Modeling Radiation Damage to Pixel Sensors in the ATLAS Detector M. - - PowerPoint PPT Presentation

modeling radiation damage to pixel sensors in the atlas
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Modeling Radiation Damage to Pixel Sensors in the ATLAS Detector M. - - PowerPoint PPT Presentation

PIXEL2018 - Academia Sinica, Taipei Modeling Radiation Damage to Pixel Sensors in the ATLAS Detector M. Bomben, LPNHE & UPD Paris on behalf of the ATLAS collaboration M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei,


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SLIDE 1

PIXEL2018 - Academia Sinica, Taipei

Modeling Radiation Damage to Pixel Sensors in the ATLAS Detector

  • M. Bomben, LPNHE & UPD – Paris
  • n behalf of the ATLAS collaboration
  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

1

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SLIDE 2

Outline

  • Introduction
  • ATLAS Radiation Damage Digitizer Goals
  • Digitizer: implementation strategy and ingredients
  • Validation
  • Predictions
  • Conclusion & Outlook
  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

2

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SLIDE 3

The CERN Large Hadron Collider (LHC)

CERN LHC is the largest and most powerful particle accelerator ever built It provides proton-proton collisions at energies up to √s = 13 TeV LHC design luminosity was 1x1034 cm-2s-1 Design value has been widely exceeded!

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

3

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SLIDE 4

The CERN Large Hadron Collider (LHC)

CERN LHC is the largest and most powerful particle accelerator ever built It provides proton-proton collisions at energies up to √s = 13 TeV LHC design luminosity was 1x1034 cm-2s-1 Design value has been widely exceeded! Large dataset integrated over first 2 LHC Runs: > 180 fb-1

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

4

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SLIDE 5

The CERN Large Hadron Collider (LHC)

CERN LHC is the largest and most powerful particle accelerator ever built It provides proton-proton collisions at energies up to √s = 13 TeV LHC design luminosity was 1x1034 cm-2s-1 Design value has been widely exceeded! Large fluence integrated over first 2 LHC Runs: > 9x1014 neq/cm2 by the innermost pixel layer

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

5 200 400 600 800 1000 1200 Days Since Start of Run 2 2 4 6 8 10 ]

2

/ cm

eq

n

14

Total Fluence at z = 0 [10 50 100 150 ]

  • 1

Run 2 Delivered Luminosity [fb

Preliminary ATLAS

Updated Oct. 25, 2018

IBL B-layer Layer 1 Layer 2

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SLIDE 6

ATLAS Inner Detector

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

6

1 . 4 m 4 Pixel barrel layers 3 Outermost: 250 µm thick 50x400 µm2 pitch Innermost layer: IBL Inserted in Run2 200 µm thick 50x250 µm2 pitch

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SLIDE 7

ATLAS Pixel Detector

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

7

1 . 4 m 4 Pixel barrel layers 3 Outermost: 250 µm thick 50x400 µm2 pitch Innermost layer: IBL Inserted in Run2 200 µm thick 50x250 µm2 pitch P l a n a r p i x e l n

  • n
  • n

s e n s

  • r

s e v e r y w h e r e b u t a t h i g h η * i n I B L w h e r e n

  • v

e l 3 D n

  • n
  • p

a r e u s e d

*outside tracking volume

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SLIDE 8
  • Significant decrease of dE/dx and

cluster size for IBL

  • Similar effect for B-Layer
  • It was necessary to increase the

bias voltage and adjust threshold to mitigate the negative trend

  • Occupancy decreasing too

2 4 6 8 10 ]

2

/cm

eq

n

14

10 × [1 Φ 2 4 6 8 10 ]

2

/cm

eq

n

14

10 × [1 Φ

20 40 60 80 100 120 140 160 180

]

  • 1

Run-2 Delivered Luminosity [fb

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

] or <cluster size> [pixels]

2

cm

  • 1

<dE/dx> [MeV g

150 V → HV 80

Preliminary ATLAS Pixel Data2016 IBL Data 2017 Data 2018

<dE/dx> φ Cluster size Cluster size z HV=80(150) V

  • Thr=2.5ke
  • ToT=8BCs@16ke

HV=350 V

  • Thr=2.5ke
  • ToT=8BCs@16ke

HV=400 V

  • Thr=2ke
  • ToT=10BCs@16ke
  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

