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  • Technical Review
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Applications of silicon strip and pixel-based particle tracking detectors

Abstract

As the review of the European particle physics strategy is underway and planned future particle accelerators are being discussed worldwide, new, improved silicon tracking detector concepts are currently being studied for use at the proposed new facilities. This Technical Review outlines the current state of the art in silicon tracking detectors for particle physics along with examples of some recent applications in other areas. The various technologies currently available in particle physics are listed and their relative merits for different uses and environments are discussed. The silicon detector research programmes to allow optimal scientific returns from future particle physics experiments are described along with their current status.

Key points

  • Particle physics experiments depend on the ability to accurately track the paths of particles produced in high-energy collisions.

  • Frontier experiments demand ever higher collision rates both to maximize sensitivity to rare processes and subtle effects, and to minimize the statistical errors on measurements.

  • The high-rate capability, tracking precision, sensor granularity, readout speed and radiation resistance of the current generation of silicon detectors has led to their widespread adoption, particularly in collider experiments (which typically require the most demanding specifications).

  • New technologies are emerging, both from within particle physics and through the design of specialist variants of commercial optical sensors, which offer significant improvements in terms of particle-track spatial resolution, fast-timing capability, detector radiation hardness, scattering material and cost per unit area.

  • Other disciplines that already use particle physics silicon tracking technologies can only benefit from adopting these developments as they become available.

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Fig. 1: Timeline of the different detector technologies with a few illustrated detectors from different experiments: NA14, DELPHI and CMS at CERN, CDF at Fermilab, STAR at the Relativistic Heavy Ion Collider and Belle II at KEK.
Fig. 2: Principle of charged particle detection and schematic of a reverse-biased diode.
Fig. 3: The evolution of the silicon detector technology over the past decades.

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References

  1. Moore, G. Cramming more components onto integrated circuits, Electronics 38, 114–117 (1968).

  2. Hartmann, F. Evolution of Silicon Sensor Technology in Particle Physics 2nd edn (Springer, 2017).

  3. Moll, M. Displacement damage in silicon detectors for high energy physics. IEEE Trans. Nucl. Sci. 65, 1561–1582 (2018).

    Article  ADS  Google Scholar 

  4. Spieler, H. Semiconductor Detector Systems (Oxford Univ. Press, 2005).

  5. Garcia-Sciveres, M. & Wermes, N. A review of advances in pixel detectors for experiments with high rate and radiation. Rep. Prog. Phys. 81, 066101 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  6. Lutz, G. Semiconductor Radiation Detectors (Springer-Verlag, 1999).

  7. Dijkstra, J. L. H. Overview of silicon detectors. Nucl. Instrum. Methods A 494, 86–93 (2002).

    Article  ADS  Google Scholar 

  8. Sze, S. Physics of Semiconductor Devices 2nd edn (Wiley, 1981).

  9. Sze, S Semiconductor Devices, Physics and Technology (Wiley, 1985).

  10. Horisberger, R. Pixel detectors for LHC. Nucl. Instrum. Methods A 284, 185–191 (1996).

    Article  ADS  Google Scholar 

  11. Apollinari, G. et al. High-Luminosity Large Hadron Collider (HL-LHC) Technical Design Report CERN-2017-007-M (CERN, 2017).

  12. The High Luminosity LHC (HL-LHC) Accelerator Project http://hilumilhc.web.cern.ch/.

  13. The CMS Collaboration CMS Technical Design Report for the Pixel Detector Upgrade CERN-LHCC-2012-016 (CERN, 2012).

  14. The CMS Collaboration CMS, Tracker Technical Design Report CERN-LHCC-98-06 (CERN, 1998).

  15. Azzi-Bacchetta, P. et al. The CDF intermediate silicon layers detector. Nucl. Phys. Proc. Suppl. 78, 307–310 (1999).

    Article  ADS  Google Scholar 

  16. The ATLAS Collaboration The Inner Detector Technical Design Report CERN-LHCC-97-16 and CERN-LHCC-97-17 (CERN, 1997).

  17. The ATLAS Collaboration Technical Design Report for the ATLAS Inner Tracker Pixel Detector CERN-LHCC-2017-021 (CERN, 2017).

