Modeling and optimization of the ratio of fluorophores: a step towards enhancing the sensitivity of ratiometric probes.

In the ratiometric fluorescent (RF) strategy, the selection of fluorophores and their respective ratios helps to create visual quantitative detection of target analytes. This study presents a framework for optimizing ratiometric probes, employing both two-component and three-component RF designs. For this purpose, in a two-component ratiometric nanoprobe designed for detecting methyl parathion (MP), an organophosphate pesticide, yellow-emissive thioglycolic acid-capped CdTe quantum dots (Y-QDs) (analyte-responsive), and blue-emissive carbon dots (CDs) (internal reference) were utilized. Mathematical polynomial equations modeled the emission profiles of CDs and Y-QDs in the absence of MP, as well as the emission colors of Y-QDs in the presence of MP separately. In other two-/three-component examples, the detection of dopamine hydrochloride (DA) was investigated using an RF design based on blue-emissive carbon dots (B-CDs) (internal reference) and N-acetyl L-cysteine functionalized CdTe quantum dots with red/green emission colors (R-QDs/G-QDs) (analyte-responsive). The colors of binary/ternary mixtures in the absence and presence of MP/DA were predicted using fitted equations and additive color theory. Finally, the Euclidean distance method in the normalized CIE XYZ color space calculated the distance between predicted colors, with the maximum distance defining the real-optimal concentration of fluorophores. This strategy offers a more efficient and precise method for determining optimal probe concentrations compared to a trial-and-error approach. The model's effectiveness was confirmed through experimental validation, affirming its efficacy.

Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe.

Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality of environmental water and assessing the potential risks associated with industrial waste. This study introduces a single-well fluorometric sensor that utilizes orange emissive thioglycolic acid stabilized CdTe quantum dots (TGA-QDs) and blue emissive carbon dots (CDs) to detect and differentiate between various chromium species, such as Cr (III) and Cr (VI) (i.e., CrO42- and Cr2O72-). The variations of fluorescence spectra of the proposed probe upon chromium species addition were analyzed using machine learning techniques such as linear discriminant analysis and partial least squares regression as a classification and multivariate calibration technique, respectively. Linear discriminant analysis (LDA) demonstrated exceptional accuracy in differentiating single-component and bicomponent samples. Additionally, the findings from the partial least squares regression (PLSR) showed that the sensor created has strong linearity within the 1.0-100.0, 1.0-100.0, and 0.1-15 µM range for Cr2O72-, CrO42-, and Cr3+, respectively. Furthermore, appropriate detection limits were successfully achieved, which were 2.6, 2.9, and 0.7 µM for Cr2O72-, CrO42-, and Cr3+, respectively. Ultimately, the successful capability of the sensing platform in the identification and quantification of chromium species in environmental water samples provides innovative insights into general speciation analytics.

Multiplex Detection of Biogenic Amines for Meat Freshness Monitoring Using Nanoplasmonic Colorimetric Sensor Array.

Biogenic amines (BAs) were presented as significant markers for the evaluation of the spoilage of meat and meat products. In this work, a colorimetric sensor array was developed for the discrimination and detection of spermine (SP), spermidine (SD), histamine (HS), and tryptamine (TP) as important BAs in food assessment. For this aim, two important spherical plasmonic nanoparticles, namely gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs), were utilized as the sensing elements of the probes. The cross-reactive interaction of the target biogenic amines and the plasmonic nanoparticles caused the aggregation-induced UV-Vis spectra changes, which were accompanied by visual color variation in the solution. The collected responses were analyzed by principal component analysis-linear discrimination analysis (PCA-LDA) to classify the four BAs. This colorimetric sensor array can also discriminate between the individual BAs and their mixture accurately. Partial least squares regression (PLS-R) was also utilized for quantitative analysis of the BAs. The wide linear concentration ranges of 0.1-10.0 µM for the four BAs and desirable figures of merits (FOMs) showed the potential of the developed sensor for quantitative detection of the BAs. Finally, the practical ability of the developed probe was studied by the determination of the BAs in the meat samples, which successfully proved the potential of the colorimetric sensor array in a food sample.

Chrono-colorimetric sensor array for detection and discrimination of halide ions using an all-in-one plasmonic sensor element.