Pixel sensors: radiation damage effects

8

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SLIDE 9

Pixel Radiation Damage Digitizer* Goals

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

9

Include all this in ATLAS MonteCarlo

Charge carriers will drift toward the collecting electrode due to electric field, which is deformed by radiation damage. Their path will be deflected by magnetic field (Lorentz angle) and diffusion. Due to radiation damage they can be trapped and induce/screen a fraction of their charge (Ramo potential). Total induced charge is then digitized and clustered. *Digitization happens after simulated charge deposition and before space point reconstruction

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SLIDE 10

Pixel Radiation Damage Digitizer Goals

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

10

Include all this in ATLAS MonteCarlo Now ready!

Charge carriers will drift toward the collecting electrode due to electric field, which is deformed by radiation damage. Their path will be deflected by magnetic field (Lorentz angle) and diffusion. Due to radiation damage they can be trapped and induce/screen a fraction of their charge (Ramo potential). Total induced charge is then digitized and clustered.

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SLIDE 11

Implementation Strategy

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

11

fluence trapping constant time travelled initial charge location E-field final depth Ramo potential induced charge Lorentz angle thermal diffusion final charge location

per e/h per geometry per condition

Start End

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SLIDE 12

Ingredients: fluence and trapping time

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

12

30 − 20 − 10 − 10 20 30 Distance along stave [cm] 1 2 3 4 5 6 7 ]

  • 1

/fb

2

/cm

eq

Si 1 MeV n

12

Absolute fluence [10

Preliminary ATLAS

= 13 TeV s

20 40 60 80 100 120 (z=0) [%] Φ (z) / Φ Relative data fluence

Insertable B-layer (IBL) Predicted by Pythia (A2) + FLUKA Predicted by Pythia (A3) + FLUKA Predicted by Pythia (A3) + Geant4

  • nly)

π Predicted by Pythia (A3) + Geant4 (n + p + Extracted from Hamburg Model + Leakage Currents

Fluence prediction taken from FLUKA & Pythia FLUKA prediction validated with leakage current and Hamburg model* simulation Ø 15% difference in the central region Trapping constants from literature**: Ø βe = (4.5±1.5)x10-16 cm2/ns Ø βh = (6.5±1.5)x10-16 cm2/ns * M. Moll, DESY-THESIS-1999-040

** ATLAS pixel coll., JINST 3 (2008) P07007

  • G. Kramberger et al., Nucl. Instrum. Meth. A481 (2002) 297
  • O. Krasel et al., IEEE Trans. on Nucl. Sci. 51 (2004) 3055.
  • G. Alimonti et al., ATL-INDET-2003-014 (2003)
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SLIDE 13

Ingredients: electric field (planar sensors)

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

13

Radiation damage induced defects deform the electric field distribution in the bulk We use TCAD simulation tools to make predictions of electric field in the bulk A 2 trap model due to CMS collaborators* has been used with Silvaco tools**

*V. Chiochia et al., Nucl. Instr. and Meth A 568 (2006) 51-55 ** https://www.silvaco.com/products/tcad.html

50 100 150 200 m] µ Bulk Depth [ 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

  • E. Field [V/cm]

= 0 Φ

2

/cm

eq

n

14

10 × = 1 Φ

2

/cm

eq

n

14

10 × = 2 Φ

2

/cm

eq

n

14

10 × = 5 Φ

Vbias = 150 V

Model chosen because:

  • developed on n-on-n pixels
  • irradiated at CERN w/ 24 GeV/c p
  • built on testbeam data
  • predicts type inversion at right fluence

Main feature: double peak electric field

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SLIDE 14

Ingredients: electric field mod. uncertainties

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

14

Fluence

(1014 neq/cm2)

EA

T (eV)

±0.4% ED

T (eV)

± 0.4% NA

(1014 cm−3)

± 10% ND

(1014 cm−3)

± 10% σA,D

e

& σD

h (10−15 cm2)

± 10% σA

h (10−15 cm2)

± 10% 1 EC-0.52eV EV +0.48eV 3.6 5 6.60 1.65 2 6.8 10 5 14 34

TCAD radiation damage model parameters come with no uncertainties So we had to explore the sensitivity of electric field on each defect parameter:

