Silicon pixel detectors with some info also on Strip and Drift detectors

1. Silicon pixel detectorswith some info also on Strip and Drift detectors

2. Summary • What is a silicon pixel detector and how it works • Sensors and readout electronics • Tests and irradiation studies • From single modules to complex detectors • A study case: The ALICE silicon vertex detector

3. Main Features • Two-dimensional segmentation detectors • Required for high quality vertexing capabilities (primary and secondary vertices, impact parameter,…) • Sizes of row and colums adapted to the needs Row Column

4. Main Features • Basic structure: a two-dimensional matrix (detector ladder) of reverse-biased silicon detector diodes (sizes: tens - hundreds of microns) flip-chip bonded to readout electronic chips • Each cell on the detector matrix is bonded to an equivalent cell on a CMOS chip, which contains most of the required electronics for that channel • Usually only binary information provided, with a selectable threshold

5. Main Features • Production of practical silicon pixel detectors made possible by the R&D progress in • component density achievable in CMOS electronic chips • development in flip-chip bonding techniques

6. Advantages vs disadvantages • Advantages: • True two-dimensional segmentation • Geometrical precision • Double-hit resolution • High signal-to-noise ratio • High speed • Disadavantages: • Only digital information • Large increase in number of connections and electronic channels • Fabrication techniques still in progress • Several phases of the process critical

7. The hybrid pixel detector Cell size: 50 x 425 microns Thickness around 200 + 200 microns

8. The hybrid pixel detector 1200 chips A matrix of 8192 (32 x 256) independent cells is envisaged for each individual pixel chip in ALICE ~ 10 M channels

9. Electronic readout • Sensible progresses achieved in the number of channels, response uniformity, individual cell control and radiation tolerance

10. Evolution of the readout pixel chip families Omega 3 (WA97/NA57) Omega 2 (WA97/NA57) ALICE2 Test ALICE1 Test

11. Development of the readout electronics Prototype Cell size No. of cells Technology Omega 2 75 x 500 16 x 63 3  Omega 3 50 x 500 16 x 127 1  ALICE1 test 50 x 420 2 x 65 0.5  ALICE2 test 50 x 420 2 x 65 0.25  ALICE1 50 x 425 32 x 256 0.25 

12. Bump-bonding techniques

13. The expected radiation dose Evaluation of the expected dose in the ALICE ITS by GEANT and FLUKA simulations taking into account 10 years operational period Layer type Cumulated dose (krad) 1 pixel 130 2 pixel 40 3 drift 13 4 drift 5 5 strip 2 6 strip 1.5

14. Irradiations of the readout electronics List of irradiations tests carried out on the ALICE readout chips

15. From single modules to complex detectors • To build a large detector with many channels several problems must be solved • ALICE: about 10 M channels • ATLAS: about 100 M channels

16. From single modules to complex detectors • Mass production organization • Mechanics and assembly • Cooling • Beam tests • Installation procedure • ...

17. Mass production after R&D • After an extensive period of R&D, a mass production activity must be organized: • sensors and electronics chip tests • qualification criteria • time schedule • efficiency evaluation • ...

18. ALICE silicon pixel detector: a case study

19. Wafer test procedures • For ALICE each wafer has 86 • readout chips • Tests to be carried out on each chip: • Current consumption (analog/digital) • JTAG functionality • Scan of all DACs • Determination of minimum threshold • Complete threshold scan of pixel matrix

20. Wafer probing Bridge to PC MB-card Power Supply VME-crate with pilot and JTAG controller Power Supply Probe Station with Probe Card CLEAN ROOM

21. Wafer probing: hardware Semiautomatic Probe Station Electronics

22. Wafer probing: software LabView-based programs Analysis with Root/C++

23. Typical results from a chip Threshold distribution A mean threshold of 17 mV corresponds to about 900 electrons. Noise Distribution A mean noise of 2.3 mV corresponds to about 120 electrons.

24. CLASS AM9VG4T AB9VHXT AZ9VETT AV9VGWT I 46 (53%) 36 (42%) 64 (74.5%) 37 (43%) II 10 (12%) 8 (9%) 8 (9%) 5 (6%) III 30 (35%) 36 (42%) 14 (16.5%) 35 (41%) Readout CHIP classification Chips classified as Class I (to be bump-bonded), Class II (minor defects), Class III (major defects)

25. CHIP classification • Minor Defects (CLASS II): • parts or whole columns are missing (no test-column effect!) • many noisy pixels (>1%) • inefficient pixels (>1%) • high threshold or noise (th> 30mV, noise>3mV) • Chips for Bump Bonding (CLASS III): • threshold<30mV (~2000 electrons rms) • no missing columns or parts of columns • no excess in current consumption • less than 1% of faulty pixels (noisy, inefficient) • test-column effect ignored

26. Beam tests at the CERN SPS 1 scintillator 2 scintillators plane 2 plane 1 plane 3 x-y table Bench 1 large scintillator Layout of the experimental set-up for ALICE pixel detector beam tests

27. The ALICE pixel project The ALICE pixel project requires joint efforts from physicists, engineers, technicians,… A (not exhaustive) list of items under way or finalized: Development of front-end chip Bump bonding and assembly techniques Carrier Bus development Electronics for control and data transfer Carbon fiber mechanics Hardware and software alignment Cooling system Test of detectors under beam Simulation tools for detector response ...

