurately monitoring health conditions, uncovering the hidden connections between the environment and human well-being, and understanding how environmental factors trigger autoimmune diseases, neurodegenerative diseases, and infectious diseases. This review evaluates the use of nanoplasmonic biosensors that can monitor environmental health and human diseases according to target analytes of different sizes and scales, providing valuable insights for preventive medicine. We begin by explaining the fundamental principles and mechanisms of nanoplasmonic biosensors. We investigate the potential of nanoplasmonic techniques for detecting various biological molecules, extracellular vesicles (EVs), pathogens, and cells. We also explore the possibility of wearable nanoplasmonic biosensors to monitor the physiological network and healthy connectivity of humans, animals, plants, and organisms. This review will guide the design of next-generation nanoplasmonic biosensors to advance sustainable global healthcare for humans, the environment, and the planet.

OriPlex: Origami-enabled multiplexed detection of respiratory pathogens

Origami biosensors leverage paper foldability to develop total analysis systems integrated in a single piece of paper. This capability can also be utilized to incorporate additional features that would be difficult to achieve with rigid substrates. In this article, we report a new design for 3D origami biosensors called OriPlex, which leverages the foldability of filter paper for the multiplexed detection of bacterial pathogens. OriPlex immunosensors detect pathogens by folding nanoparticle reservoirs containing different types of nanoprobes. This releases antibody-coated nanoparticles in a central channel where targets are captured through physical interactions. The OriPlex concept was demonstrated by detecting the respiratory pathogens Pseudomonas aeruginosa (PA) and Klebsiella pneumoniae (KP) with a limit of detection of 3.4·103 cfu mL-1 and 1.4·102 cfu mL-1, respectively, and with a turn-around time of 25 min. Remarkably, the OriPlex biosensors allowed the multiplexed detection of both pathogens spiked into real bronchial aspirate (BAS) samples at a concentration of 105 cfu mL-1 (clinical infection threshold), thus demonstrating their suitability for diagnosing lower tract respiratory infections. The results shown here pave the way for implementing OriPlex biosensors as a screening test for detecting superbugs requiring personalized antibiotics in suspected cases of nosocomial pneumonia.

Monitoring saliva compositions for non-invasive detection of diabetes using a colorimetric-based multiple sensor

The increasing population of diabetic patients, especially in developing countries, has posed a serious risk to the health sector, so that the lack of timely diagnosis and treatment process of diabetes can lead to threatening complications for the human lifestyle. Here, a multiple sensor was fabricated on a paper substrate for rapid detection and controlling the progress of the diabetes disease. The proposed sensor utilized the sensing ability of porphyrazines, pH-sensitive dyes and silver nanoparticles in order to detect the differences in saliva composition of diabetic and non-diabetic patients. A unique color map (sensor response) was obtained for each studied group, which can be monitored by a scanner. Moreover, a good correlation was observed between the colorimetric response resulting from the analysis of salivary composition and the fasting blood glucose (FBG) value measured by standard laboratory instruments. It was also possible to classify participants into two groups, including patients caused by diabetes and those were non-diabetic persons with a total accuracy of 88.9%. Statistical evaluations show that the multiple sensor can be employed as an effective and non-invasive device for continuous monitoring of diabetes, substantially in the elderly.

Advancement in Paper-Based Electrochemical Biosensing and Emerging Diagnostic Methods

The utilization of electrochemical detection techniques in paper-based analytical devices (PADs) has revolutionized point-of-care (POC) testing, enabling the precise and discerning measurement of a diverse array of (bio)chemical analytes. The application of electrochemical sensing and paper as a suitable substrate for point-of-care testing platforms has led to the emergence of electrochemical paper-based analytical devices (ePADs). The inherent advantages of these modified paper-based analytical devices have gained significant recognition in the POC field. In response, electrochemical biosensors assembled from paper-based materials have shown great promise for enhancing sensitivity and improving their range of use. In addition, paper-based platforms have numerous advantageous characteristics, including the self-sufficient conveyance of liquids, reduced resistance, minimal fabrication cost, and environmental friendliness. This study seeks to provide a concise summary of the present state and uses of ePADs with insightful commentary on their practicality in the field. Future developments in ePADs biosensors include developing novel paper-based systems, improving system performance with a novel biocatalyst, and combining the biosensor system with other cutting-edge tools such as machine learning and 3D printing.