  • concentration
  • energy
  • electron and hole capture

cross sections Trends are compatible with expectations

m] µ Bulk Depth [ 20 40 60 80 100 120 140 160 180 [V/cm]

z

E 2000 4000 6000 8000 10000 12000 14000

Nominal + 10%

int A

g

  • 10%
int A

g

2

/cm

eq

n

14

10 × = 1 Φ = 80 V

bias

V m] µ Bulk Depth [ 20 40 60 80 100 120 140 160 180 [V/cm]

z

E 2000 4000 6000 8000 10000 12000 14000

Nominal energy + 0.4% energy - 0.4%

2

/cm

eq

n

14

10 × = 1 Φ = 80 V

bias

V m] µ Bulk Depth [ 20 40 60 80 100 120 140 160 180 [V/cm]

z

E 2000 4000 6000 8000 10000 12000 14000

Nominal + 10%

e

σ

  • 10%
e

σ

2

/cm

eq

n

14

10 × = 1 Φ = 80 V

bias

V m] µ Bulk Depth [ 20 40 60 80 100 120 140 160 180 [V/cm]

z

E 2000 4000 6000 8000 10000 12000 14000

Nominal + 10%

h

σ

  • 10%
h

σ

2

/cm

eq

n

14

10 × = 1 Φ = 80 V

bias

V

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SLIDE 15

Ingredients: annealing

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

15

02/07/2015 01/01/2016 01/07/2016 31/12/2016

Date 20 40 60 80 100 120 140 [V]

depl

V

Preliminary ATLAS IBL

Hamburg Model Simulation Simulation Uncertainty Data with Bias Voltage Scan

Annealing not modeled in TCAD Effective correction to TCAD: rescale defects concentration in TCAD to match the average (constant) space charge concentration predicted by Hamburg Model Hamburg model predictions based on bias voltage scans

20 40 60 80 100 120 140 160 180 m] µ Bulk Depth [ 8000 − 6000 − 4000 − 2000 − 2000 4000

9

10 × ]

3

Space Charge [e/cm

2

/cm

eq

n

14

10 × = 2 Φ = 80 V

bias

V

Chiochia Hamburg TCAD with eff. annealing

IBL stayed cold most of the time è small correction More important effect for B-Layer

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SLIDE 16

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Ramo Potential 0.05 0.1 0.15 0.2 0.25 0.3 0.35 m µ X / 200 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 m µ Depth / 200

  • in-n Planar Sensor

+

m n µ 200

e-

Ingredients: signal from trapped carriers

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

16

Charge drift towards collecting electrode They induce larger and larger current the closer they get to the electrode If trapped only a fraction of the total charge will be induced Trapping position is stochastically determined, based on fluence and voltage conditions The final signal is calculated in a 3x3 pixels matrix thanks to the Ramo potential

2D slice of 3D Ramo potential calculated using TCAD simulations B

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SLIDE 17

Ingredients: Lorentz angle deflection

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

17

m] µ Starting Depth in z [ 50 100 150 Tangent Lorentz Angle 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Electrons Holes Unirradiated

2

/cm

eq

n

14

10 × 1

2

/cm

eq

n

14

10 × 2

2

/cm

eq

n

14

10 × 5

Pixel Preliminary ATLAS

  • in-n Planar Sensor, 80 V, Chiochia Rad. Model

+

m n µ 200

(a)

Electric field profile no longer shows linear dependence on bulk depth

50 100 150 200 m] µ Bulk Depth [ 2000 4000 6000 8000 10000 12000 14000

  • E. Field [V/cm]

= 0 Φ

2

/cm

eq

n

14

10 × = 1 Φ

2

/cm

eq

n

14

10 × = 2 Φ

2

/cm

eq

n

14

10 × = 5 Φ

It is now even more important to model the Lorentz angle depth-dependence

slide-18
SLIDE 18

Validation: Charge Collection Efficiency (CCE)

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

18

]

  • 1

Integrated Luminosity [fb 10

2

10 Fraction of Charge 0.6 0.7 0.8 0.9 1

Data 400 V Data 350 V Data 150 V Data 80 V Standalone Simulation 400 V Standalone Simulation 350 V Standalone Simulation 150 V Standalone Simulation 80 V