Most nanoparticle based colorimetric sensor array utilize several sensor elements and static response for discrimination of target analytes. This approach can be complicated and costly to synthesize or functionalize different nanoparticles for providing wide color variation. Herein, triangular silver nanoparticles (TSNPs) were used to develop a colorimetric sensor array by time-dimension responses. The principle of this sensor array is based on the diverse etching process of TSNPs in the presence of three halide ions, including bromide (Br-), iodide (I-) and chloride (Cl-). Various etchings of TSNPs induced color changes at different reaction time intervals, which produced a colorimetric pattern for each ion. Therefore, using time dependent etching responses of TSNPs as a single sensing component can produce a wide color variation which can be distinguished by naked eyes. The colorimetric responses of TSNPs upon the addition of different concentrations of halide ions have been analyzed by PLS regression (PLS-R) and PLS discriminant analysis (PLS-DA). The analytical figures of merit confirmed that the developed chrono-colorimetric TSNPs -based sensor array is successful in both the discrimination and quantitative detection of halide ions. At the final step, the three halide ions were accurately determined in a real water sample, which verified the potential of the developed sensor in a real sample.

Paper-based optical nanosensors - A review.

Paper-based analytical devices (PADs) have shown great promise for point-of-care testing and on-site detection of analytes with chemical, biochemical, and environmental importance owing to their low cost, convenience, scalability, portability, and biocompatibility. The World Health Organization stated that sensors should meet the ASSURED criteria (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable). Paper-based optical sensors meet most of these criteria, making them in high demand and applicable in remote areas. Optical PADs outputs are obtained by different means, such as dyes, nanostructures, redox agents, and pH indicators. The outstanding physical and chemical characteristics of nanostructures, their intense signals, and tunable optical properties make them ideal for many sensing platforms, including paper-based ones. This review focuses primarily on paper-based nanosensors using various nanostructures to fabricate and produce optical signals for visualization. We describe the fundamentals and state of the art of PADs and comprehensively explain the following topics: paper types as the substrate of PADs, PAD fabrication approaches, nanostructure stabilization on PADs, signal acquisition, data handling, interpretation of results, sensing mechanisms, and application areas. We also discuss future trends and strategies to enable PADs to reach their full potential and increase their commercialization opportunities.

Determination of spermine and spermidine in meat with a ratiometric fluorescence nanoprobe and a combinational logic gate.

A ratiometric fluorescent nanoprobe is developed with a wide color variation for visual determination of spermine (SP) and spermidine (SD) in meat samples. The green emission provided from the combination of yellow emissive quantum dots and blue emissive carbon dots turns into pink when SP or SD are present. The results show that the developed sensor has good linearity in the range of 0.5-10 and 0.5-80 µM for SP and SD and suitable detection limits were achieved including 0.2 and 2.1 µM for SP and SD. The probe was highly selective in the presence of amino acids and other biogenic amines. RGB indices were extracted to build a combinational logic gate for visual and simultaneous detection of SP and SD. The dual functional logic gate was easy to design and convenient to operate. Finally, a portable sensor was fabricated for visual, rapid and on-site assessment of meat freshness.

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.

Nanoplasmonic sensor array for the detection and discrimination of pesticide residues in citrus fruits.

Great attention has been directed towards developing rapid and straightforward methods for the identification of various pesticides that are usually used simultaneously in citrus fruits. The extensive use of diverse classes of pesticides in citrus fruits and their high toxicity may cause serious diseases in the human body. In the current study, a non-enzymatic sensor array has been developed for the identification and discrimination of five different pesticides belonging to diverse classes, including organophosphate, carbamate, and bipyridylium. For this aim, two gold nanoparticles (AuNPs) with different capping agents, citrate and borohydride, were used as sensing elements. The aggregation-induced spectra alterations of AuNPs were utilized to identify the pesticides in a wide range of concentrations (20-5000 ng mL-1). We have employed data visualization methods (i.e., heat maps, bar plots, and color difference maps), a supervised pattern recognition method (i.e., linear discrimination analysis), and partial least squares regression to qualitatively and quantitatively determine the pesticides. Finally, the practical applicability of the developed sensor array was evaluated for the identification of target pesticides in lime peel. The outcomes revealed that the probe could accurately verify the absence or presence of the pesticides in lime fruit.

