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EDX-Spectra Simulation

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Presentation on theme: "EDX-Spectra Simulation"— Presentation transcript:

1 EDX-Spectra Simulation
Optimization of Excitation Conditions and Detection Limit Calculations in EPMA F. Eggert, Röntgenanalytik Apparatebau GmbH, Berlin Introduction Theory of simulation complete spectra Applications of spectra simulation Determination of detection limits with spectra simulation Summary

2 EDX – Spectra Simulation Inroduction
Introduction Today the standardless evaluation of measured spectra is an established methodology in Electron Probe Microanalysis (EPMA) with Energy Dispersive Spectrometer (EDX) in Scanning Electron Microscope (SEM) New developments offer the possibility to calculate complete spectra in dependence to analytical conditions (spectra simulation). The basics are: - Exact knowledge about all X-ray lines of elements and about other atomic data - Knowledge about absolute cross-sections of both, the Characteristic X-rays and the Bremsstrahlung - Calculation of excitation and absorption of X-rays in specimen and detector (characteristic radiation and Bremsstrahlung) - Calculation of the entire Bremsstrahlung-deviation as the main background and simulation of other background components - Simulation of detector-resolution influence and count-statistics to simulate realistic spectra The content of presentation is to show the benefits of spectra simulation to daily analytical work with Electron Microscope and EDX.

3 EDX – Spectra Simulation Basics
Theory of Simulation The ratio of emitted counts of characteristic X-ray quanta to the counts of emitted Bremsstrahlung-quanta with same energy (in an specified energy region) is known as P/B-ratio (or P/U in this equation). Calculation of the Bremsstrahlung deviation for all spectra channels taking into account the self-absorption Albr and detector-absorption l in specimen.  mass absorption coefficients (µ/) = f (Z , E)  absorption jumps of (µ/) with energies EC X Lifshin empiric 2.parameters Kramers l is the index of current channel during spectra calculation

4 EDX – Spectra Simulation Basics
Theory of Simulation + All line- and shell- energies Relative emission rates of a single shell Excitation of sub-shells Coster-Kronig transitions Fluoresence yields Bremsstrahlung + Lines Escape + Artefacts (ICC) Count statistics (Noise) ____________________ = Simulated Spectrum (2000 cps, 3 minutes)

5 The accuracy of data base is crucially for quality of simulation!
EDX – Spectra Simulation Basics Atomic Data Library (Data Base) To make the simulation possible, an atomic data library with fast access to all element specific data is necessary: The accuracy of data base is crucially for quality of simulation!

6 EDX – Spectra Simulation Application
Optimization Before the Measurement: Eo 15 keV 20 keV 25 keV 30 keV

7 EDX – Spectra Simulation Application
Verification: Excitation of Lines (Eo) Excitation of Au-L lines (Sub-Shells !) with different Eo

8 EDX – Spectra Simulation Application
Optimization / Verification: Tilt-Angle AuAg-Alloy Eo: 15 keV tilt: -30o...+30o Simulation Absorption-Effects: - Irregular Surfaces - Rough Specimen - Particle

9 EDX – Spectra Simulation Application
Optimization: Influence of Detector-Resolution AuAg-Alloy: eV vs. 165 eV

10 EDX – Spectra Simulation Application
Verification of Possible Overlap-Problems 5% Pd in Pb with/without Pd

11 EDX – Spectra Simulation Application
Element-Identification (Verification of Unknown Peaks) Si in Specimen ? ...with Escape ... without Escape No !

12 EDX – Spectra Simulation Application
Element-Identification (Comparison with Real Spectra) Spectrum with Ba ...measured spectrum ...simulated spectrum Additional elements ? Improve data-base ? Compare !

13 EDX – Spectra Simulation Application
Teaching (Simulation of EDX X-Ray Acquisition Process) 15s Acq.time 2000 cps „Acquisition“ ready ...

14 EDX – Spectra Simulation Detection Limits
Calculation of Detection Limits The question is, whether an element in specimen with expected concentration is detectable or not? If an element is detectable... How are the optimal measurement and excitation conditions (SEM and spectrometer parameters) and how long does it take (acquisition time)? The signal/background-ratio is the base for calculations of detection limits ( P/B-ratio) ... determination is possible with spectra-simulation ! Counts Counts Probability Probability Significance Level NS Detection Limit NDL

15 EDX – Spectra Simulation Detection Limits
Detection-Limit of an Element with Different Specimens MDL for Pd in Te M L K MDL for Pd in Au

16 EDX – Spectra Simulation Detection Limits
Detection-Limits with Varying Conditions Al in Cu M L K

17 EDX – Spectra Simulation Detection Limits
Simulation of Spectra-Acquisition Near Detection-Limits  MDL = 0.2 % Significant element presence ! Concentration below the detection-limit ! Is it really possible ... ? Yes  You had luck ! Al: 0.15 % Al: 0.3 % #1 #3 #2 Al: 1 %

18 EDX – Spectra Simulation Detection Limits
Simulation of Spectra Acquisition / Detection Limit = f (time) 5 s: MDL = 1.8% 10 s: MDL = 1.3% 20 s: MDL = 0.9 % detectable ! 50 s: MDL = 0.6 % 100 s: MDL = 0.4 % 2000 cps 1% Zr in Sn ?

19 EDX – Spectra Simulation Summary
It is possible to calculate the entire EDX-spectrum with a standardless EPMA-correction model taking into account all effects of specimen- and detector-interaction. Spectra simlation is useful for a better understanding and interpretation of measured spectra. With spectra simulation all complex effects of excitation, absorption and detection are shown very descriptive and didactically (teaching, coaching, …) The simulation of several excitation situations gives the possibility to optimize all conditions even before the actual specimen maesurement and data acquisition. With spectra simulation the analyst is able to make estimations for detection limits. Effects of counting-statistics are possible to verify. Future View:  Application of spectra simulation for interactive qualitative analysis (displacement of simple line-mark identification) Calculation of entire spectrum for a visual comparison after quantitative evaluation (reconstruction) for an improvement of final result-reliabilities

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