Colorimetric sensor array based on gold nanoparticles and amino acids for identification of toxic metal ions in water

Colorimetric sensing for translational applications: from colorants to mechanisms

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

Surface-Engineered Nanomaterials for Optical Array Based Sensing

Array based sensing governed by optical methods provides fast and economic way for detection of wide variety of analytes where the ideality of detection processes depends on the sensor element's versatile mode of interaction with multiple analytes in an unbiased manner. This can be achieved by either the receptor unit having multiple recognition moiety, or their surface property should possess tuning ability upon fabrication called surface engineering. Nanomaterials have a high surface to volume ratio, making them viable candidates for molecule recognition through surface adsorption phenomena, which makes it ideal to meet the above requirements. Most crucially, by engineering a nanomaterial's surface, one may produce cross-reactive responses for a variety of analytes while focusing solely on a single nanomaterial. Depending on the nature of receptor elements, in the last decade the array-based sensing has been considering as multimodal detection platform which operates through various pathway including single channel, multichannel, binding and indicator displacement assay, sequential ON-OFF sensing, enzyme amplified and nanozyme based sensing etc. In this review we will deliver the working principle for Array-based sensing by using various nanomaterials like nanoparticles, nanosheets, nanodots and self-assembled nanomaterials and their surface functionality for suitable molecular recognition.

A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

An approach to zwitterionic peptide design for colorimetric detection of the Southampton norovirus SV3CP protease

Noroviruses are highly contagious and are one of the leading causes of acute gastroenteritis worldwide. Due to a lack of effective antiviral therapies, there is a need to diagnose and surveil norovirus infections to implement quarantine protocols and prevent large outbreaks. Currently, the gold standard of diagnosis uses reverse transcription polymerase chain reaction (RT-PCR), but PCR can have limited availability. Here, we propose a combination of a tunable peptide substrate and gold nanoparticles (AuNPs) to colorimetrically detect the Southampton norovirus 3C-like protease (SV3CP), a key protease in viral replication. Careful design of the substrate employs a zwitterionic peptide with opposite charged moieties on the C- and N- termini to induce a rapid color change visible to the naked eye; thus, this color change is indicative of SV3CP activity. This work expands on existing zwitterionic peptide strategies for protease detection by systematically evaluating the effects of lysine and arginine on nanoparticle charge screening. We also determine a limit of detection for SV3CP of 28.0 nM with comparable results in external breath condensate, urine, and fecal matter for 100 nM of SV3CP. The key advantage of this system is its simplicity and accessibility, thus making it an attractive tool for qualitative point-of-care diagnostics.

3-Aminophenylboronic Acid Conjugation on Responsive Polymer and Gold Nanoparticles for Qualitative Bacterial Detection

Background

Because of their sensitive and selective responses to a wide variety of analytes, colorimetric sensors have gained widespread acceptance in recent years. Gold nanoparticles (AuNPs) are widely employed in visual sensor strategies due to their high stability and ease of use. Combining AuNPs with a responsive polymer can result in distinct surface plasmon resonance (SPR) changes that can be utilized as colorimetric biosensors.

Objectives

The purpose of this research is to develop a colorimetric-based sensor through the utilization of the optical properties of gold nanoparticles (AuNPs) crosslinked with pH-responsive polymers poly (acrylic acid) (PAA) conjugated to 3-aminophenyl boronic acid (APBA).

Methods

The polymer (PAA) was synthesized via RAFT polymerization. The inversed Turkevic method was used to produce AuNPs, which were subsequently used in a self-assembly process using poly (acrylic acid)-aminophenyl boronic acid (PAA-APBA) to create the self-assembled AuNPs-APBA-PAA. The particle size, zeta potential, and reversibility of the polymer-modified gold nanoparticles were determined using a transmission electron microscope (TEM), a particle size analyzer (PSA), and an Ultraviolet-Visible spectrophotometer (UV-Vis spectrophotometer). Visual, UV-Vis spectrophotometer and TEM observations confirmed the system's ability to identify bacteria. Statistical analysis was performed using a one-way analysis of variance using Excel software.

Results

Using UV-Vis spectrophotometry, the particle size of AuNPs was determined to be 25.7 nm, and the maximum absorbance occurred at 530 nm. AuNPs PAA APBA colloid exhibited an absorbance maximum of 532 nm, a zeta potential of -41.53, and a pH transition point between 4 and 5. At E. coli concentrations of 4.5 x 107 CFU/mL, the color of the system sensors changed from red to blue after 15 hours of incubation, whereas at S. aureus concentrations of 1.2 x 109 CFU/mL, the color changed to purple immediately after mixing. The TEM confirmed that the detection mechanism is based on the boronate-polyol bonding of saccharides on the outer membranes of Escherichia coli and Staphylococcus aureus.

Conclusions

The use of APBA in conjunction with pH-responsive PAA polymers containing AuNPs to detect E. coli and S. aureus bacteria induces a maximum wavelength transition, followed by a color change from red to blue. By the process of de-swelling of the responsive polymer, which induces the aggregation of the AuNPs, the established sensor system is able to alter the color. The conjugated polymer and gold nanoparticle-based sensor system demonstrated a promising method for bacterial detection.