Paper-Based Multiplex Sensors for the Optical Detection of Plant Stress

The rising population and the ongoing climate crisis call for improved means to monitor and optimise agriculture. A promising approach to tackle current challenges in food production is the early diagnosis of plant diseases through non-invasive methods, such as the detection of volatiles. However, current devices for detection of multiple volatiles are based on electronic noses, which are expensive, require complex circuit assembly, may involve metal oxides with heating elements, and cannot easily be adapted for some applications that require miniaturisation or limit front-end use of electronic components. To address these challenges, a low-cost optoelectronic nose using chemo-responsive colorimetric dyes drop-casted onto filter paper has been developed in the current work. The final sensors could be used for the quantitative detection of up to six plant volatiles through changes in colour intensities with a sub-ppm level limit of detection, one of the lowest limits of detection reported so far using colorimetric gas sensors. Sensor colouration could be analysed using a low-cost spectrometer and the results could be processed using a microcontroller. The measured volatiles could be used for the early detection of plant abiotic stress as early as two days after exposure to two different stresses: high salinity and starvation. This approach allowed a lowering of costs to GBP 1 per diagnostic sensing paper. Furthermore, the small size of the paper sensors allows for their use in confined settings, such as Petri dishes. This detection of abiotic stress could be easily achieved by exposing the devices to living plants for 1 h. This technology has the potential to be used for monitoring of plant development in field applications, early recognition of stress, implementation of preventative measures, and mitigation of harvest losses.

Mask assistance to colorimetric sniffers for detection of Covid-19 disease using exhaled breath metabolites

According to World Health Organization reports, large numbers of people around the globe have been infected or died for Covid-19 due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Researchers are still trying to find a rapid and accurate diagnostic method for revealing infected people by low viral load with the overriding goal of effective diagnostic management. Monitoring the body metabolic changes is known as an effective and inexpensive approach for the evaluation of the infected people. Here, an optical sniffer is introduced to detect exhaled breath metabolites of patients with Covid-19 (60 samples), healthy humans (55 samples), and cured people (15 samples), providing a unique color pattern for differentiation between the studied samples. The sniffer device is installed on a thin face mask, and directly exposed to the exhaled breath stream. The interactions occurring between the volatile compounds and sensing components such as porphyrazines, modified organic dyes, porphyrins, inorganic complexes, and gold nanoparticles allowing for the change of the color, thus being tracked as the sensor responses. The assay accuracy for the differentiation between patient, healthy and cured samples is calculated to be in the range of 80%-84%. The changes in the color of the sensor have a linear correlation with the disease severity and viral load evaluated by rRT-PCR method. Interestingly, comorbidities such as kidney, lung, and diabetes diseases as well as being a smoker may be diagnosed by the proposed method. As a powerful detection device, the breath sniffer can replace the conventional rapid test kits for medical applications.

Mask assistance to colorimetric sniffers for detection of Covid-19 disease using exhaled breath metabolites

According to World Health Organization reports, large numbers of people around the globe have been infected or died for Covid-19 due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Researchers are still trying to find a rapid and accurate diagnostic method for revealing infected people by low viral load with the overriding goal of effective diagnostic management. Monitoring the body metabolic changes is known as an effective and inexpensive approach for the evaluation of the infected people. Here, an optical sniffer is introduced to detect exhaled breath metabolites of patients with Covid-19 (60 samples), healthy humans (55 samples), and cured people (15 samples), providing a unique color pattern for differentiation between the studied samples. The sniffer device is installed on a thin face mask, and directly exposed to the exhaled breath stream. The interactions occurring between the volatile compounds and sensing components such as porphyrazines, modified organic dyes, porphyrins, inorganic complexes, and gold nanoparticles allowing for the change of the color, thus being tracked as the sensor responses. The assay accuracy for the differentiation between patient, healthy and cured samples is calculated to be in the range of 80%-84%. The changes in the color of the sensor have a linear correlation with the disease severity and viral load evaluated by rRT-PCR method. Interestingly, comorbidities such as kidney, lung, and diabetes diseases as well as being a smoker may be diagnosed by the proposed method. As a powerful detection device, the breath sniffer can replace the conventional rapid test kits for medical applications.

