Fabrication of a re-useable ionic liquid-based colorimetric organo nanosensor for detection of nerve agents' stimulants

Nerve agents are highly poisonous organophosphorus chemicals, and the possibility of being used in terrorist attacks seriously threatens public safety. Thus, developing quick and straightforward detection techniques for these dangerous substances is paramount for the scientific communities. In this contribution, we have fabricated a sensitive and easily applicable ionic liquids (ILs) based colorimetric sensor for detecting various nerve agents' stimulants in solution and gas phases, respectively, based on methyl orange (MO)-based IL ([P66614]+[MO]-) derived from MO dye and trihexyltetradecylphosphonium chloride (P66614Cl) by a simple ion exchange mechanism. The developed [P66614]+[MO]- and water-suspended [P66614]+[MO]- nanoparticles are found to be very much sensitive to detecting various nerve agents' stimulants having detection limits in the μM range in any medium and could be identified based on the response times which is found to be superior to many chemosensors available in the literature. The naked eye observed a distinct color change from yellow to fuchsia in the presence of nerve agents' stimulants, which shows better sensitivity than the free organic indicator. Furthermore, a facile test strip with [P66614]+[MO]- and water-suspended [P66614]+[MO]- NPs has been fabricated that can achieve visual detection of various nerve agents' stimulants within the stockpiles of other analogous harmful analytes. Also, a dip-stick experiment has been performed to detect harmful toxic analytes vapor. The effectiveness of [P66614]+[MO]- and water-suspended [P66614]+[MO]- NPs in identifying and quantifying various nerve agents' stimulants demonstrated its potential for usage as a signal tool for real sample analysis.

Copper nanoclusters-based fluorescent sensor array to identify metal ions and dissolved organic matter

In recent years, the prevention and control of water pollution has received extensive attention. There is a need to develop simple and effective strategies for the rapid detection of metal ions and dissolved organic matter (DOM) in order to improve water quality. To this end, the first copper nanoclusters (CuNCs)-based fluorescent sensor array was done to identify 12 metal ions (Pb²⁺, Fe³⁺, Cu²⁺, Cd²⁺, Cr³⁺, Co²⁺, Ni²⁺, Zn²⁺, Ag⁺, Fe²⁺, Hg²⁺, and Al³⁺) and DOM (humic substances, lipids, fatty acids, amino acids, and lignans). The results revealed that CuNCs that were synthesized with polyethyleneimine (PEI), histidine (His), and glutathione (GSH) exhibited different binding abilities to metal ions and DOM. These unique fluorescence responses were analyzed using principal component analysis (PCA) and linear discriminant analysis (LDA) to identify metal ions and DOM in the buffer. The aforementioned 12 metal ions were classified at a limit concentration of 1.5 μM. Moreover, quantification of metal ions was achieved even at a low concentration of 0.83 μM (Zn²⁺). This array also worked well in the recognition of metal ions in tap water as well as distinguishing riverine and seawater samples of different regions, which was of great significance in environmental monitoring.

Fluorescent Ionic Probe for Determination of Mechanical Properties of Healed Poly(ethylene-co-methacrylic acid) Ionomer Films

In recent years, advanced materials with properties resembling biological systems, particularly artificial muscles, have received intense scrutiny. This is because the interesting conformational shape characteristics of such materials have benefited a variety of technologies, including textiles, 3D printing, and medical devices. Although a multitude of shape memory properties have been studied and developed in recent years, self-healing of these polymers after puncture or rupture has also become a major area of study. Most techniques for detection of such processes are mechanically based and require considerable hands-on monitoring. Thus, a rapid visual detection method for self-healing is highly desirable. Herein, we describe fluorescence studies for rapid detection of self-healing properties of a partially neutralized sodium ionomer poly(ethylene-co-methacrylic acid) (PEMA). In this study, two different fluorophores, parent non-ionic 4,6-dipyrenylpyrimidine and ionic 4,6-dipyrenylpyrimidinium iodide fluorophores, were evaluated as possible sensors of self-healing. Incorporation of these probes via solution blending and compatibility into a PEMA of these fluorophores were evaluated. Thermal characterizations using differential scanning calorimetry were also performed to elucidate physical characteristics of healed sites. Ratiometric fluorescence emission variations were explored within puncture-healed ionomer films and related to Young's modulus properties with good linearity, indicating potential utility of this approach for monitoring elastic modulus properties after healing has occurred. Further statistical analyses of mechanical processes using quadratic discriminant analysis resulted in development of several highly accurate predictive models for determining time since damage healing.