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.

Optical nanoprobes for chiral discrimination.

Chiral discrimination has always been a hot topic in chemical, food and pharmaceutical industries, especially when dealing with chiral drugs. Enantiomeric recognition not only leads to better understanding of the mechanism of molecular recognition in biological systems, but may further assist in developing useful molecular devices in biochemical and pharmaceutical studies. By emerging nanotechnology and exploiting nanomaterials in sensing applications, a great deal of attention has been given to the design of optical nanoprobes that are able to discriminate enantiomers of chiral analytes. This review explains how engineering nanoparticles (NPs) with desired physicochemical properties allows developing novel optical nanoprobes for chiral recognition. Fundamental concepts related to the origin of chirality in NPs have been briefly presented. Colorimetric and fluorimetric assays in which different types of chiral NPs are used for enantioselective recognition, have been comprehensively described. The main types of nanomaterials described in this review consist of luminescent quantum dots (QDs), carbon dots (CDs), silicon NPs and metal nanoclusters (NCs), as well as plasmonic nanostructures. The mechanisms of sensing in these NP-based optical chiral assays along with relevant examples have been also discussed. Finally, the remaining challenges and future directions have been provided for researchers interested in this topic.

Ratiometric fluorescent nanoprobes for visual detection: Design principles and recent advances - A review.

Signal generation techniques for visual detection of analytes have received a great deal of attention in various sensing fields. These approaches are considered to be advantageous when instrumentation cannot be employed, such as for on-site assays, point-of-care tests, and he althcare diagnostics in resource-constrained areas. Amongst various visual detection approaches explored for non-invasive quantitative measurements, ratiometric fluorescence sensing has received particular attention as a potential method to overcome the limitations of intensity-based probes. This technique relies on changes in the intensity of two or more emission bands (induced by an analyte), resulting in an effective internal referencing which improves the sensitivity of the detection. The self-calibration, together with the unique optophysical properties of nanoparticles (NPs) have made the ratiometric fluorescent nanoprobes more sensitive and reliable, which in turn, can result in more precise visual detection of the analytes. Over the past few years, a vast number of ratiometric sensing probes using nanostructured fluorophores have been designed and reported for a wide variety of sensing, imaging, and biomedical applications. In this work, a review on the NP-based ratiometric fluorescent sensors has been presented to meticulously elucidate their development, advances and challenges. With a special emphasis on visual detection, the most important steps in the design of fluorescent ratiometric nanoprobes have been given and based on different classes of analytes, recent applications of fluorescent ratiometric nanoprobes have been summarized. The challenges for the future use of the technique investigated in this review have been also discussed.

A rainbow ratiometric fluorescent sensor array on bacterial nanocellulose for visual discrimination of biothiols.

Considering the crucial role of biothiols in many biological processes, which turns them into highly valuable biomarkers for the early diagnosis of various diseases, the development of an affordable, sensitive and portable probe for the identification and discrimination of these compounds is of great importance. Herein, we developed a ratiometric fluorescent (RF) sensor array with a wide color emissive variation, on a bacterial cellulose (BC) nanopaper substrate for the visual discrimination of biothiols. To this aim, RF sensing elements including N-acetyl l-cysteine capped green CdTe quantum dots-rhodamine B (GQDs-RhB) and red CdTe QDs-carbon dots (RQDs-CDs) at two different NaOH concentrations (0 and 5 mM) were utilized as sensor elements for the discrimination of biothiols. Owing to the high affinity of the thiol group (SH) to the surface of CdTe QDs and the aggregation of the QDs, the fluorescence (FL) emission of the QDs changed while the emission of the CDs and rhodamine B remained almost unchanged upon the addition of biothiols. Accordingly, characteristic rainbow-like FL fingerprint patterns were created for each biothiol which were then distinguished both visually and spectroscopically. Hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) pattern recognition techniques were employed for the identification and discrimination of biothiols. Based on the designed RF sensor array, convenient test strips were fabricated on BC nanopaper for the visual discrimination of biothiols. It has been shown that this probe can successfully identify biothiols in human plasma as well. Altogether, the developed nanopaper-based sensor array offers an efficient biothiol discrimination tool that can be potentially exploited in the near future in theranostic and point-of-care applications.