Visual diagnosis of COVID-19 disease based on serum metabolites using a paper-based electronic tongue

This study aims to use a paper-based sensor array for point-of-care detection of COVID-19 diseases. Various chemical compounds such as nanoparticles, organic dyes and metal ion complexes were employed as sensing elements in the array fabrication, capturing the metabolites of human serum samples. The viral infection caused the type and concentration of serum compositions to change, resulting in different color responses for the infected and control samples. For this purpose, 118 serum samples of COVID-19 patients and non-COVID controls both men and women with the age range of 14–88 years were collected. The serum samples were initially subjected to the sensor, followed by monitoring the variation in the color of sensing elements for 5 min using a scanner. By taking into consideration the statistical information, this method was capable of discriminating COVID-19 patients and control samples with 83.0% accuracy. The variation of age did not influence the colorimetric patterns. The desirable correlation was observed between the sensor responses and viral load values calculated by the PCR test, proposing a rapid and facile way to estimate the disease severity. Compared to other rapid detection methods, the developed assay is cost-effective and user-friendly, allowing for screening COVID-19 diseases reliably.

Non-invasive detection of COVID-19 using a microfluidic-based colorimetric sensor array sensitive to urinary metabolites

A colorimetric sensor array designed on a paper substrate with a microfluidic structure has been developed. This array is capable of detecting COVID-19 disease by tracking metabolites of urine samples. In order to determine minor metabolic changes, various colorimetric receptors consisting of gold and silver nanoparticles, metalloporphyrins, metal ion complexes, and pH-sensitive indicators are used in the array structure. By injecting a small volume of the urine sample, the color pattern of the sensor changes after 7 min, which can be observed visually. The color changes of the receptors (recorded by a scanner) are subsequently calculated by image analysis software and displayed as a color difference map. This study has been performed on 130 volunteers, including 60 patients infected by COVID-19, 55 healthy controls, and 15 cured individuals. The resulting array provides a fingerprint response for each category due to the differences in the metabolic profile of the urine sample. The principal component analysis-discriminant analysis confirms that the assay sensitivity to the correctly detected patient, healthy, and cured participants is equal to 73.3%, 74.5%, and 66.6%, respectively. Apart from COVID-19, other diseases such as chronic kidney disease, liver disorder, and diabetes may be detectable by the proposed sensor. However, this performance of the sensor must be tested in the studies with a larger sample size. These results show the possible feasibility of the sensor as a suitable alternative to costly and time-consuming standard methods for rapid detection and control of viral and bacterial infectious diseases and metabolic disorders.

Surfactant stabilized gold nanomaterials for environmental sensing applications - A review

Surfactant stabilized Gold (Au) nanomaterials (NMs) have been documented extensively in recent years for numerous sensing applications in the academic literature. Despite the crucial role these surfactants play in the sensing applications, the comprehensive reviews that highlights the fundamentals associated with these assemblies and impact of these surfactants on the properties and sensing mechanisms are still quite scare. This review is an attempt in organizing the vast literature associated with this domain by providing critical insights into the fundamentals, preparation methodologies and sensing mechanisms of these surfactant stabilized Au NMs. For the simplification, the surfactants are divided into the typical and advanced surfactants and the Au NMs are classified into Au nanoparticles (NPs) and Au nanoclusters (NCs) depending upon the complexity in structure and size of the NMs respectively. The preparative methodologies are also elaborated for enhancing the understanding of the readers regarding such assemblies. The case studies regarding surfactant stabilized Au NMs were further divided into colorimetric sensors, surface plasmonic resonance (SPR) based sensors, luminescence-based sensors, and electrochemical/electrical sensors depending upon the property utilized by the sensor for the sensing of an analyte. Future perspectives are also discussed in detail for the researchers looking for further progress in that particular research domain.

A colorimetric electronic tongue for point-of-care detection of COVID-19 using salivary metabolites

The monitoring of profile concentrations of chemical markers in saliva samples can be used to diagnose COVID-19 patients, and differentiate them from healthy individuals. Here, this purpose is achieved by designing a paper-based colorimetric sensor with an origami structure, containing general receptors such as pH-sensitive organic dyes, Lewis donors or acceptors, functionalized nanoparticles, and ion metal complexes. The color changes taking place in the receptors in the presence of chemical markers are visually observed and recorded with a digital instrument. Different types and amounts of the chemical markers provide the sensor with a unique response for patients (60 samples) or healthy (55 samples) individuals. These two categories can be discriminated with 84.3% accuracy. This study evidences that the saliva composition of cured and healthy participants is different from each other with accuracy of 85.7%. Moreover, viral load values obtained from the rRT-PCR method can be estimated by the designed sensor. Besides COVID-19, it may possible to simultaneously identify smokers and people with kidney disease and diabetes using the specified electronic tongue. Due to its high efficiency, the prepared paper device can be employed as a rapid detection kit to detect COVID-19.