  18. Abbott, B. Production and Integration of the ATLAS insertable B-layer. J. Instrum. 13, T05008 (2018).

    Article  Google Scholar 

  19. The CMS Collaboration The Phase-2 Upgrade of The CMS Tracker CERN-LHCC-2017-009 (CERN, 2017).

  20. The ATLAS Collaboration Technical Design Report for the ATLAS Inner Tracker Strip Detector CERN-LHCC-2017-005 and ATLAS-TDR-025, (CERN, 2017).

  21. Moll, M. & Casse, G. RD50 Collaboration, CERN https://rd50.web.cern.ch/rd50/.

  22. Unno, Y. et al. Development of n+-in-p large-area silicon microstrip sensors for very high radiation environments — ATLAS12 design and initial results. Nucl. Instrum. Methods A 765, 80–90 (2014).

    Article  ADS  Google Scholar 

  23. The RD53 Collaboration RD53A Integrated Circuit Specifications CERN-RD53-PUB-15-001 (CERN, 2015).

  24. Parker, S., Kenny, C. & Segal, J. 3D — a proposed new architecture for solid-state radiation detectors. Nucl. Instrum. Methods A 395, 328–343 (1997).

    Article  ADS  Google Scholar 

  25. Da Via, C. et al. 3D silicon detectors status and applications. Nucl. Instrum. Methods A 549, 122–125 (2005).

    Article  ADS  Google Scholar 

  26. Pellegrini, G. et al. First double-sided 3-D detectors fabricated at CNM-IMB. Nucl. Instrum. Methods 592, 38–43 (2008).

    Article  ADS  Google Scholar 

  27. Sadrozinski, H. et al. Ultra-fast silicon detectors (UFSD). Nucl. Instrum. Methods A 831, 18–23 (2016).

    Article  ADS  Google Scholar 

  28. Cartiglia, N. et al. The 4D pixel challenge. J. Instrum. 11, C12016 (2016).

    Article  Google Scholar 

  29. The LHCb Collaboration LHCb Vertex Locator Technical Design Report CERN-LHCC-2001-011, (CERN, 2001).

  30. Collins, P. The LHCb VELO (VErtex LOcator) and the LHCb VELO upgrade. Nucl. Instrum. Methods A 699, 160–165 (2013).

    Article  ADS  Google Scholar 

  31. Sadrozinski, H. et al. 4D tracking with ultra-fast detectors. Rep. Prog. Phys. 81, 026101 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  32. Cartiglia, N. et al. Beam test results of a 16 ps timing system based on ultra-fast silicon detectors. Nucl. Instrum. Methods A 850, 83–88 (2017).

    Article  ADS  Google Scholar 

  33. The FCC Collaboration The future circular collider study https://fcc.web.cern.ch/Pages/default.aspx.

  34. Faccio, F. et al. Radiation-induced short channel (RISCE) and narrow channel (RINCE) effects in 65 and 130 nm MOSFETs. IEEE Trans. Nucl. Sci. 62, 2933–2940 (2015).

    Article  ADS  Google Scholar 

  35. Menouini, M. et al. 1 GRad total dose evaluation of 65 nm CMOS technology for the HL-LHC upgrades. J. Instrum. 10, C05009 (2015).

    Article  Google Scholar 

  36. Peric, I. A novel monolithic pixelated particle detector implemented in high-voltage CMOS technology. Nucl. Instrum. Methods A 582, 876–885 (2007).

    Article  ADS  Google Scholar 

  37. Wermes, M. From hybrid to CMOS pixels… a possibility for LHC’s pixel future? J. Instrum. 10, C12023 (2015).

    Article  Google Scholar 

  38. Pernegger, H. et al. First tests of a novel radiation hard CMOS sensor process for depleted monolithic active pixel sensors. J. Instrum. 12, P06008 (2017).