A nanopaper-based artificial tongue: a ratiometric fluorescent sensor array on bacterial nanocellulose for chemical discrimination applications.

In the present study, a ratiometric fluorescent sensor array as an artificial tongue has been developed on a nanopaper platform for chemical discrimination applications. The bacterial cellulose (BC) nanopaper was utilized for the first time as a novel, flexible, and transparent substrate in the optical sensor arrays for developing high-performance artificial tongues. To fabricate this platform, the hydrophobic walls on the BC nanopaper substrates were successfully created using a laser printing technology. In addition, we have used the interesting photoluminescence (PL) properties of an immobilized ratiometric probe (carbon dot-Rhodamine B (CD-RhB) nanohybrids) on the nanopaper platform to improve the visual discrimination analysis. Heavy metal ions were utilized as model analytes to verify the applicability of the fabricated nanopaper-based ratiometric fluorescent sensor array (NRFSA). Using the color variation of the NRFSA platform upon the addition of heavy metal ions, which have been obtained by a smartphone (under an UV irradiation), five heavy metal ions (i.e., Hg(ii), Pb(ii), Cd(ii), Fe(iii), and Cu(ii)) have been well-distinguished through the RGB analysis via production of the characteristic PL fingerprint-like response patterns for each of them. Moreover, the developed optical sensor array was successfully exploited to identify the heavy metal ions in the water and fish samples. We have also found that the PL spectra, which have been obtained by a spectrofluorometer, of the developed NRFSA can be exploited for discrimination applications. We believe that the nanopaper-based artificial tongues will provide innovative insights into the development of optical sensor arrays towards advanced (bio)chemical discrimination applications and can revolutionize the conventional optical sensor array technology.

Nanoparticle-based optical sensor arrays.

As in many other methods that have integrated nanoparticles (NPs), the chemical nose/tongue strategy has also progressed greatly since the entrance of NPs into this field. The fascinating tunable physicochemical properties of NPs have made them powerful candidates for array-based sensing platforms and have enabled the development of real-time, sensitive and portable systems that are able to target complex mixtures of analytes. In particular, the unique optical properties of NPs have a key role in providing promising array-based sensing approaches. This review will describe the main aspects and processes of most common NP-based optical sensor arrays. The fundamental steps in the design of a sensor array together with details of each step would be provided. The review begins with the principles of optical sensor arrays and presents the concept of cross-reactivity as the main criterion in the selection of sensing elements. Changes in the absorption and emission properties of the assembled sensing elements are categorized into two main classes of optical signals (colorimetric and fluorometric). Popular chemometric methods used for analyzing the data acquired by a sensor array have also been briefly introduced. On the basis of the objective and the desired application, different types of plasmonic and fluorescent NP that possess unique opto-physical properties have been presented as available choices in the design of sensing elements. The vast number of applications of NP-based optical sensor arrays published throughout the literature have then been reviewed according to their mechanism of interaction and the type of optical signal. Finally, the remaining challenges and future directions in this topic have been highlighted.

A sensitive and selective colorimetric method for detection of copper ions based on anti-aggregation of unmodified gold nanoparticles.

A highly sensitive and selective colorimetric method for detection of copper ions, based on anti-aggregation of D-penicillamine (D-PC) induced aggregated gold nanoparticles (AuNPs) was developed. Copper ions can hinder the aggregation of AuNPs induced by D-PC, through formation of mixed-valence complex with D-PC that is a selective copper chelator. In the presence of a fixed amount of D-PC, the aggregation of AuNPs decreases with increasing concentrations of Cu(2+) along with a color change from blue to red in AuNPs solution and an increase in the absorption ratio (A520/A650). Under the optimum experimental conditions (pH 7, [AuNPs] =3.0 nmol L(-1) and [NaCl]=25 mmol L(-1)), a linear calibration curve for Cu(2+) was obtained within the range of 0.05-1.85 µmol L(-1) with a limit of detection (3Sb) of 30 nmol L(-1). Excellent selectivity toward Cu(2+) was observed among various metal ions due to a specific complex formation between Cu(2+) and D-PC. The proposed method has been successfully applied for the detection of Cu(2+) in various real samples.