PARAFAC under non-negativity constraint is adapted to recover the underlying Beer-Lambert law of the excitation-emission fluorescence matrix measurements acquired from analyte-triggered semiconductor QDs photoluminescence modulation. When and why?

IF 5.6 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Talanta Pub Date : 2025-01-01 Epub Date: 2024-09-14 DOI:10.1016/j.talanta.2024.126896
Sarmento J Mazivila, Jose X Soares, Rui A S Lapa, M Lúcia M F S Saraiva, Jose O Fernandes, Sara C Cunha, Joao L M Santos
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引用次数: 0

Abstract

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 AgInS2 (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.

非负性约束下的 PARAFAC 适用于恢复从分析物触发的半导体 QDs 光致发光调制中获得的激发-发射荧光矩阵测量的基本比尔-朗伯定律。何时以及为何?
背景:分析物触发的半导体量子点(QDs)在非一致响应的荧光物种存在下的调制是具体的多路数据处理中一个具有挑战性的分析问题。在不同激发/发射模式下,具有异质尺寸和/或表面功能分子分布不均的量子点的荧光响应成分(称为化学等级)会出现显著波动。这种现象可能会导致比尔-朗伯定律所规定的比例关系出现重大偏差。不过,即使存在这种偏差,在确定 QDs 系统中适当的化学等级后,也可以成功地选择多向模型:结果:我们发现,在一个有效的 PARAllel FACtor(PARAFAC)模型中,在正确确定化学等级的情况下,原始激发-发射荧光矩阵(EEFM)测量中的每种荧光反应成分都能获得有意义的纯光谱剖面。通过对从半导体 QDs 传感系统中获取的两个不同数据集的三向数据阵列进行 PARAFAC 三线性分解,并采用低秩三线性假设,充分说明了这一点。第一个数据集是在此首次展示的,它包括呕吐毒素对硫代苹果酸(TMA)包裹的 AgInS2 (AIS) QDs 的配体驱动淬灭的 EEFM 测量。第二个数据集是通过阳离子桥接对谷胱甘肽(GSH)包裹的碲化镉 QDs 被铅(II)淬灭的 EEFM 测量,用于说明问题。这项研究的结果能够测定鱼饲料真实样本中ppb级的呕吐毒素,展示了PARAFAC模型在解析光谱特征(载荷)和纯浓度曲线(分数)方面的功效:意义:PARAFAC 模型在适当的化学阶数条件下,可以通过有化学意义的信息,轻松检索具有低阶三线性结构的原始 EEFM 测量的基本 Beer-Lambert 法则,前提是:(i) 没有观察到 Beer-Lambert 法则的偏差,这一点在通过 TMA 封装的 AIS QDs 获得的呕吐毒素驱动的分子传感数据集中有深入讨论、或 (ii) Beer-Lambert 定律出现明显偏差,如通过 GSH 封层 CdTe QD 的 Pb(II) 桥接传感离子物种所收集的数据集。
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来源期刊
Talanta
Talanta 化学-分析化学
CiteScore
12.30
自引率
4.90%
发文量
861
审稿时长
29 days
期刊介绍: Talanta provides a forum for the publication of original research papers, short communications, and critical reviews in all branches of pure and applied analytical chemistry. Papers are evaluated based on established guidelines, including the fundamental nature of the study, scientific novelty, substantial improvement or advantage over existing technology or methods, and demonstrated analytical applicability. Original research papers on fundamental studies, and on novel sensor and instrumentation developments, are encouraged. Novel or improved applications in areas such as clinical and biological chemistry, environmental analysis, geochemistry, materials science and engineering, and analytical platforms for omics development are welcome. Analytical performance of methods should be determined, including interference and matrix effects, and methods should be validated by comparison with a standard method, or analysis of a certified reference material. Simple spiking recoveries may not be sufficient. The developed method should especially comprise information on selectivity, sensitivity, detection limits, accuracy, and reliability. However, applying official validation or robustness studies to a routine method or technique does not necessarily constitute novelty. Proper statistical treatment of the data should be provided. Relevant literature should be cited, including related publications by the authors, and authors should discuss how their proposed methodology compares with previously reported methods.
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