Colorimetric detection of heavy metal ions with various chromogenic materials: Strategies and applications

Detection of heavy metal ions has drawn significant attention in environmental and food area due to their threats to the human health and ecosystem. Colorimetry is one of the most frequently-used methods for the detection of heavy metal ions owing to its simplicity, easy operation and rapid on-site detection. The development of chromogenic materials and their sensing mechanisms are the key research direction in the area of colorimetric method. Since each chromogenic material has their unique optical and chemical properties, they have totally different colorimetric sensing mechanisms. This review focuses on the chromogenic materials and their sensing strategies for the colorimetric detection of heavy metal ions. We divide the chromogenic materials into three types, including organic materials, inorganic materials, and other materials. As for each type of chromogenic material, we discuss their detailed sensing strategies, sensing performance, and real sample applications. Moreover, current challenges and perspectives related to the colorimetry of heavy metal ions are also discussed in this review. The aim of this review is to help readers to better understand the principles of colorimetric methods for heavy metal ions and push the development of rapid detection of heavy metal ions.

Printed colorimetric chemosensor array on a 96-microwell paper substrate for metal ions in river water

Here, we propose a printed 96-well microtiter paper-based chemosensor array device (PCSAD) to simultaneously detect metal ions for river water assessment. Colorimetric chemosensors for metal ions have been designed based on molecular self-assembly using off-the-shelf catechol dyes and a phenylboronic acid (PBA) derivative. The colorimetric self-assembled chemosensors consisting of catechol dyes and a PBA derivative on a 96-well microtiter paper substrate demonstrated various color changes according to the disassembly of the ensembles by the addition of nine types of metal ions. An in-house-made algorithm was used to automate imaging analysis and extract color intensities at seven types of color channels from a captured digital image, allowing for rapid data processing. The obtained information-rich inset data showed fingerprint-like colorimetric responses and was applied to the qualitative and quantitative pattern recognition of metal ions using chemometric techniques. The feasibility of the 96-well microtiter PCSAD for environmental assessment has been revealed by the demonstration of a spike-and-recovery test against metal ions in a river water sample.

Effect of Surface Curvature on Colloidal Stability of Silver Nanoparticles with Monomolecular and Mixed Thiol Ligand Layers in the Presence of Alkali Cations

Colloidal stability of silver nanoparticles is the critical parameter while designing colloidal colorimetric biosensors. Here, we examined colloidal stability of 11-mercaptoundecanoate-capped quasi-spherical silver nanoparticles and silver nanoplates in 0.02 M phosphate buffers with pH 8.0 containing Li⁺ , Na⁺ , K⁺ , or Cs⁺ cations. While quasi-spherical nanoparticles demonstrate a good colloidal stability in the presence of all studied cations, nanoplates aggregate in the presence of Na-phosphate buffer. The mechanism of aggregation consists in the ion-specific nanoparticle-cation bridging interaction, which is sensitive to the nanoparticle surface curvature. Increased apparent dissociation constant of carboxyl groups on the zero-curvature nanoplates' surface enhances bridging interactions and makes nanoplates colloidally unstable. Bridging interactions can be eliminated by using mixed bimolecular 11-mercaptoundecanoate-11-mercaptoundecanol surface ligand layer. Silver nanoplates with mixed ligand layer show an enhanced colloidal stability at a standard carbodiimide bioconjugation protocol.

Colorimetric sensor arrays for the differentiation of baijiu based on amino-acid-modified gold nanoparticles

It is of great significance for quality control to realize the discrimination for baijiu from different brands and origins. Strong-aroma-type baijiu (SAB), one of the most important Chinese aroma-type baijiu, exhibits the largest variety and market share. In this study, we proposed colorimetric sensor arrays based on gold nanoparticles (AuNPs) modified with different amino acids (AAs) to recognize the organic acids, and further distinguish different SABs. Three representative AAs, namely methionine (Met), tryptophan (Trp), and histidine (His), were selected to modify the AuNPs surface. The investigation of the effect of the main ingredients of SAB on AA@AuNPs aggregation confirmed that this aggregation mainly resulted from organic acids. Moreover, this aggregation was successfully used for differentiating 11 organic acids. Different pH conditions can not only cause changes of the content of organic acids in baijiu, but also disrupt the balance among flavor substances of baijiu to some extent. Consequently, the AA@AuNPs arrays under two pH conditions have been successfully applied to distinguish 14 kinds of SABs from different brands and origins. The proposed colorimetric sensor method is simple, rapid, and visualized and provides a potential application prospect for the quality control of baijiu and other alcoholic beverages.

Mixed-Ligand gold nanoparticles based optical sensor array for the recognition and quantification of seven toxic metals

Sensor arrays use pattern recognition for the identification and quantification of analytes. In the presented work, a gold nanoparticle (GNP) based optical sensor array was employed to classify and quantify seven toxic metals (arsenic, barium, cadmium, cerium, chromium, lead, and mercury). The sensor array receptors were GNPs functionalized by mercaptoundecanoic acid, 2-mercaptoethanesulfonate, and a 1:1 mixture of the two ligands. The mixed-ligand particle responds to the same analytes as the mono-ligand particles but in a distinctive way. This behavior demonstrates the high potential of mixed-ligand particles in the fabrication of sensor array receptors. The responses of the GNPs to different concentrations of the seven metal ions were analyzed, and a unique "classification trajectory" was produced for every metal. Samples of different metal concentrations were then measured and identified using the "classification trajectories". Once sample composition has been identified, a PLSR model, produced from the concatenated sensor array spectra of four calibration samples for each nanoparticle, was used to determine the metal concentration.