    Article  Google Scholar 

  39. Besson, A. et al. From vertex detectors to inner trackers with CMOS pixel sensors. Nucl. Instrum. Methods A 845, 33–37 (2017).

    Article  ADS  Google Scholar 

  40. Price, T. MAPS technology for vertexing, tracking, and calorimetry. Phys. Proc. 37, 932–939 (2012).

    Article  ADS  Google Scholar 

  41. The Linear Collider Collaboration http://www.linearcollider.org/.

  42. Boland, M. et al. Updated Baseline for A Staged Compact Linear Collider CERN–2016–004 (CERN, 2017).

  43. Goldstein, J. Development of detector technologies for ILC vertexing. Proc. Sci. https://doi.org/10.22323/1.287.0050 (2017).

    Google Scholar 

  44. Abelev, B. et al. Technical design report for the upgrade of the ALICE inner tracking system. J. Phys. G Nucl. Part. Phys. 41, 087002 (2014).

    Google Scholar 

  45. Lutz, G. et al. DEPFET-detectors: new developments. Nucl. Instrum. Methods A 572, 311–315 (2007).

    Article  ADS  Google Scholar 

  46. Luetticke, F. et al. The ultralight DEPFET pixel detector of the Belle II experiment. Nucl. Instrum. Methods A 845, 118–121 (2017).

    Article  ADS  Google Scholar 

  47. Turchetta, R. et al. A monolithic active pixel sensor for charged particle tracking and imaging using standard VLSI CMOS technology. Nucl. Instrum. Methods A 458, 677–689 (2001).

    Article  ADS  Google Scholar 

  48. Valin, I. et al. A reticle size CMOS pixel sensor dedicated to the STAR HFT. J. Instrum. 7, C01102 (2012).

    Article  Google Scholar 

  49. Baudot, J. et al. Development of single- and double-sided ladders for the ILD vertex detectors. Preprint at https://arxiv.org/abs/1203.3689 (2012).

  50. Brau, J. et al. Monolithic CMOS pixel detector for international linear collider vertex detection. Pramana 69, 1009–1013 (2007).

    Article  ADS  Google Scholar 

  51. Hanranek, M. et al. Readout chip for column parallel CCD, CPR2A. Nucl. Instrum. Methods A 607, 640–647 (2009).

    Article  ADS  Google Scholar 

  52. Calancha Paredes, C. et al. Progress in the development of the vertex detector with fine pixel CCD at the ILC. Proc. Sci https://doi.org/10.22323/1.198.0022 (2014).

    Google Scholar 

  53. Valerio, P. et al. A prototype hybrid pixel detector ASIC for the CLIC experiment. J. Instrum. 9, C01012 (2014).

    Article  Google Scholar 

  54. Cortina Gil, E. & Soung-Yee, L. SOIPIX Programme and applications. J. Instrum. 10, C08018 (2015).

    Article  Google Scholar 

  55. The circular electron positron collider http://cepc.ihep.ac.cn/.

  56. Casse, G. Recent developments on silicon detectors. Nucl. Instrum. Methods A 732, 16–20 (2013).

    Article  ADS  Google Scholar 

  57. Adloff, C. et al. Calorimetry for lepton collider experiments — CALICE results and activities. Preprint at https://arxiv.org/abs/1212.5127 (2012).

  58. The CALICE Collaboration, Welcome to CALICE https://twiki.cern.ch/twiki/bin/view/CALICE/WebHome.

  59. Magnan, A.-M. HGCAL: a high-granularity calorimeter for the endcaps of CMS at HL-LHC. J. Instrum. 12, C01042 (2017).

    Article  Google Scholar 

  60. Kluge, A. et al. The TDCpix readout ASIC: a 75 ps resolution timing front-end for the NA62 Gigatracker hybrid pixel detector. Nucl. Instrum. Methods A 732, 511–514 (2013).

