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Status and future plan of scanning system in Japan

This meeting discusses the evaluation of the effective area and recent updates in scanning speed for a scanning system in Japan. The goal is to define the effective area by analyzing the distortion map obtained from ellipticity measurements of 40 nm silver nanoparticles.

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Status and future plan of scanning system in Japan

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  1. 2019/6/13 – 2019/6/14 NEWSdm Collaboration meeting Status and future plan of scanning system in Japan Ryuta Kobayashi

  2. Contents • Evaluate effective area • Recently update of scanning speed

  3. Effective area evaluation

  4. introduction motivation Need to calculate effective scanning speed define effective analysis volume To decide effective area in 1st scanning(Ellipse analysis) in edge of view cannot get a true information optical image has distortion ・ellipticity ・angle Cause contamination of fog event <- need to limit analysis area • this is one of the reasons for losing effective area Need to ・understand the distortion effect of the scanning area ・decide effective area from this effect

  5. Flow of define effective area understand the distortion effect of the scanning area Goal : make distortion map ≒ ellipticity map of 40 nm silver Nano particle 1. Scan 40 nm Ag sample 2. Get ellipticity and angle map of 40 nm Ag -> distortion map decide effective area from this effect Goal : define effective area by ellipticity threshold 3. Calculate center of distortion Get ellipticity distribution per distance from center 5. Get the ellipticity threshold which can analysis the event in each distance

  6. Sample info • Sample : 40 nm Ag Nano particle • Thick of sample : 1.5 um • Scanned Area : 5mm × 5mm (5202 view) • Number of event : 780238 events (150 events /view)

  7. 0°< Angle < 180° Make distortion map How to make ? 0° 1. Separate area per 64 × 64 pixel (PTS3 has 2048 ×1088pixel -> 32 × 17 area is created) 90° Example of gaussian fitting (use python library limfit) 2. For each 64× 64 area Define representative value of ellipticity and angle 180° Ellipticity Use mean value Angle Fit histogram by gaussian Use center value of gaussian Ellipticity is calculated by FFT and center of brightness moment

  8. angle = peak angle(0 °– 180°) color = mean ellipticity Distortion map 1 Vector = 64 * 64 pixel

  9. Distortion map

  10. Flow of define effective area done understand the distortion effect of the scanning area Goal : make distortion map ≒ ellipticity map of 40 nm silver Nano particle 1. Scan 40 nm Ag sample 2. Get ellipticity and angle map of 40 nm Ag -> distortion map next decide effective area from this effect Goal : define effective area by ellipticity threshold 3. Calculate center of distortion Get ellipticity distribution per distance from center 5. Get the ellipticity threshold which can analysis the event in each distance

  11. Distortion Map (X, Y projection) Color : number of events

  12. Distortion Map (X,Y projection) Event select ・ 100 < Max – bg brightness < 200 ・ 35 < mean – bg brightness < 80 ・ 35 < npix < 75 ・ 3 < minor < 5

  13. Distortion Map (X,Y projection) Only center Events

  14. Decide center of distortion Use representative value of ellipticity in 64×64pixel area Useonlycenterarea Select only center events(500 < y <600) In X projection, 500 < y < 600 In Y projection, 800 < x < 1000 Fit by Use b for center position center of distortion is defined (X , Y) = (918.0 , 468.0)

  15. Event selection Cut condition by brightness, minor, ellipticity 780238 events -> 7986 events ・ 100 < Max – bg brightness < 200 ・ 35 < mean – bg brightness < 80 ・ 35 < npix < 75 ・ 3 < minor < 5 Decide by 100 keV C ion signal region Manual check (all events : 7986 events) Ag nano event : 7624 events BG events : 362 events

  16. Get ellipticity distribution in each radius Events () radius Center of distortion

  17. Normalizebyarea Histogram width is expanded by optical aberration

  18. How to decide ellipticity threshold Event num within radius : N Leak rate : r If N ・r < 50 not defined ellipticity threshold Ellipticity threshold Because Linearity of effective area and elliptical threshold is broken N・r events