Protein discrimination using erythrosin B-based GUMBOS in combination with UV-Vis spectroscopy and chemometrics

GUMBOS (Group of Uniform Materials Based on Organic Salts) have recently emerged as interesting materials for protein analysis due to their unique features and high tunability. In this regard, four novel erythrosin B (EB)-based GUMBOS were synthesized and their potential to discriminate among proteins with distinct properties (e.g., size, charge, and hydrophobicity) was assessed. These solid-phase materials were prepared using a single-step metathesis reaction between EB and various phosphonium and ammonium cations, namely tetrabutylphosphonium (P₄₄₄₄⁺), tributylhexadecylphosphonium (P₄₄₄₁₆⁺), tetrabutylammonium (N₄₄₄₄⁺), and benzyldimethylhexadecylammonium (BDHA⁺). Subsequently, the effect of pH (3.0, 4.5, and 6.0) and reaction time (5, 10, and 15 min) on the discriminatory power of synthesized GUMBOS was evaluated. Absorption spectra resulting from the interaction between EB-based GUMBOS and proteins were analyzed using partial least squares discriminant analysis (PLSDA). Unlike time, the pH value was determined to have influence over GUMBOS discrimination potential. Correct protein assignments varied from 86.5% to 100.0%, and the best discriminatory results were observed for [P₄₄₄₄]₂[EB] and [N₄₄₄₄]₂[EB] at pH 6.0. Additionally, these two GUMBOS allowed discrimination of protein mixtures containing different ratios of albumin and myoglobin, which appeared as individualized clusters in the PLSDA scores plots. Overall, this study showcases EB-based GUMBOS as simple synthetic targets to provide a label-free, cost-effective, rapid, and successful approach for discrimination of single proteins and their mixtures.

A novel non-enzymatic sensor for prostate cancer biomarker sensing based on electrocatalytic oxidation of sarcosine at nanostructured NiMn2O4 impregnated carbon paste electrode

This work addresses the electrocatalytic activity of a binary metal oxide catalyst of NiMn₂O₄ for electroxidation of sarcosine, the well-known prostate cancer biomarker. The nanocatalyst described was prepared via hydrothermal synthesis route, followed by calcination at 800 °C. Field emission scanning electron microscopy and X-ray diffraction were applied to obtain information about the material morphology and structure. A carbon paste electrode modified with nano-NiMn₂O₄ showed unique catalytic activity in sarcosine electroxidation which led to a significant rise in oxidation current (about four times) in comparison with the blank electrode. However, the carbon paste electrodes containing single oxides of NiO and Mn₂O₃ exhibited no considerable enhancement in sarcosine signal. The cyclic voltammetry results indicated that the Mn³⁺/Mn⁴⁺ couple was responsible for sarcosine oxidation, and NiO may enhance the content of Mn⁴⁺species in NiMn₂O₄ material. The carbon paste-based NiMn₂O₄ electrode was applied in the sensitive determination of sarcosine in the concentration range of 0.01-5.0 μM with the relative standard deviation of 3.49% (n = 5). The detection limit and quantification limit of the probe were determined to be 3.8 and 12 nM, respectively. The remarkable sensitivity and high selectivity of the method approved the sensor applicability in measurement of sarcosine content in urine samples.

Development of an automated yeast-based spectrophotometric method for toxicity screening: Application to ionic liquids, GUMBOS, and deep eutectic solvents

Saccharomyces cerevisiae has been used as a eukaryotic model organism for studying the toxic effects of various compounds. In this context, an automated spectrophotometric method based on the enzymatic reduction of methylene blue dye to a colorless product by living yeast cells was implemented in a sequential injection analysis system. Loss of yeast viability/impaired metabolic activity was monitored by an increase in optical density at 664 nm. To prove the usefulness of this approach, the toxicity of ILs (ionic liquids), GUMBOS (group of uniform materials based on organic salts), and DESs (deep eutectic solvents) was examined. Differences obtained between IC₅₀ values confirmed the impact of structural elements on each compounds' toxicity. While DESs appeared to be less toxic than ILs, GUMBOS were found to be among the most toxic compounds to yeast cells and thus can be viewed as promising antimicrobial candidates. The automated methodology showed satisfactory repeatability and reproducibility (RSD < 9%), which is in good agreement with Green Chemistry principles. In fact, the method required consumption of only 40 μL of reagents and produced less than 2 mL of effluents per cycle. Thus, the developed assay can be used as an alternative tool for toxicity screening.

