An array sensor consisting of a single indicator with multiple concentrations and its application in ion discrimination

Designing optimal sensor arrays: leveraging hard modeling for improved performance

In a sensor array system with the ability to design multiple sensor elements, selecting the optimal sensor elements can maximize the efficiency of the sensor array in responding to various analytes. This paper proposes the application of hard chemical modeling as a means to identify the optimal subset of indicator displacement assay (IDA)-based sensors in the array, aiming to achieve maximum performance for detection or quantification. The model governing all reactions in the IDA sensor and the model of the pure spectrum of active species are first determined. Next, by applying the model of the pure spectrum of active species (including the indicator and indicator-receptor complex) to each sensor element and taking into account the system's nonlinearity, corrected concentration profiles of active species are derived using the generalized classical least square (G-CLS) method. These corrected concentration profiles are utilized as the output signal for each sensor element. Finally, the dynamic ranges (DR) of each sensor element and subsequently the DR for all possible sensor arrays are determined.To assess the effectiveness of the sensor array through dynamic range analysis, an IDA-based sensor system comprising five different elements was designed. It was observed that sensors with a larger dynamic range, when arranged together in an array, are more efficient for the quantitative identification of analytes. However, simply increasing the number of elements in the sensor array may not necessarily enhance its effectiveness; instead, it could amplify the noise within the system. Additionally, multivariate fitting regression with Gaussian function (MFRG), a nonlinear calibration method, was applied to assess the prediction ability of all possible designed sensor arrays.

A pH-Based Single-Sensor Array for Discriminating Metal Ions in Water

Human activities, such as mining and manufacturing, expose society and the natural environment to harmful levels of metal ions. Recently, optical sensor arrays for metal ion detection have become popular owing to their favourable features, such as facile sample preparation and the requirement of less expensive instrumentation compared to traditional, spectrometry‐based analysis techniques. Sensor arrays usually consist of numerous optical probes that are used in combination to generate unique analyte responses. In contrast, here we present an array that comprises a single fluorescent sensor, Coum4‐DPA, that produces unique responses to metal ions in different pH environments. With this simple sensing platform, we were able to classify 10 metal ions in different water sources and quantify Pb²⁺ in tap water using just one fluorescent sensor, a few pH buffers and two sets of spectral data. This novel approach significantly decreases time and costs associated with probe synthesis and data collection, making it highly transferrable to real‐world metal sensing applications.

Array-Based Discriminative Optical Biosensors for Identifying Multiple Proteins in Aqueous Solution and Biofluids

Identification of proteins is an important issue both in medical research and in clinical practice as a large number of proteins are closely related to various diseases. Optical sensor arrays with recognition ability have been flourished to apply for distinguishing multiple chemically or structurally similar analytes and analyzing unknown or mixed samples. This review gives an overview of the recent development of array-based discriminative optical biosensors for recognizing proteins and their applications in real samples. Based on the number of sensor elements and the complexity of constructing array-based discriminative systems, these biosensors can be divided into three categories, which include multi-element-based sensor arrays, environment-sensitive sensor arrays and multi-wavelength-based single sensing systems. For each strategy, the construction of sensing platform and detection mechanism are particularly introduced. Meanwhile, the differences and connections between different strategies were discussed. An understanding of these aspects may help to facilitate the development of novel discriminative biosensors and expand their application prospects.

Single-system based discriminative optical sensors: different strategies and versatile applications

Discriminative optical sensors with pattern recognition properties and high-throughput ability have been widely developed as they can distinguish multiple chemically similar analytes. Compared to traditional sensor arrays composed of a series of sensor elements, single-system based discriminative sensors using an array of optical changes at different wavelengths to provide input signals have drawn intensive attention recently. On the one hand, they can provide discrimination ability that is lack in using selective sensors; on the other hand, they can simplify the complex data acquisition process accompanied by multiple-element-based sensor arrays and reduce consumption of sensor samples. This tutorial review gives an overview of the development of single-system based discriminative optical sensors. Different strategies for the construction of single-system based discriminative sensors including dynamic combinatorial libraries, cross-reactive conjugated polymers, DNA G-quadruplex ensembles, combinatorial fluorescent molecular sensors, and fluorophore/surfactant aggregate ensembles are particularly introduced.

Fluorescent sensing arrays for cations and anions

A review of fluorescent sensing arrays for anions and cations, highlighting promising strategies and directions for future research.

Intraparticle FRET of Mn(ii)-doped carbon dots and its application in discrimination of volatile organic compounds

To achieve an energy transfer system in emissive nanoparticles, a conventional strategy is to graft an exterior fluorophore onto the surface of the host. In this paper, we report for the first time an intraparticle Förster resonance energy transfer (IPFRET) system formed intrinsically in Mn(ii)-doped carbon dots (MCDs). In virtue of the small particle size of MCDs and the modified band structure, intraparticle energy transfer from a fluorophore-like donor component to a metal-related acceptor component takes place. The IPFRET of MCDs was found to be sensitive to the chemical environment (e.g., polarity) via the effects of external influences on the metal-to-ligand charge transfer (MLCT). Surface enhanced Raman spectroscopy was employed to verify the MLCT-related metal-coordination conformation, and proved capable of collecting bonding information of metal-doped species of carbon dots. Benefitting from the sensitivity of the IPFRET signal, MCDs exhibited high potential in sensing applications.