  19. Distance from center of distortion VS ellipticity threshold リークレートを変えたときの領域ごとの楕円率閾値の変化

  20. Relation Radius and effective area radius Center of distortion By using this, Convert radius to effective area

  21. Relation ellipticity threshold and effective area ・Convert radius to rate of effective area ・exchange axis

  22. Scanning Speed update

  23. Review of past Scanning status Detail status of image processing Taking image Update these today. 1.3s 0.8 s Taking picture Image processing 1.31 s Tracking Moving and dumping time of stage 0.85 s 0.48 s 1.5 s/View Recognize surface ・画像フィルタ 　・二値化 0.1 s Scanning speed Our goal • 21.9g/year Within 0.1 s/View

  24. Recently updateof image processing 1.3 [s/view] Taking image all process time 0.8 s 1.5 s/View Use high luminosity Light source And increase frame rate 150 fps -> 300 fps 1.25 s/View 0.6 [s/view] Taking image Tracking If use all area for analysis Scanning speed • 26.3g/year Parallelization image processing 0.4 s 0.48 s 0.1 s Tracking ↑Ideal Max scanning speed Recognize surface 0.1 s Recognize surface 0.1 s

  25. Scanning Speed Max Scanning speed × effective area = effective scanning speed Effective area is changed by ellipticity threshold -> scanning speed is defined by ellipticity threshold Ideal Max scanning speed only 1st scanning

  26. Thinkabout real scanning Scan flow Idealscan flow Event scan Full volume scan More scanning 2nd scanning Ellipse fitting (save images, get detail info) use higher magnification lens (in future) 1st scanning Ellipse fitting (save no image) ・Multi wavelength ・phase contrast ・polarization Assumption Fog event : 0.3 – 0.4 events /view ( (3 ~ 4) events /1) In 2nd Scan Number of scan event Fog event * leak rate + dust event Change able By situation ・batch ・cut etc. dust event : 0.3 – 0.4 events /view ( (3 ~ 4) events /1) Scanning speed Without saving image 1.25 s/view -> 26.3 g/y With saving image 2.25 s/view (2.25 s/event) 20% leak 18640 -> 1.86倍 (1.18 g/month) 10% leak 17920 -> 1.79倍 (1.23 g/month) 5% leak 17560->1.75倍 (1.26 g/ month) 1% leak 17272 -> 1.73倍 (1.27 g/month) 0% leak 172001.72倍 (1.28 g/month) 1st 10000 view 2nd (4000* leak + 4000 event)

  27. 20% leak (1.18 g/month) * effective area 10% leak (1.23 g/month) * effective area 5% leak (1.26 g/ month) * effective area 1% leak (1.27 g/month) * effective area 0% leak (1.28 g/month) * effective area

  28. Ellipse fitting has 2 type ・Open CV function need not to save images ・FFT only offline -> need to save images Practical scan flow Event scan Full volume scan More scanning ・Multi wavelength ・phase contrast ・polarization Scanning time 1.25 s/view speed 26.5 g/y 1st scanning Ellipse fitting (save no image) Open CV ellipse analysis Scanning time 2.25 s/event 2nd scanning Ellipse fitting (save images, get detail info) With FFT ellipse analysis use higher magnification lens (in future) Pattern 1 Scanning time 2.25 s/view speed 14.7 g/y Ellipse fitting (save images) With FFT ellipse analysis Pattern 2

  29. Pattern 1 Old ellipse fitting -> no correlation between low ellipticity and length Need to use loose ellipse threshold in 1st selection -> only use brightness cut and size cut(minor , npix) -> cut almost fog event in 2nd selection? Pattern 2 Pattern 2 Need to use loose ellipse threshold -> only use brightness cut and size cut(minor , npix) -> cut almost fog event in 2nd selection?