Influence of particle size on the SARS-CoV-2 spike protein detection using IgG-capped gold nanoparticles and dynamic light scattering

Due to the unprecedented and ongoing nature of the coronavirus outbreak, the development of rapid immunoassays to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its highly contagious variants is an important and challenging task. Here, we report the development of polyclonal antibody-functionalized spherical gold nanoparticle biosensors as well as the influence of the nanoparticle sizes on the immunoassay response to detect the SARS-CoV-2 spike protein by dynamic light scattering. By monitoring the increment in the hydrodynamic diameter (ΔD_H) by dynamic light scattering measurements in the antigen-antibody interaction, SARS-CoV-2 S-protein can be detected in only 5 min. The larger the nanoparticles, the larger ΔD_H in the presence of spike protein. From adsorption isotherm, the calculated binding constant (K _D ) was 83 nM and the estimated limit of detection was 13 ng/mL (30 pM). The biosensor was stable up to 90 days at 4 °C. Therefore, the biosensor developed in this work could be potentially applied as a fast and sensible immunoassay to detect SARS-CoV-2 infection in patient samples.

An efficient differential sensing strategy for phenolic pollutants based on the nanozyme with polyphenol oxidase activity

To realize the efficient differential sensing of phenolic pollutants in sewage, a novel sensing strategy was successfully developed based on one nanozyme (GMP-Cu) with polyphenol oxidase activity. Phenolic pollutants can be oxidized by GMP-Cu, and the oxidation products reacts subsequently with 4-aminoantipyrine to produce a quinone-imine compound. The absorption spectra of final quinone-imine products resulted from different phenolic pollutants showed obvious differences, which were due to the interaction difference between GMP-Cu and phenolic pollutants, as well as the different molecular structures of the quinone-imine products from different phenolic pollutants. Based on the difference of absorption spectra, a novel differential sensing strategy was developed. The genetic algorithm was used to select the characteristic wavelengths at different enzymatic reaction times, HCA and PLS-DA algorithms were utilized for the discriminant sensing of seven representative phenolic pollutants, including hydroquinone, resorcinol, catechol, resorcinol, phenol, p-chlorophenol, and 2,4-dichlorophenol. Scientific wavelength selection algorithm and recognition algorithm resulted in the successful identification of phenolic pollutants in sewage with a discriminant accuracy of 100%, and differentiation of the phenolic pollutants regardless of their concentration. These results indicate that sensing strategy can be used as an effective tool for the efficient identification and differentiation of phenolic pollutants in sewage.

Carbon Quantum Dots Based Chemosensor Array for Monitoring Multiple Metal Ions

The simultaneous identification of multiple metal ions in water has attracted enormous research interest in the past few decades. We herein describe a novel method for multiple metal ion detection using a carbon quantum dots (CQDs)-based chemosensor array and the CQDs are functionalized with different amino acids (glutamine, histidine, arginine, lysine and proline), which act as sensing elements in the sensor array. Eleven metal ions are successfully identified by the designed chemosensor array, with 100% classification accuracy. Importantly, the proposed method allowed the quantitative prediction of the concentration of individual metal ions in the mixture with the aid of a support vector machine (SVM). The sensor array also enables the qualitative detection of unknown metal ions under the interference of tap water and local river water. Thus, the strategy provides a novel high-throughput approach for the identification of various analytes in complex systems.

A Charge-Switchable Zwitterionic Peptide for Rapid Detection of SARS-CoV-2 Main Protease

The transmission of SARS-CoV-2 coronavirus has led to the COVID-19 pandemic. Nucleic acid testing while specific has limitations for mass surveillance. One alternative is the main protease (Mpro ) due to its functional importance in mediating the viral life cycle. Here, we describe a combination of modular substrate and gold colloids to detect Mpro via visual readout. The strategy involves zwitterionic peptide that carries opposite charges at the C-/N-terminus to exploit the specific recognition by Mpro . Autolytic cleavage releases a positively charged moiety that assembles the nanoparticles with rapid color changes (t<10 min). We determine a limit of detection for Mpro in breath condensate matrices <10 nM. We further assayed ten COVID-negative subjects and found no false-positive result. In the light of simplicity, our test for viral protease is not limited to an equipped laboratory, but also is amenable to integrating as portable point-of-care devices including those on face-coverings.

Rational design of a self-assembled surfactant film in nanopipettes: combined fluorescence and electrochemical sensing

Herein, a generalizable method based on the formation of a self-assembled surfactant film was reported to build a nanopipette system. Using this nanopipette, it was found that arginine metabolism shows an age-related difference in Alzheimer's disease.

