Call: +34
Email: matildemataloni@gmail.com
Address: c/Pedro Cerbuna 12, Universidad de Zaragoza, Facultad de Ciencias, Departamento de Química Analítica – Zaragoza (Spain)
ABOUT ME
Matilde Mataloni obtained her degree in “Chimica e Tecnologie Chimiche” at the University of Genoa (Italy) in 2021. After completing the master’s degree in “Scienze Chimiche” at the same university, she is currently a predoctoral student under a joint supervision between the University of Genoa and the University of Zaragoza, respectively in the research groups “Chimica Analitica degli Elementi in Tracce” and “Métodos Rápidos de Análisis con Técnicas Espectroscópicas – MARTE”.
Her research project is titled “On the study of traditional and emerging contaminants in environmental samples via ICP-MS, both by isotopic analysis and single particle analysis”.
PUBLICATIONS
2025
Bazo, Antonio; López-Villellas, Lorién; Mataloni, Matilde; Bolea-Fernandez, Eduardo; Rua-Ibarz, Ana; Grotti, Marco; Aramendía, Maite; Resano, Martín
Improving detection and figures of merit in single-particle inductively coupled plasma-mass spectrometry via transient event heights Journal Article
En: Analytica Chimica Acta, vol. 1378, pp. 344694, 2025, ISSN: 0003-2670.
@article{BAZO2025344694,
title = {Improving detection and figures of merit in single-particle inductively coupled plasma-mass spectrometry via transient event heights},
author = {Antonio Bazo and Lorién López-Villellas and Matilde Mataloni and Eduardo Bolea-Fernandez and Ana Rua-Ibarz and Marco Grotti and Maite Aramendía and Martín Resano},
url = {https://www.sciencedirect.com/science/article/pii/S0003267025010888},
doi = {https://doi.org/10.1016/j.aca.2025.344694},
issn = {0003-2670},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
journal = {Analytica Chimica Acta},
volume = {1378},
pages = {344694},
abstract = {Background
Single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) is a powerful method for characterizing micro- and nanoparticulate materials. The technique primarily relies on the linear relationship between the integrated intensities of individual events (peak areas) and the analyte mass, though transit times (peak widths) have also been used for quantitative purposes. This work (1) evaluates the potential of using peak heights as analytical signals in SP-ICP-MS, (2) introduces a new method for determining peak heights, and (3) explores scenarios in which peak height offers added value over the commonly used SP-ICP-MS signals.
Results
A new method was proposed to estimate peak height values in SP-ICP-MS accurately. The cumulative intensity across consecutive dwell times was modeled using a third-degree polynomial, from which the adjusted peak height was derived. This approach reduces the uncertainty associated with using raw maximum intensity values, yielding NP distributions comparable to those obtained via integrated intensities. The effect of dwell time on peak height was also evaluated. An optimal range (50 μs–200 μs) was identified, where a linear relationship was observed between the peak height and the square of the NP diameter. Within this range, peak height showed the lowest bias when characterizing smaller NPs, indicating the potential to improve the limit of quantification (LoQ). Additionally, peak heights proved helpful in determining the limit of detection (LoD) and setting appropriate threshold values for data processing, thereby helping to flag incorrect resultsand addressing a challenge in SP-ICP-MS analysis.
Significance
This is the first study to evaluate peak height as an analytical signal in SP-ICP-MS. The results highlight its advantages in specific applications, such as sizing NPs near the LoD, and in supporting the more reliable use of other signals, such as peak areas, by helping to identify incorrect threshold selection that could lead to biased distributions. Finally, monitoring peak heights allows for a more realistic and assumption-free determination of the LoD.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
Single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) is a powerful method for characterizing micro- and nanoparticulate materials. The technique primarily relies on the linear relationship between the integrated intensities of individual events (peak areas) and the analyte mass, though transit times (peak widths) have also been used for quantitative purposes. This work (1) evaluates the potential of using peak heights as analytical signals in SP-ICP-MS, (2) introduces a new method for determining peak heights, and (3) explores scenarios in which peak height offers added value over the commonly used SP-ICP-MS signals.
Results
A new method was proposed to estimate peak height values in SP-ICP-MS accurately. The cumulative intensity across consecutive dwell times was modeled using a third-degree polynomial, from which the adjusted peak height was derived. This approach reduces the uncertainty associated with using raw maximum intensity values, yielding NP distributions comparable to those obtained via integrated intensities. The effect of dwell time on peak height was also evaluated. An optimal range (50 μs–200 μs) was identified, where a linear relationship was observed between the peak height and the square of the NP diameter. Within this range, peak height showed the lowest bias when characterizing smaller NPs, indicating the potential to improve the limit of quantification (LoQ). Additionally, peak heights proved helpful in determining the limit of detection (LoD) and setting appropriate threshold values for data processing, thereby helping to flag incorrect resultsand addressing a challenge in SP-ICP-MS analysis.
Significance
This is the first study to evaluate peak height as an analytical signal in SP-ICP-MS. The results highlight its advantages in specific applications, such as sizing NPs near the LoD, and in supporting the more reliable use of other signals, such as peak areas, by helping to identify incorrect threshold selection that could lead to biased distributions. Finally, monitoring peak heights allows for a more realistic and assumption-free determination of the LoD.
Single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) is a powerful method for characterizing micro- and nanoparticulate materials. The technique primarily relies on the linear relationship between the integrated intensities of individual events (peak areas) and the analyte mass, though transit times (peak widths) have also been used for quantitative purposes. This work (1) evaluates the potential of using peak heights as analytical signals in SP-ICP-MS, (2) introduces a new method for determining peak heights, and (3) explores scenarios in which peak height offers added value over the commonly used SP-ICP-MS signals.
Results
A new method was proposed to estimate peak height values in SP-ICP-MS accurately. The cumulative intensity across consecutive dwell times was modeled using a third-degree polynomial, from which the adjusted peak height was derived. This approach reduces the uncertainty associated with using raw maximum intensity values, yielding NP distributions comparable to those obtained via integrated intensities. The effect of dwell time on peak height was also evaluated. An optimal range (50 μs–200 μs) was identified, where a linear relationship was observed between the peak height and the square of the NP diameter. Within this range, peak height showed the lowest bias when characterizing smaller NPs, indicating the potential to improve the limit of quantification (LoQ). Additionally, peak heights proved helpful in determining the limit of detection (LoD) and setting appropriate threshold values for data processing, thereby helping to flag incorrect resultsand addressing a challenge in SP-ICP-MS analysis.
Significance
This is the first study to evaluate peak height as an analytical signal in SP-ICP-MS. The results highlight its advantages in specific applications, such as sizing NPs near the LoD, and in supporting the more reliable use of other signals, such as peak areas, by helping to identify incorrect threshold selection that could lead to biased distributions. Finally, monitoring peak heights allows for a more realistic and assumption-free determination of the LoD.