  30. Other Option Decrease saving images time This option need to buy SSD and expand card (300,000 yen is need to buy) Time of saving images time 1 s/view (HDD) -> if use SSD(M.2, NVMe (NVM Express)) < 0.1 s /view Need test expansion card of SSD (I had tried only SSD attached directory mother board) Pattern 2 Other plan for decrease saving image time ・decrease save volume (save only event pictures) ・develop FFT analysis for online <- for future development

  31. Extra thought experiment If change number of dust events Number of dust also affect to scanning speed (effect of 2nd scanning time)

  32. Problem toward increase scanning speed Cause of limit scanning speed Scanning machine ability (Max speed 26.3 g/year) ・camera speed ・moving stage velocity ・scanning volume Effective scanning volume (lost scanned volume) Quantity of BG event (for 2nd scanning) ・opticalaberration ・fog ・dust

  33. Future plan Improve scanning machine ability ・High speed camera Need to camera software adopt to high speed camera At least , it takes 3 months 300 fps → 1000 fps Scanning time 1.25 -> 1.0 s/view Max Scanning speed 33.1 g/ y ・Shorten moving time <- Decrease dumping effect Use strobe light source 0.85 s/view -> 0.1 s/view Scanning time 1.0 -> 0.2 s/view Max Scanning speed 165.6 g/ y

  34. Expand effective area ・Shorten wave length range Decrease color aberration effect ・aberration correction by program Correct aberration by using distortion map

  35. Back up

  36. Cameralink規格 @ PTS3 2M Camera , Full 2M pixel * 116 picture = 232 MB 232 [MB/View] / 680 [MB/s] = 0.341 s/View http://jiia.org/wp-content/themes/jiia/pdf/fsf.pdf

  37. FFT Open CV ellipse fitting

  38. Old(open cv function) New(FFT function)

  39. ・ 100 < Max – bg brightness < 200 ・ 35 < mean – bg brightness < 80 ・ 35 < npix < 75 ・ 3 < minor < 5 Event select X,Y projection Manual cut

  40. Manual cut

  41. Old(opencv ellipticity) projection

  42. Old(Open CV ellipse fitting) NEW(FFT ellipse analysis)

  43. New (FFT) Old (open cv)

  44. Assumption Fog event : 0.3 – 0.4 events /view ( (3 ~ 4) events /1) dust event : 0.3 – 0.4 events /view (( (3 ~ 4) events /1)) after ellipse 1st 10000 view 2nd (4000* leak + 4000 event) Scanning speed Without saving image 1.25 s/view -> 26.3 g/y With saving image 2.25 s/view (2.25 s/event) 10 % leak 固定9 Dust event 4 event / g 17920 -> 1.79倍 (1.23 g/month) 1 12520-> 1.25倍 (1.76 g /month) 1 10900-> 1.09倍 (2.02 g/month) 1 10738-> 1.074倍 (2.05 g /month) 1 (electron BG)10721-> 1.0721 (2.06 g/month) 0 10720 -> (2.06 g/month) 1 + 1% leak 10073.8 (2.19 g/month) 0 + 0 leak 10000 (2.208 g/month)

  45. 1st 10000 view 2nd (4000* leak + 4000 event) If image save time = 0 20% leak 14800 -> 1.48倍 (1.49 g/month) 10% leak 14400 -> 1.44倍 (1.53 g/month) 5% leak 14200->1.42倍 (1.56 g/ month) 1% leak 14040 -> 1.404倍 1.57 g/month) 0% leak 140001.4倍 (1.58 g/month) O dust + 0 leak 2.208 g / month 20% leak 18640 -> 1.86倍 (1.18 g/month) 10% leak 17920 -> 1.79倍 (1.23 g/month) 5% leak 17560->1.75倍 (1.26 g/ month) 1% leak 17272 -> 1.73倍 (1.27 g/month) 0% leak 172001.72倍 (1.28 g/month) 1 + (fog * leak / 10000)

  46. 20% leak (1.18 g/month) 10% leak (1.23 g/month) 5% leak (1.26 g/ month) 1% leak (1.27 g/month) 0% leak (1.28 g/month)

  47. For shorten saving images time • Decrease save file volume • Save only event images • 2MB * 116 pictues / view = 232 MB/view • -> 1.2 kB * 100 event /view = 1.2 MB/view • Increase saving time • HDD -> SSD(M.2) • 1s/view -> 0.1-0.2 s/view • SSD(M.2) Max volume 1-2TB / SSD • Mather board has 1~2 slot for SSD(M.2) • Expand card is need to attach more SSD

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