A peroxidase-like activity-based colorimetric sensor array of noble metal nanozymes to discriminate heavy metal ions

Heavy metal ions (HMIs), including Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺ from the environment pose a threat to human beings and can cause a series of life-threatening diseases. Therefore, colorimetric sensors with convenience and flexibility for HMI discrimination are still required. To provide a solution, a peroxidase-like activity-based colorimetric sensor array of citrate-capped noble metal nanozymes (osmium, platinum, and gold) has been fabricated. Some studies reported that some HMIs could interact with the noble metal nanozymes leading to a change in their peroxidase-like activity. This phenomenon was confirmed in our work. Based on this principle, different concentrations of HMIs (Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺) were discriminated. Moreover, their practical application has been tested by discriminating HMIs in tap water and SiYu lake water. What is more, as an example of the validity of our method to quantify HMIs at nanomolar concentrations, the LOD of Hg²⁺ was presented. To sum up, our study not only demonstrates the differentiation ability of this nanozyme sensor array but also gives hints for using nanozyme sensor arrays for further applications.

A new magnetic adsorbent of eggshell-zeolitic imidazolate framework for highly efficient removal of norfloxacin

Many effluents contain various antibiotics commonly, where the simultaneous removal of them is a big challenge. In this study, the magnetic biocomposite (eggshell-zeolitic imidazolate framework) was designed and synthesized by green and facile method. Zeolitic imidazolate framework-8 (ZIF-8) particles were stabilized on the surface of magnetic eggshell (Fe₃O₄-ES), generating a new Fe₃O₄-ES/ZIF-8 adsorbent, which was also fully characterized using FTIR, XRD, SEM and BET techniques. Thereafter, norfloxacin (NOR) adsorption processes were investigated through different influencing factors (dosage, concentration, pH and temperature). The Langmuir adsorption isotherm could confirm a maximum removal efficiency of 80.13% for NOR. Kinetic studies illustrated that the pseudo-first-order model was in line with the experimental data of the simultaneous removal of NOR. Moreover, the magnetic nature of the adsorbent caused an easy separation from the aqueous solution.

A theoretical approach on the ability of functionalized gold nanoparticles for detection of Cd2

Cadmium (Cd) as a toxic element that is widely present in water, soil, and air has important effects on human health, therefore proposing an accurate and selective method for detection of this element is of importance. In this article, by employing full atomistic molecular dynamics (MD) simulations and density functional theory dispersion corrected (DFT-D3) calculations, the effects of 6-mercaptonicotinic acid (MNA) and L-cysteine (CYS) on the stability of gold nanoparticles (AuNPs) and their sensitivity against Cd²⁺ were investigated. The obtained results indicate that pure AuNPs are not stable in water, while functionalized AuNPs with CYS and MNA groups have considerable stability without aggregation. In other words, the functional groups on the surface of AuNPs elevate their resistance against aggregation by an increase in the repulsive interactions between the gold nanoparticles. Moreover, functionalized AuNPs have considerable ability for selective detection of Cd²⁺ in the presence of different metal ions. Based on the MD simulation results, MNA-CYS-AuNPs (functionalized AuNPs with both functional groups) have the maximum sensitivity against Cd²⁺ in comparison with MNA-AuNPs and CYS-AuNPs due to the strong electrostatic interactions. DFT-D3 calculations reveal that the most probable interactions between the metal ions and functional groups are electrostatic, and Cd²⁺ can aggregate functionalized AuNPs due to strong electrostatic interactions with MNA and CYS groups. Moreover, charge transfer and donor-acceptor analyses show that molecular orbital interactions between the functional groups and Cd²⁺ can be considered as the driving force for AuNPs aggregation. A good agreement between the theoretical results and experimental data confirms the importance of the molecular modeling methods as a fast scientific protocol for designing new functionalized nanoparticles for application in different fields.

Lignin-mediated green synthesis of functionalized gold nanoparticles via pulsed laser technique for selective colorimetric detection of lead ions in aqueous media

A versatile green synthesis technique of pulsed laser irradiation and the sonochemical process was used for the production of functionalized gold nanoparticles (Au NPs) in the presence of lignin matrixes. In this study, the futuristic advantages of the lignin biopolymer were explored for the preparation of zero-valent Au NPs in the absence of any other reducing agents. The resulting lignin functionalized Au NPs (L-Au_f NPs) were characterized via high-resolution transmission electron microscopy, X-ray diffraction, UV-vis spectroscopy, and Fourier-transform infrared spectroscopy. The optimum lignin concentration can generate uniformly dispersed crystalline L-Au_f NPs. The optimized L-Au_f (1-5) NPs permit the selective colorimetric detection of heavy metal ions; thus, the L-Au_f (1-5) NPs demonstrated a highly selective colorimetric sensing tendency toward Pb²⁺ ions within a short time interval among the various metal ions (Pb²⁺, Fe³⁺, Cu²⁺, Cr⁶⁺, Co²⁺, Ag²⁺, Ca²⁺, Cd²⁺, Ba²⁺, and Hg²⁺). The prominent color change of L-Au_f NPs from red wine to purple indicates the detection of Pb²⁺ ions. This robust characteristic nature of L-Au_f (1-5) NPs can also detect very low concentrations of 1.8 μM in the linear range of 0.1-1 mM. Hence, the outcome of this study coincides with existing studies and indicates that L-Au_f (1-5) NPs can also be used as effective sensors for the rapid and selective detection of Pb²⁺ ions via the colorimetric analysis using the real environmental samples.