    Article  ADS  Google Scholar 

  61. Takakhashi, J. et al. Silicon drift detectors for the STAR/SVT experiment at RHIC. Nucl. Instrum. Methods A 439, 497–506 (2000).

    Article  ADS  Google Scholar 

  62. Nouais, D. et al. The ALICE silicon drift detector system. Nucl. Instrum. Methods A 501, 119–125 (2003).

    Article  ADS  Google Scholar 

  63. Mager, M. ALPIDE, the monolithic active pixel sensor for the ALICE ITS upgrade. Nucl. Instrum. Methods A 824, 434–438 (2016).

    Article  ADS  Google Scholar 

  64. The Electron Ion Collider, A machine that will unlock the secrets of the strongest force in Nature https://www.bnl.gov/eic/.

  65. Abelleira Fernandez, J. et al. A large hadron electron collider at CERN: report on the physics and design concepts for machine and detector. J. Phys. G. Nucl. Part. Phys. 39, 075001 (2012).

  66. The AMS Collaboration, The alpha magnetic spectrometer https://home.cern/about/experiments/ams.

  67. The Fermi Gamma-ray space telescope, NASA https://fermi.gsfc.nasa.gov/.

  68. Sadrozinski, H. et al. Operation of the preclinical head scanner for proton CT. Nucl. Instrum. Methods A 831, 394–399 (2016).

    Article  ADS  Google Scholar 

  69. Taylor, J. et al. Proton tracking for medical imaging and dosimetry. J. Instrum. 10, C02015 (2015).

    Article  Google Scholar 

  70. Esposito, M. et al. PRaVDA: the first solid-state system for proton computed tomography. Eur. J. Med. Phys. 55, 149–154 (2018).

    Google Scholar 

  71. Campbell, M. The medipix collaboration https://medipix.web.cern.ch/.

  72. Schmitt, B. The SLS detectors group, The Paul Scherrer Institut https://www.psi.ch/detectors/detectors-group.

  73. Matsumura, H. et al. Improving charge-collection efficiency of SOI pixel sensors for X-ray astronomy. Nucl. Instrum. Methods A 794, 255–259 (2015).

    Article  ADS  Google Scholar 

  74. Butler, M. Sensor market set to soar. Photonics Media https://www.photonics.com/a62311/Sensor_Market_Set_to_Soar (2017).

  75. Guerrini, N. et al. A high frame rate, 16 million pixels, radiation hard CMOS sensor. J. Instrum. 6, C03003 (2011).

    Article  Google Scholar 

  76. Anelli, A. et al. Radiation tolerant VLSI circuits in standard deep submicron CMOS technologies for the LHC experiments: practical design aspects. IEEE Trans. Nucl. Sci. 46, 1690–1696 (1999).

    Article  ADS  Google Scholar 

  77. Faruqi, G. M. A. Direct imaging for electron microscopy. Nucl. Instrum. Methods A 878, 180–190 (2018).

    Article  ADS  Google Scholar 

  78. Rogmagnoli, G. et al. Silicon micro-fluidic cooling for NA62 GTK pixel detectors. Microelectron. Eng. 145, 133–137 (2015).

    Article  Google Scholar 

  79. Sedgwick, I. et al. LASSENA: A 6.7 megapixel, 3-sides buttable wafer-scale CMOS sensor using a novel grid-addressing architecture. International Image Sensor Society http://www.imagesensors.org/Past%20Workshops/2013%20Workshop/2013%20Papers/08-2_030_Sedgwick_paper.pdf (2013).

  80. Barber, G. et al. Operation of a silicon vertex detector in the NA14 photoproduction experiment. Nucl. Instrm Methods A 253, 530–536 (1987).

    Article  ADS  Google Scholar 

  81. Contin, G. MAPS-based vertex detectors: operational experience in STAR and future applications. Proc. Sci. https://doi.org/10.22323/1.309.0019 (2018).

