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Electrospray Ionization (ESI) Mass Spectrometry01:12

Electrospray Ionization (ESI) Mass Spectrometry

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Higher molecular weight biomolecules are nonvolatile compounds that may decompose before ionizing or vaporizing during mass analysis with conventional electron impact ionization methods. Accordingly, electrospray ionization (ESI) is the favored method for vaporizing and ionizing biomolecules as it circumvents rapid fragmentation and enables the recording of mass signals for the entire biomolecule.
ESI utilizes electrical energy to transfer ions from the liquid phase of the sample into the...
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Related Experiment Video

Updated: Jun 5, 2025

In Situ Lithiated Reference Electrode: Four Electrode Design for In-operando Impedance Spectroscopy
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SoC estimation on Li-ion batteries: A new EIS-based dataset for data-driven applications.

Hamza Mustafa1, Carmine Bourelly2, Michele Vitelli1

  • 1University of Cassino and Southern Lazio, Cassino, Frosinone, Italy.

Data in Brief
|December 16, 2024
PubMed
Summary

This study introduces a new dataset of Electrochemical Impedance Spectroscopy (EIS) measurements for Lithium Iron Phosphate (LFP) batteries. This resource aids in developing advanced algorithms for battery State of Charge (SoC) assessment and performance prediction.

Keywords:
DatasetElectrochemical impedance spectroscopyLFP batteriesState of charge

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Area of Science:

  • Battery Technology
  • Electrochemistry
  • Energy Storage Systems

Background:

  • Lithium-ion (Li-ion) batteries are vital for modern technology.
  • Electrochemical Impedance Spectroscopy (EIS) offers deep insights into battery performance.
  • Acquiring diverse EIS datasets for State of Charge (SoC) studies is challenging.

Purpose of the Study:

  • To present a novel EIS dataset for 600 mAh Lithium Iron Phosphate (LFP) batteries.
  • To facilitate research in battery SoC assessment and performance prediction.
  • To support the development of data-driven battery management algorithms.

Main Methods:

  • Acquisition of EIS measurements from multiple LFP batteries at various SoC levels.
  • Utilized a battery-specific impedance meter and electronic load for controlled data collection.
  • Included repeated measurements across different battery discharging cycles.

Main Results:

  • A comprehensive and original EIS dataset for LFP batteries.
  • Data enables analysis of frequency domain properties related to SoC.
  • Dataset supports the development of algorithms for SoC estimation and performance prediction.

Conclusions:

  • The presented dataset is a valuable resource for battery research and development.
  • It advances the application of impedance spectroscopy in battery characterization.
  • The dataset has significant potential for future innovations in Li-ion battery technologies.