A Smartphone-Based Fluorescent Electronic Tongue for Tracing Dopaminergic Agents in Human Urine

The importance of tracing dopaminergic agents in the progression assessment of Parkinson's disease has boosted the demand for fast, sensitive, and real-time multi-analyte detection. Herein, visual and fingerprint fluorimetric patterns have been created by an optical sensor array to simultaneously detect and discriminate among levodopa, carbidopa, benserazide, and entacapone, as important dopaminergic agents. A dual emissive nanoprobe consisting of red quantum dots and blue carbon dots with an overall pink emission has been fabricated to provide unique emission patterns in the presence of the target analytes. The sensor elements in the array come from it's differential response in the absence and presence of cetyltrimethylammonium bromide under alkaline conditions. A smartphone camera was used to take photos from the solutions in the wells. Distinct changes in the spectral profiles along with vivid and concentration-dependent color variations led to visual discrimination of dopaminergic agents in a broad concentration range. The results of linear discriminant analysis revealed great discrimination accuracies. Different concentrations of the target analytes were excellently recognized in human urine. The high sensitivity of the array, which is a bonus to rapid, on-site, and visual discrimination of dopaminergic agents, holds great promise for routine analysis of real-world clinical samples.

Toward Food Freshness Monitoring: Coordination Binding-Based Colorimetric Sensor Array for Sulfur-Containing Amino Acids

Herein, a self-assembled colorimetric chemosensor array composed of off-the-shelf catechol dyes and a metal ion (i.e., Zn2+) has been used for the sulfur-containing amino acids (SCAAs; i.e., glutathione, glutathione disulfide, L-cysteine, DL-homocysteine, and L-cystine). The coordination binding-based chemosensor array (CBSA) fabricated by a competitive assay among SCAAs, Zn2+ ions, and catechol dyes [i.e., pyrocatechol violet (PV), bromopyrogallol red (BPR), pyrogallol red (PR), and alizarin red S (ARS)] yielded fingerprint-like colorimetric changes. We succeeded in the qualification of SCAAs based on pattern recognition [i.e., a linear discrimination analysis (LDA)] with 100% correct classification accuracy. The semiquantification of reduced/oxidized forms of SCAAs was also performed based on LDA. Furthermore, we carried out a spike test of glutathione in food samples using the proposed chemosensor array with regression analysis. It is worth mentioning that we achieved a 91-110% recovery rate in real sample tests, which confirmed the accuracy of the constructed model. Thus, this study represents a step forward in assessing food freshness based on supramolecular analytical methods.

Selective sensing of sulfate anions in water with cyclopeptide-decorated gold nanoparticles

The interaction of cyclopeptides bound to the surface of mixed monolayer-protected gold nanoparticles with sulfate anions causes the crosslinking and concomitant precipitation of the nanoparticles from aqueous solutions even in presence of an excess of competing anions, thus allowing the naked eye detection of sulfate in water.

Coordination array for accurate colorimetric sensing of multiple heavy metal ions

Heavy metals detection is of great significance to the environment and human health, and most of the detection methods require expensive instruments and laborious operation. Herein, we present a coordination array for accurate and rapid colorimetric heavy metal ions sensing. The array was composed of six chelates and has cross response to Hg²⁺, Cd²⁺, Pb²⁺ and Cu²⁺. The results could be observed by naked eyes or detected by plate reader combined with pattern analysis. Linear discrimination analysis was applied for the pattern analysis and the four heavy metal ions (Pb²⁺, Cd²⁺, Hg²⁺ and Cu²⁺) generated a clustering map at 1 μM. The coordination array demonstrates a great potential for sensing heavy metal ions simultaneously.

Simultaneous detection and identification of thiometon, phosalone, and prothioconazole pesticides using a nanoplasmonic sensor array

In this work, a colorimetric sensor array has been designed for the identification and discrimination of thiometon (TM) and phosalone (PS) as organophosphate pesticides and prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation AuNPs and AgNPs through the cross-reactive interaction between the target pesticides and plasmonic nanoparticles. Therefore, these aggregation-induced UV-Vis spectra changes were utilized to discriminate the target pesticides with the help of linear discriminant analysis (LDA). Besides, we have employed the bar plots and the heat maps as visual non-statistical methods to differentiate the pesticides in a wide range of concentrations (i.e., 20-5000 ng mL^-1). Multivariate calibration plots from partial least squares (PLS)- regression indicated that the responses linearly depend on the pesticide concentrations in the range of 100-1000 ng mL^-1 with the limit of detections (LOD) of 66.8, 68.3, and 41.4 ng mL^-1, for TM, PS, and PC, respectively. Finally, the potential applicability of the proposed sensor array has been evaluated for the detection and identification of the pesticides in the mixtures, water samples, and cucumber fruit.

