Overview. Fundamentals: characteristic X-rays Principles of XEDS analysis. X-ray spectrum analysis. Reading: Williams and Carter, Chapters 32-34

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1 Qualitative XEDS X-ray Energy Dispersive Spectroscopy (XEDS, EDS, EDX) Analysis of characteristic X-rays generated when the electron beam hits the specimen Provides elemental information about the sample Quick and easy, extremely common

2 Overview Fundamentals: characteristic X-rays Principles of XEDS analysis Detection Signal processing X-ray spectrum analysis Understanding artifacts Peak identification Reading: Williams and Carter, Chapters 32-34

3 Characteristic X-rays: Generation

4 Characteristic X-ray: Generation Emitted x ray, E = hν = ΔE Electron High energy from higher energy incoming level relaxes electron to fill hole Emitted ΔEelectron

5 Characteristic X-rays quantum numbers s

6 Characteristic X-rays electronic states

7 Possible transitions

8 Relative intensity of transitions

9 Energy dispersive spectrometer How it works: X-rays are detected by a semiconductor detector The detector generates a charge pulse proportional to the X-ray energy The pulse is converted to a voltage The signal is amplified, isolated and identified The signal is stored in a channel assigned to that specific energy in the computer

10 Energy dispersive spectrometer Components Detector for x-rays detects one x-ray photon then switches off to process Processing electronics converts the charge pulse into voltage and stores in proper energy channel Computer to calibrate spectrum, peak intensity, identify peaks etc.

11 Detectors: semiconductor detector Most detectors are made from Si (p-i-n diode) When the semiconductor absorbs X-rays, electrons are transferred from valence to conduction band (creating electron-hole pairs) The energy per pair is known (3.8 ev for Si) so the number of pairs is linked to the X-ray energy Electrons and holes separated in p-i-n diode by a reverse bias and the resulting electron pulse measured

12 Detector Design

13 Semiconductor detector Cooling to very low temperature necessary Thermal energy creates e-h pairs (noise) FET noise (signal processing) Prevent Li atoms from diffusing Detector windows (to column) None: appropriate only in UHV (but best signal) Conventional Be: Robust, some X-ray absorption Thin windows: Less robust, but less absorption

14 Turning X-rays into spectra When an X-ray photon hits the detector: Electron-hole pairs are created, separated, captured The charge enters the FET amplifier and is converted to a voltage pulse The pulse is digitized and the X-ray energy computed The computer assigns the signal to the appropriate energy channel Note: the resolution is determined by the energy channel width. This should not be set too small!

15 Turning X-rays into spectra Important variables Time constant: the time to evaluate the magnitude of the charge pulse (typically μs). Longer gives better resolution but shorter gives more counts this is controlled by the system Dead time: The time the pulse processor is turned off while evaluating the pulse (between pulses). It is related to the input of X-rays In most cases the important thing it to have as many counts as possible!

16 Energy resolution Resolution limited by XEDS electronics Higher temperature, higher counts lead to decreased resolution

17 Things to know about the XEDS

18 The X-ray spectrum Element-specific characteristic peaks Natural linewidth 1-5 ev XEDS output linewidth ev Continuous non-characteristic background Artifact peaks originating from: the detector the specimen outside the region of interest elsewhere in the system

19 Artifacts from the Detector (Si)

20 Other X-rays Generated Bremsstrahlung X-rays occur when electrons are decelerated by interaction with atomic nuclei any energy up to beam energy Spurious X-rays come from the specimen but not from the chosen analysis region (from Bremsstrahlung X-rays or uncollimated electrons) System X-rays can come from elsewhere in the microscope than the specimen when electrons scattered by the sample strike other parts of the system

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22 Reduce post-specimen scatter Remove the objective aperture for XEDS Operate at zero tilt whenever possible Use a Be specimen holder and Be grids Use thin foils, flakes etc. rather than discs with bulk regions Also: measurements of the microscope without sample will indicate background

23 Qualitative XEDS Critical to understand what sample consists of Without proper qualitative XEDS, quantitative analysis is meaningless! ALL peaks must be identified, such that artifacts are understood and all present elements are accounted for Otherwise quantification cannot be accurate The more you know about the sample BEFORE analysis, the more reliable your analysis will be

24 Qualitative XEDS: Important Points Choose appropriate energy range: 0-40 kev Dead time should be below ~50% Counts. Time: high counts are very important, but long times can damage or possibly contaminate a sample To minimize damage, a larger probe size may be beneficial

25 Peak Identification Procedure Check most intense first Determine if it fits K, L, M Look for family peaks Look for artifacts Go to next intense peak and repeat procedure Look for artifacts

26 Peak Identification To identify a peak: Most intense peak: check for a good fit, first with Kα If a Kα line fits, check for Kβ at 10% energy must be present If Kα fits and the element is at least Cl, check for low-energy L peaks

27 Peak Identification If the most intense peak can NOT be identified as Kα, check if an Lα line fits If Lα fits, other L-family peaks must be present number visible will vary with La intensity and energy Check for higher-energy Kα/Kβ these must be present if the energy range is broad enough Check for M lines these may be present for larger elements if a lot is present

28 Peak identification If most intense peak is not Kα or Lα, check for an Mα fit this is only possible for very heavy elements! Mα and Mβ are difficult to resolve, but check for other small lines in the M family If an Mα line fits, there must be higher energy L lines, and possibly K lines may be detectable Note: peaks identification is easier if you recognize typical peak families!

29 Peak Identification: Challenges Family members may be missing if they are covered up by other peaks Pathological overlap: some elements have peaks very close together and cannot be resolved with the poor XEDS energy resolution Peak deconvolution: mathematical procedure to separate known peaks (read Section 34.4) Useful IF you know something about your sample!

30 Peak Visibility The existence of small peaks can be difficult to confirm when background is high Mathematical fitting can help to distinguish peaks from noise If small amounts of elements are expected to be present, very high numbers of counts can confirm their presence Be aware of specimen damage during long acquisition times!

31 Sample spectrum

32 Sample Spectrum

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34 Sample Spectrum 2