1. Update on 50 um Sensor Calibration using LNLS Data Mathieu Benoit

2. Outline Reminder of previous results – XAFS – Fluorescence measurements Improved Calibration procedure Calibration of A06-W0110 and results

3. Energy Measurements with monochromator (XAFS1) X-Ray incident beam goes to Crystal Monochromator and is then delivered to the experimental area. Energy can be selected with 0.1keV accuracy along the 5-15 keV range. 2 sensors (C04-W0110,D09-W0126) were tested in this beamline to obtain single pixel calibration for a subset of pixel (beam 2.5x3mm2) Analysis on one of the sample will be presented by Mateus Vincente for UFRJ

4. Global Surrogate Fit After disscusion with LNLS experts, it seems there is a problem with the XAFS1 bealine energy calibration, a new calibration will be performed and hopefully correction to the dialed energy will be provided

5. Fluorescence measurements (MX1) TargetCoCrCuFeMnNiTiVZn E (kα) in keV 4.514.955.4145.896.46.937.478.048.63 X-Ray beam (7.9,15.8 keV) 1e12 photons/ s Target Fluorescent photons field ~ 1000 single pixel clusters per pixel / 50k frames (1ms integration) -> ~30-45 min per fluo Only tested with one assembly (A06-W0110) but possibility to run multiple assemblies at the same time (Large Fluorescence radiation field ) Timepix+FITPix

6. Single Pixel TOT Spectrum First Harmonic scattered

7. Calibration Curve

8. Single Pixel Energy Spectrum First Harmonic scattered

9. Improved Calibration procedure Clustering (>15 keV) Extraction of 65k Histogram to ROOT Format (TH1) Clustering (>15 keV) Extraction of 65k Histogram to ROOT Format (TH1) Raw Data 65k Histograms per source Peak Value extraction (Tspectrum +1.5 sigma gaussian fit) N*65k peak values per source Iterative surrogate fit: Bad point taken out from fit Iterative surrogate fit: Bad point taken out from fit The calibration code has been optimized to reduce execution time : Take advantage of large memory -> Parallel processing of 65k pixels Skip clustering for low energy (low charge sharing probability for thin sensors) ROOT6 -> TreeReader C++ Subroutine implemented for big data parsing A factor 1000 has been gained in calibration speed !! (4-5 hours on a single CPU vs a 15-20h on 256 CPUS )

10. Peak TOT Distribution

12. Surrogate Fit example

13. Threshold dispersion 870 +- 60 electrons

14. Shift between Fe55 and the rest of dataset

15. Chi2 Distribution

16. Calibrated results Pixel per pixel calibration, E=5.812261 +- 0.669641 Global calibration, E=5.740523 +- 0.672768 Clustered Pixel per pixel calibration, E=5.628588 +- 0.567811 Fe 55 E=5.89 keV

17. Calibrated results ---- fit results : Cd109 ---- Pixel per pixel calibration, E=23.493483 +- 2.538012 Global calibration, E=22.919686 +- 2.410405 Clustered Pixel per pixel calibration, E=24.805484 +- 2.719838 Cd109 E=22-25 keV

18. Calibrated results ---- fit results : Am241 ---- Pixel per pixel calibration, E=59.221432 +- 3.938544 Global calibration, E=64.852706 +- 4.131776 Clustered Pixel per pixel calibration, E=61.352736 +- 4.223673 Am241 E=13.9,26.3,59.5 keV

19. Conclusion A06-W0110 has been fully calibrated using LNLS Data + Am241 + Cd109 Analysis time has been reduced by a factor 1000! A few more points can be improved for the surrogate fit (better selection of points, Chi2 cuts etc...) Calibration results have limited effects compared to global calibration, however, calibration is still needed for comparison to simulation LNLS propose to perform XRF measurements on more assemblies for us if needed, UFRJ Rio student ready to go to Campinas to take measurements for us