Programmable Engineering of DNA-AuNP Encoders Integrated Multimodal Coupled Analysis for Precision Discrimination of Multiple Metal Ions

A cross-responsive strategy (CRS) based on gold nanoparticles (AuNPs) through attaching various recognition receptors on the surface of AuNPs for identifying multiple analytes is presented, and the detection throughput and overall identification accuracy are improved. However, the CRS's recognition receptor cannot get comprehensive information from the target analytes limited in number and type, which determines the overall identification accuracy. Therefore, the practicability of the CRS runs into a bottleneck. Herein, we report a programmable DNA-AuNP encoder combined with a multimodal coupled analysis algorithm for high-throughput detection and accurate analysis of multiple metal ions. The programmable DNA-AuNP encoder breaks through the limitation of the recognition receptor's quantity. Furthermore, the multimodal signals from target metal ion-induced DNA-AuNP aggregation are related to and observed in the ultraviolet absorbance spectrum, surface potential, and particle diameter. The multimodal coupled analysis algorithm can reflect comprehensive information on the target analyte more completely. Finally, this study provides a highly generic tool for the cross-responsive strategy.

Construction of DNA Biosensors for Mercury (II) Ion Detection Based on Enzyme-Driven Signal Amplification Strategy

Mercury ion (Hg²⁺) is a well-known toxic heavy metal ion. It is harmful for human health even at low concentrations in the environment. Therefore, it is very important to measure the level of Hg²⁺. Many methods, reviewed in several papers, have been established on DNA biosensors for detecting Hg²⁺. However, few reviews on the strategy of enzyme-driven signal amplification have been reported. In this paper, we reviewed this topic by dividing the enzymes into nucleases and DNAzymes according to their chemical nature. Initially, we introduce the nucleases including Exo III, Exo I, Nickase, DSN, and DNase I. In this section, the Exo III-driven signal amplification strategy was described in detail. Because Hg²⁺ can help ssDNA fold into dsDNA by T-Hg-T, and the substrate of Exo III is dsDNA, Exo III can be used to design Hg²⁺ biosensor very flexibly. Then, the DNAzyme-assisted signal amplification strategies were reviewed in three categories, including UO₂²⁺-specific DNAzymes, Cu²⁺-specific DNAzymes and Mg²⁺-specific DNAzymes. In this section, the Mg²⁺-specific DNAzyme was introduced in detail, because this DNAzyme has highly catalytic activity, and Mg²⁺ is very common ion which is not harmful to the environment. Finally, the challenges and future perspectives were discussed.

A colorimetric paper-based ATONP-ALP nanobiosensor for selective detection of Cd2+ ions in clams and mussels

A colorimetric paper-based enzyme-coupled antimony tin oxide nanoparticle (ATONP) nanobiosensor for selective detection of Cd²⁺ ions in clams and mussels is presented. Alkaline phosphatase (ALP) was immobilized on ATONPs via 16-phosphonohexadecanoic acid (16-PHA) to develop ATONP-ALP nanobiosensor. The biosensor was characterized using XPS, Raman spectroscopy, SEM, and EDX. ATONP-ALP nanobiosensor exhibited high selectivity towards detection of Cd²⁺ ion with a LOD 0.006 μg L^-1 and linear range of detection 0.005-1 μg L^-1. The developed biosensor was further integrated into a low-cost paper-based format. A visual color change was obtained for Cd²⁺ ion in the range 0.1-10 μg L^-1. The developed biosensor was successfully demonstrated for the analysis of Cd²⁺ ions in clams with recoveries 101-104%. The ATONP-ALP nanobiosensor was validated using mussel tissue (BCR-668) and the conventional ICP-OES and ICP-MS techniques.

Chemical sensing with Au and Ag nanoparticles

Noble metal nanoparticles (NPs) are ideal scaffolds for the fabrication of sensing devices because of their high surface-to-volume ratio combined with their unique optical and electrical properties which are extremely sensitive to changes in the environment. Such characteristics guarantee high sensitivity in sensing processes. Metal NPs can be decorated with ad hoc molecular building blocks which can act as receptors of specific analytes. By pursuing this strategy, and by taking full advantage of the specificity of supramolecular recognition events, highly selective sensing devices can be fabricated. Besides, noble metal NPs can also be a pivotal element for the fabrication of chemical nose/tongue sensors to target complex mixtures of analytes. This review highlights the most enlightening strategies developed during the last decade, towards the fabrication of chemical sensors with either optical or electrical readout combining high sensitivity and selectivity, along with fast response and full reversibility, with special attention to approaches that enable efficient environmental and health monitoring.