Starch/Polyaniline Biopolymer Film as Potential Intelligent Food Packaging with Colourimetric Ammonia Sensor

The use of petroleum-based plastics in food packaging leads to various environmental impacts, while spoilage of food and misinterpretation of food-date labelling account for food insecurity; therefore, a biopolymer capable of indicating food edibility is prepared to resolve these issues. In this research, starch/polyaniline (starch/PANI) biopolymer film was synthesised and investigated as an ammonia sensor for potential application as intelligent food packaging. FT-IR and XRD were used to confirm the composition of the biopolymer films, while UV-Vis spectrometry was applied to identify the oxidation state of PANI in emeraldine form. PANI was successfully incorporated into the starch matrix, leading to better thermal stability (TGA) but decreasing the crystallinity of the matrix (DSC). The performance of the polymer-film sensor was determined through ammonia-vapour sensitivity analysis. An obvious colour change from green to blue of starch/PANI films was observed upon exposure to the ammonia vapour. Starch/PANI 0.4% is the optimum composition, having the best sensor performance with good linearity (R2 = 0.9459) and precision (RSD = 8.72%), and exhibiting excellent LOD (245 ppm). Furthermore, the starch/PANI films are only selective to ammonia. Therefore, the starch/PANI films can be potentially applied as colourimetric ammonia sensors for intelligent food packaging.

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.

Disposable Paper-Based Biosensors for the Point-of-Care Detection of Hazardous Contaminations-A Review

The fast detection of trace amounts of hazardous contaminations can prevent serious damage to the environment. Paper-based sensors offer a new perspective on the world of analytical methods, overcoming previous limitations by fabricating a simple device with valuable benefits such as flexibility, biocompatibility, disposability, biodegradability, easy operation, large surface-to-volume ratio, and cost-effectiveness. Depending on the performance type, the device can be used to analyze the analyte in the liquid or vapor phase. For liquid samples, various structures (including a dipstick, as well as microfluidic and lateral flow) have been constructed. Paper-based 3D sensors are prepared by gluing and folding different layers of a piece of paper, being more user-friendly, due to the combination of several preparation methods, the integration of different sensor elements, and the connection between two methods of detection in a small set. Paper sensors can be used in chromatographic, electrochemical, and colorimetric processes, depending on the type of transducer. Additionally, in recent years, the applicability of these sensors has been investigated in various applications, such as food and water quality, environmental monitoring, disease diagnosis, and medical sciences. Here, we review the development (from 2010 to 2021) of paper methods in the field of the detection and determination of toxic substances.

Highly specific fingerprinting of alkaline earth metal ions by a tunable plasmonic nanosensor array based on nanoaggregation of metallochromic dyes-AuNPs

Metal ions, specifically alkaline earth metal ions (AEMIs; Mg²⁺, Ca²⁺, Sr²⁺, and Ba²⁺), have essential roles in industrial processes, medical testing, and environmental evaluation; therefore, developing sensitive detection methods capable of their contents is highly required. To this aim, we have designed an absorbance nanosensor array using three metallochromic dyes decorated on AuNPs and have monitored variations in AuNP plasmonic profiles upon the addition of AEMIs in different buffer and pH solutions. The array is designed in a tunable size of 2 × 3 × 1(2/3); as the type buffer and pH of solution are fixed, the number of dyes can be changed in three individual modes, three binary modes, and a ternary mode, respectively. Owing to the different binding affinities of AEMIs toward dyes in different buffer and pH solutions, fingerprint-like plasmonic profiles with different levels of aggregation AuNPs were generated for all modes of array. These aggregation AuNP-based fingerprint profiles in the wavelengths of 500, 525, 550, 575, 600, 625, 650, 675, 700, 725, and 750 nm were used to discriminate the AEMIs by applying pattern recognition methods including linear discrimination analysis (LDA) and hierarchical clustering analysis (HCA) to identify each AEMI in the range 2.1-24.7 μM. Accordingly, limits of detection (LODs) values of 0.013 (±3.13), 0.014 (±2.99), 0.020 (±4.17), and 0.017 (±4.31) μM were obtained the Mg²⁺, Ca²⁺, Sr²⁺, and Ba²⁺, respectively. The results revealed that all the modes of array could well differentiate complex mixtures of the AEMIs. Our suggested array also exhibited a good performance in the differentiation of AEMIs in real samples and a certified reference material (CRM) sample.

