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Metal ion pollution poses a global concern due to its significant risks to both human health and environmental well-being. The toxicity of these ions can increase when they coexist, interacting with each other and with other harmful substances, even at low concentrations. Therefore, an accurate, rapid, and cost-effective methodology is urgently needed for the simultaneous quantification of multiple metal ions. This study presents a new approach for the multiplexed detection of various metal ions (Ag + , Cu 2+ , Hg 2+ , Al 3+ , Pb 2+ , Fe 3+ , Fe 2+ , Zn 2+ , Ni 2+ , Cd 2+ , and Ca 2+ ) using a triple-emission nanoprobe comprising carbon dots and distinctly capped CdTe quantum dots, specifically green-emitting glutathione -quantum dots and red-emitting 3-mercaptopropionic acid-quantum dots. The method achieved high accuracy by analysing first- and second-order photoluminescence data with distinct advanced chemometric tools. R 2 P values for partial least squares and unfolded partial least square models exceeding 0.9 for several metal ions at low concentrations (mmol L -1 ) were obtained. Additionally, PL second-order data yielded significantly better results than PL first-order data, attributed to the distinct behaviour of the metal ions over time. Interestingly, it was also noted for the first time the significant contribution of the molar ratio between the metal ions on the models' accuracy. This novel method provides a highly accurate and efficient way to detect multiple metal ions simultaneously, paving the way for improved environmental monitoring and pollution assessment. The utilization of the proposed method contributes to a better understanding of the complex interactions in mixed metal ion systems, allowing for earlier detection and mitigation of metal ion contamination threats., Competing Interests: Declarations. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Analyte-triggered semiconductor quantum dots (QDs) modulation in the presence of non-consistently responsive fluorescent species represents a challenging analytical issue in concrete multi-way data handling. QDs with heterogeneous sizes and/or uneven distribution of functional moieties on their surfaces exhibit significant fluctuations in the fluorescent response components, known as chemical rank, across different excitation/emission modes. This phenomenon may lead to a substantial deviation from the proportionality prescribed by Beer-Lambert law. Nonetheless, even in the presence of such deviation, a multi-way model may be successfully selected after determining a proper chemical rank in a QDs system., Results: We show that in a valid PARAllel FACtor (PARAFAC) model under properly determined chemical rank, meaningfully resolved pure spectral profiles can be reached for each fluorescent responsive constituent in the original excitation-emission fluorescence matrix (EEFM) measurements. This was thoroughly illustrated by applying PARAFAC trilinear decomposition of a three-way data array of two distinct datasets acquired from semiconductor QDs sensing systems with low-rank trilinear assumption. The first dataset, presented here for the first time, comprises EEFM measurements of the ligand-driven quenching of thiomalic acid (TMA)-capped AgInS 2 (AIS) QDs by vomitoxin. The second dataset, employed for illustrative purposes, comprises EEFM measurements of the quenching, via cation bridging, of glutathione (GSH)-capped CdTe QDs by Pb(II). The results of this study enabled the determination of vomitoxin at a ppb level in real samples of fish feeds, showcasing the efficacy of the PARAFAC model in resolving spectral signatures (loadings) and pure concentration profiles (scores)., Significance: PARAFAC under a properly examined chemical rank can be easily adapted for retrieval the underlying Beer-Lambert law of the original EEFM measurements with a low-rank trilinear structure through the chemically meaningful information either when (i) no deviation of Beer-Lambert law was observed as deeply discussed in connection with the dataset acquired from vomitoxin-driven molecular sensing through TMA-capped AIS QDs, or when (ii) substantial deviations of the Beer-Lambert law are evident, as discussed in connection with the dataset collected from sensing ionic species through Pb(II) bridging of GSH-capped CdTe QDs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)