Tributylhexadecylphosphonium Modification Strategy to Construct Gold Nanoprobes for the Detection of Aqueous Cr(III)-Organic Complexes

Most metal probes based on gold nanoparticles (AuNPs) are designed for free metal ions in synthetic waters, and very few are applicable in the detection of metal-organic complexes ubiquitous in real water samples. In this study, we proposed a novel colorimetric nanoprobe strategy for complexed Cr(III) species based on the analyte-induced aggregation of AuNPs, as coated by a cationic surfactant tributylhexadecylphosphonium bromide (THPB) instead of traditional carboxyl modifiers. Such a detection system could be realized via both naked eye and/or UV-vis spectroscopy with detection limits of 8.0 and 0.29 μM, respectively, much lower than its allowable maximum level in industrial effluent as regulated by China EPA (1.5 mg Cr/L, ∼30 μM). The proposed detection system also exhibits high selectivity against various interfering substances including free ions, small organic molecules, and other metal-citrate complexes. The unique hydrolysis and extremely slow decomplexation of Cr(III) are believed to favor the formation of the specific interaction between Cr(III)-citrate and THPB-AuNPs, as verified by X-ray photoelectron spectroscopy characterization, thus endowing the nanoprobe with specific discrimination of the complexed Cr(III) via the aggregation of THPB-AuNPs. Also, the THPB-AuNPs could be stored at room temperature for 30 days and maintain constant detection performance. Moreover, the quantitative detection of Cr(III)-organic complexes with the background of various real water samples agreed well with that based on inductively coupled plasma atomic emission spectrometry, making it an attractive alternative for on-site detection of authentic samples containing Cr(III)-organic species.

Pattern-Based Recognition Systems: Overcoming the Problem of Mixtures

The transformative potential of pattern-based sensing techniques is often hampered by their difficulty in dealing with mixtures of analytes, a drawback that severely limits the applications of this sensing approach (the "problem of mixtures"). We show here that this is not an intrinsic limitation of the pattern sensing method. Indeed, we developed general guidelines for the design of the sensing, signal detection, and data interpretation methods to avoid this constraint, which resulted in chemical fingerprinting systems capable of recognizing unknown mixtures of analytes in a single experiment, without separation or pre-treatment before data acquisition. In support of these design principles, we report their successful application to an important analytical problem, metal ion discrimination and quantitation, by constructing a sensor array that provided a linear colorimetric response over a wide range of analyte concentrations. The resulting data set was interpreted using common multivariate data processing algorithms to achieve quantitative identification and concentration determination for pure and mixture samples, with excellent predictive ability on unknowns. Separation and detection methods for analyte mixtures, normally envisioned as independent processes, were successfully integrated in a single system.

Application of NaYF4:Yb/Er/Tm UCNPs in Array-Based Sensing of Neurotransmitters: From a Single Particle to a Multichannel Sensor Array

A novel multichannel sensor array has been designed using a single, yet multiemissive lanthanide-doped upconversion nanoparticle (UCNP). The energy levels of lanthanide ions gave rise to several emission bands which were exploited as individual sensor elements for the recognition of four important neurotransmitters (NTs): dopamine, norepinephrine, levodopa, and serotonin. At alkaline conditions, the oxidation products of these NTs quenched the fluorescence emissions of UCNPs with different quenching degrees. The resulting fingerprint multichannel emission profiles from NaYF₄:Yb/Er/Tm UCNPs allowed the discrimination of NTs with excellent accuracy. The recognition was further verified in artificial cerebrospinal fluid, as a complex biological media. We believe that the designed UCNP-based multichannel sensor array offers innovative insights into the discrimination of various chemical signatures using a single measurement.

AuNPs@PMo12 nanozyme: highly oxidase mimetic activity for sensitive and specific colorimetric detection of acetaminophen

The design of a highly specific and sensitive approach for the quantitative and qualitative determination of acetaminophen (AP) is crucial from a human health point of view. In this study, AuNPs@PMo12, as a nanozyme, has been developed for the highly sensitive and selective detection of AP with 3,3',5,5'-tetramethylbenzidine (TMB) within a few seconds without adding oxidizing reagents (e.g. H2O2). Synthesized nanosensors are able to oxidize TMB to yellow-brown oxidized TMB (oxTMB). The maximum peak wavelength of oxTMB was observed at 450 nm. The addition of AP and then increasing its concentration led to the production of different products in blue color. In experimental measurements, the limit of detection was obtained as 14.52 mg L-1. The quantitative determination of AP concentrations can be carried out using UV-vis spectroscopy. The design of nanosensors is cost-effective and application of them in H2O2-free and enzyme-free conditions provides a rapid sensing approach for practical use in disease monitoring and diagnosis.

Sensor Array Based Determination of Edman Degradated Amino Acids Using Poly(p-phenyleneethynylene)s

A cross‐reactive optical sensor array based on poly(p‐phenyleneethynylene)s (PPEs) determines Edman degraded amino acids. We report a sensor array composed of three anionic PPEs P1–P3, and their electrostatic complexes with metal ions (Fe²⁺, Cu²⁺, Co²⁺). We recorded distinct fluorescence intensity response patterns as “fingerprints” of this chemical tongue toward standard phenylthiohydantoin (PTH) amino acids—degradation products of the Edman process. These “fingerprints” were converted into canonical scores by linear discrimination analysis (LDA), which differentiates all of the PTH‐amino acids. This array discriminates PTH‐amino acid residues degraded from an oligopeptide through Edman sequencing. This approach is complementary to chromatography approaches which rely on mass spectrometry; our array offers the advantage of simplicity.