    Google Scholar 

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Acknowledgements

The author thanks his many colleagues in the international experimental particle physics community and especially those whose excellent presentations, articles, reviews and books are cited here. This Review could not have been completed without the encouragement of the Birmingham Particle Physics Group (whose recent research has relied to a significant degree on the UK’s Science and Technology Facilities Council 2015–2019 consolidated grant: ST/N000463/1) or without the wider support of the School of Physics and Astronomy at the University of Birmingham, UK. The author is also indebted to colleagues in the medical physics community and to the European Union’s Horizon 2020 Research and Innovation programme (under Grant Agreement no. 654168).

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Supplementary information

Glossary

Bunch crossing

In a collider, particles are accelerated in a large number of bunches and they counter rotate in the accelerator and keep passing through each other to produce interactions.

Trigger

Only data from bunch crossings containing a collision of interest are kept. Very fast processing of a subset of the data provides the ‘trigger‘ to readout that data from temporary on-detector data storage.

Vertex

In a collider, the produced particle tracks spread out from the point where the collision occurred, the ‘primary vertex’. If one or more of these particles subsequently decay to produce more tracks, there are also ‘secondary vertices’ from which the additional tracks originate.

Beam pipe

Particle collisions take place in the vacuum pipe ‘beam pipe’ in which the particle bunches circulate and collide.

Vertexing

Extrapolating tracks back to where they meet (that is, to the vertex they originate from).

Granularity

The segmentation of the signal-collecting nodes defines the detector granularity and hence ability to cope with many simultaneous hits per unit area.

Calorimeter

A detector that measures charged or neutral particle energy through measuring the particle showers they produce when they interact in a dense absorber.

Bunch train

In some accelerators, bunches come grouped together in time (bunch trains) with relatively long periods of inactivity in between them.

Radiation length

The thickness of the material (X0) required to reduce the mean energy of a traversing electron by 1/e \(\left( \sim 1/2.718\right)\).

Sensing matrix

The nodes within the sensor measuring the signal arranged in a matrix of pixels.

Zero suppression

Even after selection using the trigger, the number of electronics channels to readout is often too large, but many channels are empty. Zero suppression means only reading out channels with signals above a pre-set threshold.

Space points

With strip detectors, there is no information where the particle causing a ‘hit’ occurred along the strip direction. Adding orthogonal strips still only gives two projections, which leaves ambiguities if many particles pass through the detector. Pixels measure directly the hit coordinates (space point with third coordinate constrained by the detector plane thickness).

Molière radius

Lateral spread of the showers produced by electrons or photons (‘electromagnetic showers’) at depth through the material d = X0.

Hadronic interaction length

Distance (d  =  λINT) over which the probability of a particle not having interacted falls by 1/e for hadrons (particles that mostly interact via the strong nuclear force).

Pixelated fast-timing

Pixel detectors give true ‘space points’ (3D information), but if the timing of the hit is also recorded accurately (few tens of picoseconds) one can speak of 4D fast-timing pixels.

Flip-chip

To marry a pixel sensor with a readout chip requires a high-density interconnect (typically conducting ‘bumps’) patterned onto one surface and then the two connected face-to-face.

Point spread function

In astronomy, the response of an optical system to a source that itself approximates an infinitely narrow point source.

Relative stopping power

Different materials slow down protons to a different degree, giving differences in where protons stop for a given incident energy.

Multiplication layer

Detectors can be designed to create a high-field region just below the charge collecting node in which the collected charge is accelerated to sufficient energy to induce further electron–hole pair production ‘charge multiplication’.

Voxel

A pixel is a 2D area on a detector in which the third coordinate is usually only determined by the thickness of the silicon plane, which is typically much larger than the pixel dimensions. By making the sensing thickness the same dimensions as the pixel gives a volume ‘voxel’ within which the hit occurred.

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Allport, P. Applications of silicon strip and pixel-based particle tracking detectors. Nat Rev Phys 1, 567–576 (2019). https://doi.org/10.1038/s42254-019-0081-z

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