Fabrication of a GUMBOS-based acid-base indicator: smart probe for sensing acids and bases in any solvent

This report outlines the synthesis of an ionic liquid-based pH-responsive indicator to sense acids or bases in non-polar as well as polar solvents. Herein, we have assembled a new ionic liquid (IL) comprised of a group of uniform materials based on organic salts (GUMBOS) by attaching a quaternary phosphonium ionic liquid with a very common acid-base indicator, methyl orange, via simple ion-exchange reaction. This integrated IL-based indicator is highly soluble in less polar solvents and exhibits good sensitivity toward the presence of acids/bases in those media. Furthermore, this indicator has been exploited in determining the dissociation constants of several acids in non-aqueous aprotic solvents by overlapping indicator method and hence this report provides essential information toward the understanding of many fundamental chemical reactions. This report has further scope for the synthesis of novel aqueous suspended nanomaterials, i.e., the nanoparticles derived from GUMBOS (nanoGUMBOS) by a simple flash nano-precipitation method. The nanomaterial has been well characterized by different spectroscopic and microscopic studies. The obtained nanoparticles also exhibit substantial pH-responsive behaviors in aqueous medium and show better susceptibility as compared to the free organic indicator. Thus, this report explores detailed studies on the IL-based indicator in sensing the acidity/basicity of various media.

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.

Protein Discrimination Using a Fluorescence-Based Sensor Array of Thiacarbocyanine-GUMBOS

Sensitive and selective detection of proteins from complex samples has gained substantial interest within the scientific community. Early and precise detection of key proteins plays an important role in potential clinical diagnosis, treatment of different diseases, and proteomic research. In the study reported here, six different compounds belonging to a group of uniform materials based on organic salts (GUMBOS) have been synthesized using three thiacarbocyanine (TC) dyes and employed as fluorescent sensors. Fluorescence properties of micro- and nanoaggregates of these TC-based GUMBOS formed in phosphate buffer solutions are studied in the absence and presence of seven proteins. Fluorescence response patterns of these TC-based GUMBOS were analyzed by linear discriminant analysis (LDA). The constructed LDA model allowed discrimination of these seven proteins at various concentrations with 100% accuracy. The sensing and discrimination abilities of these TC-based GUMBOS were further evaluated in mixtures of two major proteins, i.e., human serum albumin and hemoglobin. Fluorescence response patterns of these mixtures were analyzed by LDA. This model allowed discrimination of various mixtures with 100% accuracy. Moreover, spiked urine samples were prepared and the responses of these sensors were collected and analyzed by LDA. Remarkably, discrimination of these seven proteins was also achieved with 100% accuracy.

A Multi-Fluorescent DNA/Graphene Oxide Conjugate Sensor for Signature-Based Protein Discrimination

Signature-based protein sensing has recently emerged as a promising prospective alternative to conventional lock-and-key methods. However, most of the current examples require the measurement of optical signals from spatially-separated materials for the generation of signatures. Herein, we present a new approach for the construction of multi-fluorescent sensing systems with high accessibility and tunability, which allows generating protein fluorescent signatures from a single microplate well. This approach is based on conjugates between nano-graphene oxide (nGO) and three single-stranded DNAs (ssDNAs) that exhibit different sequences and fluorophores. Initially, the three fluorophore-modified ssDNAs were quenched simultaneously by binding to nGO. Subsequent addition of analyte proteins caused a partial recovery in fluorescent intensity of the individual ssDNAs. Based on this scheme, we have succeeded in acquiring fluorescence signatures unique to (i) ten proteins that differ with respect to pI and molecular weight and (ii) biochemical marker proteins in the presence of interferent human serum. Pattern-recognition methods demonstrated high levels of discrimination for this system. The high discriminatory power and simple format of this sensor system should enable an easy and fast evaluation of proteins and protein mixtures.