Colorimetric Differentiation of Multiple Oxidizing Anions Based on Two Core-Shell Au@Ag Nanoparticles with Different Morphologies as Array Recognition Elements

The efficient discrimination of oxidizing anions is of considerable importance in environmental monitoring. Here, for the first time, we have developed a simple and fast colorimetric sensor array for detection and identification of oxidizing anions, which takes advantage of the etching of the Ag shell of two core-shell Au@Ag nanoparticles (Au@Ag nanospheres (Au@Ag NPs) and Au@Ag nanocubes (Au@Ag NCs)) by oxidizing anions. The differential etching ability of various oxidizing anions to the Ag shell of the two Au@Ag nanoparticles resulted in different absorbance and color change of the nanoparticles. Thus, employing Au@Ag NPs and Au@Ag NCs as the array's receptors and the indicators, six oxidizing anions (i.e., BrO₃^-, Cr₂O₇^2-, ClO₄^-, IO₃^-, IO₄^-, and MnO₄^-) down to 10 nM could be identified from each other by their own colorimetric response patterns. Moreover, the complex mixtures of oxidizing anions could be well discriminated. Most importantly, the sensor array was successfully applied to the discrimination of oxidizing anions in river water and tap water samples.

Recent Advances in Nanomaterials for Analysis of Trace Heavy Metals

In an effort to achieve high sensitivity analysis methods for ultra-trace levels of heavy metals, numerous new nanomaterials are explored for the application in preconcentration processes and sensing systems. Nanomaterial-based methods have proven to be effective for selective analysis and speciation of heavy metals in combination with spectrometric techniques. This review outlined the different types of nanomaterials applied in the field of heavy metal analysis, and concentrated on the latest developments in various new materials. In particular, the functionalization of traditional materials and the exploitation of bio-functional materials could increase the specificity to target metals. The hybridization of multiple materials could improve material properties, to build novel sensor system or achieve detection-removal integration. Finally, we discussed the future perspectives of nanomaterials in the heavy metal preconcentration and sensor design, as well as their respective advantages and challenges. Despite impressive progress and widespread attention, the development of new nanomaterials and nanotechnology is still hampered by numerous challenges, particularly in the specificity to the target and the anti-interference performance in complex matrices.

Solid-Phase Extraction, Preservation, Storage, Transport, and Analysis of Trace Contaminants for Water Quality Monitoring of Heavy Metals

Accurate quantification of trace contaminants currently requires collection, preservation, and transportation of large volumes (250-1000 mL) of water to centralized laboratories, which impedes monitoring of trace-level pollutants in many resource-limited environments. To overcome this logistical challenge, we propose a new paradigm for trace contaminant monitoring based on dry preservation: solid-phase extraction, preservation, storage, transport, and analysis of trace contaminants (SEPSTAT). We show that a few grams of low-cost, commercially available cation exchange resin can be repurposed to extract heavy metal cations from water samples even in the presence of background ions, dryly preserve these cations for at least 24 months, and release them by acid elution for accurate quantification. A compact, human-powered device incorporating the sorbent removes spiked contaminants from real water samples in a few minutes. The device can be stored and transported easily and produces a sample suitable for measurement by standard methods, predicting the original sample heavy metal concentration generally within an error of 15%. These results suggest that, by facilitating the collection, storage, handling, and transportation of water samples and by enabling cost-effective use of high-throughput capital-intensive instruments, SEPSTAT has the potential to increase the ease and reach of water quality monitoring of trace contaminants.

White Eggshells: A Potential Biowaste Material for Synergetic Adsorption and Naked-Eye Colorimetric Detection of Heavy Metal Ions from Aqueous Solution

In the present work, we have utilized a simple, no-cost, unmodified eggshell powder as a naked-eye colorimetric detector, which on simple dispersion in aqueous solution of metal ions exhibited characteristic color change from white to pale green, pale blue, yellow, pale yellow, dark yellow, pale pink, blue, and brown for metal ions V⁴⁺, Cr³⁺, Cr⁶⁺, Fe²⁺, Fe³⁺, Co²⁺, Cu²⁺, and Ag⁺, respectively. The effects of various parameters like concentration of metal ions, pH, temperature, and adsorbent dosage were investigated by batch sorption experiments. Also, Freundlich and Langmuir models were used to describe the adsorption isotherm. The eggshell powder before and after adsorption was characterized qualitatively by the naked-eye and quantitatively by diffuse reflectance spectroscopy-UV, Fourier transform infrared, atomic absorption spectroscopy, powder X-ray diffraction, scanning electron microscopy with energy-dispersive X-ray spectroscopy, Brunauer-Emmett-Teller, zeta potential, and X-ray photoelectron spectroscopy techniques. In addition, the competitive adsorption of metal ions in mixtures and the recycle experiments were carried out to prove the sustainability of the material. Further, the red, green, and blue alterations were extracted from the colorimetric array and subjected to hierarchical clustering analysis using the Ward method by calculating the Euclidean distance, which displayed facile discrimination of 10 heavy metal ions at 1 mM level. Thus, the unmodified eggshell powder has been proven to be an impressive value-added sustainable material for synergistic metal adsorption and colorimetric naked-eye detection of a series of metal ions with detection limits of 10^-4 M for Fe³⁺, Fe²⁺, and Cu²⁺; 10^-3 M for Cr³⁺, Cr⁶⁺, Ag⁺, and Co²⁺; and 5 × 10^-3 M for V⁴⁺.