28. Conclusions Silicon pixel detectors are now widely used in LHC experiments Only recently the process of building a large detector is entirely reliable There is room for further progresses in the field New applications of pixel detectors (Medicine, …) are being exploited

29. Silicon strip detectors

30. Principles of operation • Basic motivation: charged particle position measurement • Use ionization signal (dE/dx) left behind by charged particle passage _ + _ + _ + _ + • Use the drift chamber analogy: ionization produces electron-ion pairs, use an electric field to drift the electrons and ions to the oppositely charged electrodes. • In a solid semiconductor, ionization produces electrons-hole pairs. For Si need 3.6 eV to produce one e-h pair. In pure Si, e-h pairs quickly recombine  need to drift the charges to electrodes … but how?

31. Principles of operation • Charge collection • Need to isolate strips from each other and collect/measure charge on each strip  high impedance bias connection (resistor or equivalent) • Usually want to AC couple input amplifier to avoid large DC input currents • Both of these structures are often integrated directly on the silicon sensor. Bias resistors via deposition of doped polysilicon, and capacitors via metal readout lines over the implants but separated by an insulating dielectric layer (SiO2 , Si3N4). – h+ e- +

32. Principles of operation Most probable charge ≈ 0.7 mean • Magnitude of collected charge • Usually specified in terms of minimum ionizing deposition: Mean charge (dE/dx)Si = 3.88 MeV/cm, for 300m thickness  116 keV This is mean loss, for silicon detectors use most probable loss (0.7 mean)  81 keV 3.6 eV needed to make e-h pair Max collected charge  22500 e (=3.6fC)

33. Principles of operation • Charge collection time, diffusion • Drift velocity of charge carriers v=E, so drift time, td = d/v = d/E • Typical values: d=300 m, E= 2.5kV/cm, e= 1350 cm2 / V·s, h= 450 cm2 / V·s, so td(e)= 9ns , td(h)= 27ns • Diffusion of charge “cloud” caused by scattering of drifting charge carriers, radius of distribution after time td:  = 2Dtd , where D is the diffusion constant, D=kT/q • Same radius for e and h since td 1/ • Typical charge radius: ≈ 6m, could exploit this to get better position resolution due to charge sharing between adjacent strips (using centroid finding), but need to keep drift times long (low field).

34. p p p n Principles of operation Obvious question: why not get a 2nd coordinate by measuring the position of the (electron) charge collected on the opposite face? • Double-sided detectors • This is possible and is often done but is not as simple as it might seem. • Problem: unlike the face with the p-strips, nothing prevents charge to spread horizontally on the back face.

35.  = p/ 12 Performance If one treats the detected charge in a binary way (threshold discrimination), the resolution is simply: • Position resolution: strip pitch and read-out pitch As mentioned earlier, if the charge distribution is shared between adjacent strips, can use centroid finding to improve this resolution. However, since typical charge distribution sizes are of order 5-10 m this implies quite fine strip pitch. In fact it is not practical to make sensors of pitch less than 20m and most are greater. Test devices have been made that have achieved  < 3.0m (using read-out pitch of 25 m), this is near the limit on precision determined by diffusion and statistical fluctuations of the ionizing energy deposition. Read-out electronics pitch limit is 50m and time/cost constraints often argue for even larger read-out pitches. Fortunately there is a trick to preserve resolution with larger read-out pitch...

36. Performance • Position resolution: capacitive charge division If one reads out only every nth strip but preserves the signal magnitude, the charge gets shared such that the centroid resolution is nearly that obtained by reading out every strip. The limitation is that some signal is lost (capacitive coupling to the backplane) and noise is a bit higher (more input capacitance) and one loses two track separation capability. This is clearly an economic solution in the case of low occupancy and has been used extensively. It does require a good signal/noise ratio, our next topic.

37. Performance noise distribution Landau distribution with noise • Signal to noise ratio (S/N) • Why is it important? Landau distribution has significant low energy tail which becomes even lower with noise broadening. One usually has low occupancy in silicon sensors  most channels have no signal. Don’t want noise to produce fake hits so need to cut high above noise tail to define good hits. But if too high you lose efficiency for real signals. The centroid determination is also degraded by poor signal to noise. • Signal • Basic signal produced is ≈ 22500 e • Typical losses of 5-10% depending on the nature of the chosen electrical network (AC coupling capacitor, stray capacitances and resistances) and front-end electronics.

38. Summary • Silicon strip detectors • - Built on simple p-n junction diode principle, now a “mature” technology • - Widespread use and cost drop thanks to microelectronics industry • - Many options and design possibilities • - Replaces wire chambers in high radiation

39. Silicon drift detectors

40. Particle n+ n+ n+ P+ P+ P+ P+ P+ - + n + - - + P+ P+ P+ P+ P+ P+ Principles of operation The transport of electrons, in a direction parallel to the surface of the detector and along distances of several cm, is achieved by creating a drift channel in the middle of the depleted bulk of a silicon wafer. At the edge of the detector, the electrons are collected by an array of small size anodes. The measured drift time gives information on the particle impact point coordinate y. The charge sharing between anodes allows the determination of the coordinate along the anode direction x. x y

41. Principles of operation

42. Large scale applications Large scale applications of such detectors require low cost, high quality and high production yields Silicon Drift Detectors are now in operation or planned as part of LHC experiments

43. SDD in ALICE Average spatial precision r  /z 38 /28 m Cell size 150 x 300 m Detector area 72.5 x 75.3 mm Total number of readout channels 133 K Total number of cells 34 M