When Social Media Empowers Analytical ...
Document type :
Article dans une revue scientifique: Article original
PMID :
Permalink :
Title :
When Social Media Empowers Analytical Chemists to Explore Millions of Spectra Derived from a Complex Sample.
Author(s) :
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Guerrini, Ruggero [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Ferreira, Victor [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Llamas, C. A. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Dujardin, C. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Motto-Ros, V. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Llamas, C. A. [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Guerrini, Ruggero [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Ferreira, Victor [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Llamas, C. A. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Dujardin, C. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Motto-Ros, V. [Auteur]
iLM - Luminescence [iLM - LUMINESCENCE]
Llamas, C. A. [Auteur]
Journal title :
Anal Chem
Abbreviated title :
Anal Chem
Volume number :
96
Pages :
3994–3998
Publication date :
2024-02-14
ISSN :
1520-6882
Keyword(s) :
Analytical chemistry
Chemical calculations
Cluster chemistry
Imaging
Spectroscopy
Chemical calculations
Cluster chemistry
Imaging
Spectroscopy
HAL domain(s) :
Chimie/Chimie théorique et/ou physique
English abstract : [en]
Analytical chemistry has never yielded such a wealth of experimental data as it does today, and this exponential trend shows no sign of abating. We continually advance the capabilities of our instruments and conceive ...
Show more >Analytical chemistry has never yielded such a wealth of experimental data as it does today, and this exponential trend shows no sign of abating. We continually advance the capabilities of our instruments and conceive innovative concepts, all in a concerted effort to naturally push the boundaries of our understanding regarding intricate sample matrices. Spectroscopic imaging, in the broadest sense, is certainly the field where we observe this acceleration even more pronouncedly. Analytical chemistry swiftly grasped the significance of processing acquired data for comprehensive exploration through utilization of chemometrics or machine learning tools. One can assert today that chemometrics undeniably constitutes an integral facet in the advancement of an analytical approach. However, we are now faced with a new challenge, as the experimental data accumulated for certain analytical techniques are so vast and massive that exploring them with such tools has become unfeasible, and this is by no means a computational capacity issue. Analytical chemistry is far from being the sole field affected by this issue, and one could argue that others have grappled with it long before us, such as, for instance, social media, to name just one. The purpose of this paper is to demonstrate that such a domain, which may initially seem distant from our concerns, can offer novel tools capable of overcoming these barriers, even though we are not necessarily dealing with the same objects. More specifically, we delve into the clustering of over 10 million LIBS spectra acquired as part of an imaging experiment aimed at exploring a singular rock sample. This will serve to demonstrate that an open-source library developed by Meta (formerly known as Facebook) can enable us to conduct a comprehensive exploration of this sample, a feat deemed impossible with conventional data analysis approaches.Show less >
Show more >Analytical chemistry has never yielded such a wealth of experimental data as it does today, and this exponential trend shows no sign of abating. We continually advance the capabilities of our instruments and conceive innovative concepts, all in a concerted effort to naturally push the boundaries of our understanding regarding intricate sample matrices. Spectroscopic imaging, in the broadest sense, is certainly the field where we observe this acceleration even more pronouncedly. Analytical chemistry swiftly grasped the significance of processing acquired data for comprehensive exploration through utilization of chemometrics or machine learning tools. One can assert today that chemometrics undeniably constitutes an integral facet in the advancement of an analytical approach. However, we are now faced with a new challenge, as the experimental data accumulated for certain analytical techniques are so vast and massive that exploring them with such tools has become unfeasible, and this is by no means a computational capacity issue. Analytical chemistry is far from being the sole field affected by this issue, and one could argue that others have grappled with it long before us, such as, for instance, social media, to name just one. The purpose of this paper is to demonstrate that such a domain, which may initially seem distant from our concerns, can offer novel tools capable of overcoming these barriers, even though we are not necessarily dealing with the same objects. More specifically, we delve into the clustering of over 10 million LIBS spectra acquired as part of an imaging experiment aimed at exploring a singular rock sample. This will serve to demonstrate that an open-source library developed by Meta (formerly known as Facebook) can enable us to conduct a comprehensive exploration of this sample, a feat deemed impossible with conventional data analysis approaches.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CNRS
CNRS
Collections :
Research team(s) :
Propriétés magnéto structurales des matériaux (PMSM)
Submission date :
2024-02-28T22:03:44Z
2024-03-20T09:49:15Z
2024-03-20T09:49:15Z