A novel electronic nose for the detection and classification of pesticide residue on apples

Excessive pesticide residues are a serious problem faced by food regulatory authorities, suppliers, and consumers. To assist with this challenge, this work aimed to develop a method of detecting and classifying pesticide residue on fruit samples using an electronic nose, through the application of three different data-recognition algorithms. The apple samples carried various concentrations of two known pesticides, namely cypermethrin and chlorpyrifos. Data collection was performed using a PEN3 electronic nose equipped with 10 metal oxide semiconductor (MOS) sensors. In order to classify and analyze these pesticide residues on the apple samples, principal component analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) results were combined with sensor output responses to realize MOS sensor array data visualization. The results indicated that all three data-recognition algorithms accurately identified the pesticide residues in the apple samples, with the PCA algorithm exhibiting the best classification and discrimination ability. Consequently, this work has shown that the MOS electronic nose, in combination with data-recognition algorithms, can provide support for the rapid and non-destructive identification of pesticide residues in fruits and can provide an effective tool for the detection of pesticide residues in agricultural products.

The MOS electronic nose in combination with data-recognition algorithms can provide an effective tool for the detection of pesticide residues in agricultural products.

Origami paper analytical assay based on metal complex sensor for rapid determination of blood cyanide concentration in fire survivors

Cyanide-based blood poisoning can seriously damage fire victims and cause death if not detected quickly. Previous conventional methods require laboratory equipment, which are expensive and increase the duration of the analysis. Here, a simple origami based microfluidic device was introduced for point of need detection of blood cyanide concentration in people involved in fire. The device is made of four layers of paper. Each layer was in the size of 1 × 1 cm folded on each other. In this work, the blood sample was acidified by trichloroacetic acid to separate cyanide from methaemoglobin in the form of HCN gas. The produced gas released into borate buffer to recover free cyanide ions which interacted with the Pt complex ([Pt(p-MeC₆H₄)₂(phen)]) used as a receptor in this study. Optimized conditions were applied to have a suitable interaction causing the color of the receptor to change from yellow to colorless. The color changes were recorded by a smartphone, and the sensor response was calculated by the routine image analysis software. The assay was capable of determining cyanide ions at different concentrations in the range of 1.0 to 100.0 µmol L⁻¹. The detection limit of these determination was equal to 0.4 µmol L⁻¹. The assay responses were not affected by the interfering species. As a practical analysis, the proposed sensor was applied to determine cyanide ions in the blood sample of 20 studied fire survivors and 10 controls with high accuracy.

A paper-based colorimetric sensor array for discrimination and simultaneous determination of organophosphate and carbamate pesticides in tap water, apple juice, and rice

A colorimetric paper-based sensor is proposed for the rapid monitoring of six major organophosphate and carbamate pesticides. The assay was constructed by dropping gold and silver nanoparticles on the hydrophilic zones of a paper substrate. The nanoparticles were modified by L-arginine, quercetin, and polyglutamic acid. The mechanism of sensing is based on the interaction between the pesticide and the nanoparticles. The color of nanoparticles changed during the interactions. A digital camera recorded these changes. The assay provided a unique response for each studied pesticide. This method can determine six individual pesticides including carbaryl, paraoxon, parathion, malathion, diazinon, and chlorpyrifos. The limit of detection for these pesticides were 29.0, 22.0, 32.0, 17.0, 45.0, and 36.0 ng mL^-1, respectively. The assay was applied to simultaneously determine the six studied pesticides in a mixture using the partial least square method (PLS). The root mean square errors of prediction were 11, 8.7, 9.2, 10, 12, and 11 for carbaryl, paraoxon, parathion, malathion, diazinon, and chlorpyrifos, respectively. The paper-based device can differentiate two types of studied pesticide (organophosphate and carbamate) as well as two types of organophosphate structures (oxon and thion). Furthermore, this sensor showed high selectivity to the pesticides in the presence of other potential species (e.g., metal ions, anions, amino acids, sugar, and vitamins). This assay is capable of determining the pesticide compounds in tap water, apple juice, and rice samples.Graphical abstract.