Day 3 - Analysis of EDS - Duscher

Day 3 - Analysis of EDS - Duscher

🎙 Duscher 👥 1K 📅 July 18, 2026 ⏱ 50 min 👁 9 📄 tutorial 🧭 2026-08-16
Available in: English (current) Français

Keywords

EDSquantificationK-factorabsorption correctionPython

Summary

This lecture, part of a summer school on machine learning in the nanoworld, focuses on the practical steps and physical principles behind quantifying Energy-Dispersive X-ray Spectroscopy (EDS) data using interactive Python workflows in Google Colab. The instructor, Duscher, demonstrates a method for identifying elements in a spectrum by iteratively subtracting the strongest peaks and fitting families of peaks with known relative intensities. He emphasizes the importance of background fitting and the use of K-factors for standardless quantification, showing that calculated K-factors from EM tables can be inaccurate, while manufacturer-calibrated K-factors yield better results. The lecture also covers absorption correction, which is crucial for low-energy X-rays, and demonstrates how to estimate sample thickness by iterating the correction until the composition matches a known standard. The instructor discusses the use of calibration standards for accurate quantification and highlights the advantages of using a model-based approach to obtain errors. The session includes interactive troubleshooting with participants, addressing issues with the code and fitting. The lecture concludes with a discussion on the limitations of standardless quantification and the importance of sample geometry and absorption in SEM.

182 words

Critical Evaluation

Value of the Information & Strength of the Argument

The lecture provides valuable practical insights into EDS quantification, demonstrating a systematic approach to peak identification and fitting. The argumentation is solid, based on physical principles and practical experience. The instructor clearly explains the rationale behind each step, such as why fitting whole families of peaks is more robust than fitting single peaks, and why absorption correction is necessary. He also acknowledges limitations and uncertainties, such as the inaccuracy of standardless K-factors and the need for iterative correction. The use of a real example (strontium titanate) and a fun example (chocolate) helps illustrate the concepts. The interactive nature of the session, with questions from participants, adds to the value by addressing common pitfalls.

Scientific Rigor, Source Quality, Title Accuracy

The lecture demonstrates scientific rigor by referencing established methods and sources, such as EM tables for K-factors and the concept of absorption correction. The instructor mentions that EM tables are based on published work and are among the best standardless options. He also discusses the importance of calibration standards from NIST. The title accurately reflects the content, as it is a lecture on EDS analysis. The content is technically detailed and appropriate for an audience with some background in electron microscopy. The instructor’s expertise is evident, and he is transparent about the limitations and potential errors in the methods.

227 words

Title / Content Match

The title accurately reflects the content: a lecture on EDS analysis, part of a series.

Quality & Reliability

7/10

The lecture is a practical tutorial by an expert in the field, demonstrating a specific workflow for EDS quantification. It includes references to established methods (K-factors, absorption correction) and mentions sources like EM tables. However, it is a single expert's perspective without peer review or external validation, and some parts are based on personal experience.

Key Moments

Cited Sources

  • EM tables — Mentioned as a source for calculated K-factors.

Concurring Sources

  • EM tables — The instructor references EM tables as a source for calculated K-factors, which is consistent with the content.

Contribution & Novelties

The lecture provides a practical, interactive workflow for EDS quantification using Python, which is not commonly covered in traditional textbooks. It emphasizes the importance of fitting entire families of peaks and using a model-based approach to obtain errors. The demonstration of absorption correction and thickness estimation is particularly useful. The lecture also highlights the limitations of standardless quantification and the benefits of using calibration standards.

Pour aller plus loin :

100 words

Radar Profile

The radar profile shows high scores in technical level and information quantity, reflecting the detailed and practical nature of the lecture. The quality and reliability scores are moderate, indicating that while the content is expert-led, it is not peer-reviewed and relies on personal experience. The overall balance suggests a valuable tutorial for advanced practitioners.

Reliability 7/10

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