ATLAS Preliminary

IBL planar modules

]

2

/cm

eq

n

14

Fluence [10 1 10

CCE for IBL across its lifetime Simulation uncertainties: Horizontal error bars include uncertainties on luminosity to fluence conversion (15%) Vertical error bars include uncertainties from the TCAD radiation damage model Data uncertainties Horizontal error bars include luminosity unc. (2%) Vertical error bars include calibration drift effects Good agreement with data but large uncertainties In the future collision data can be used to further constrain the radiation damage model

End 2016 End 2017 End 2018

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SLIDE 19

Validation: Lorentz angle

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

19

]

  • 1

Integrated Luminosity [fb 10

2

10 [mrad]

L

θ Δ 10 20 30 40 50 60 70 80 ]

2

/cm

eq

n

14

10 × fluence [

1 −

10 1

syst ⊕ stat σ Allpix Simulation 80 V - Allpix Simulation 80 V Petasecca Model Data 80 V

ATLAS Preliminary IBL planar modules

The trend of increase of Lorentz angle with luminosity is robust Models predicting no double peak in electric field fail at reproducing increase of L.A. with luminosity

0.1 − 0.1 0.2 0.3 0.4 0.5 Incidence Angle [rad] 1 1.2 1.4 1.6 1.8 2 Mean Transverse Cluster Size Standalone Simulation Insertable B-layer Data

Pixel Preliminary ATLAS

Bias Voltage 150 V | < 0.6 η |

2

/cm

eq

1 MeV n

14

10 × 2 ≈ Φ

Lorentz angle is extracted from a fit to the cluster size vs track incident angle

Petasecca et. al, IEEE TNS 53 (2006) 2971

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SLIDE 20

Validation and predictions: HV scans

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

20

Bias Voltage [V] 200 400 600 800 1000 ToT [BC] 1 2 3 4 5 6 7 8 9 10

data - end 2017 (end 2017)

2

/cm

eq

n

14

=6 10 φ Standalone Simulation: (end 2018)

2

/cm

eq

n

14

=8.7 10 φ Standalone Simulation:

ATLAS Preliminary IBL planar modules

Both data and simulation charge eements in both shape

  • rking

point to avoid under depletion

End 2017 End 2018

Standalone simulation to predict MPV of the fitted Landau distribution

  • f the ToT as a function
  • f bias voltage for fixed

fluence Good agreements in both shape and plateau position This confirms that both the electric field and the trapping time are correctly reproduced in

  • ur modeling!

Predictions now used to determine desired bias voltage during LHC Run3 for all pixel layers

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SLIDE 21

Predictions: energy loss

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

21

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 20 40 60 80 100 120 140 160 180

Damage No Radiation Run 2 Beginning

  • 1

~15 fb

  • f 2016

Near End

  • f 2016

Near End 2017 End of 2018 End of

0.6 0.8 1 1.2 1.4 1.6 / g]

2

Cluster dE/dx [MeV cm IBL B-layer Layer 1 Layer 2

Simulation Preliminary ATLAS

> 1 GeV

track T

p 2 4 6 8 10

]

2

/cm

eq

n

14

[1 MeV 10 Fluence

100 200 300 400 500

Bias Voltage [V]

Digitizer can be used to make predictions on fundamental observables Energy loss per layer for tracks with pT > 1 GeV Several scenarios considered, in terms of

  • fluence
  • bias voltage
  • different layer by layer

N.B. other parameters (thr., tuning) fixed

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SLIDE 22

Conclusions and outlook

  • Effects of radiation damage to silicon sensor bulk are already visible

in the ATLAS pixel detector

  • Increasing bias voltage helps mitigating the main effect (signal loss)
  • Fundamental to reproduce these effects in simulations
  • The new ATLAS digitizer includes radiation damage effects
  • First comparison with collision data are promising
  • The new digitizer is an essential tool to determine ATLAS Pixel

detector data taking future conditions

  • Work is ongoing to include 3D modeling and extend predictions to

High Luminosity LHC fluence for the new ATLAS Inner Tracker

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

22

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SLIDE 23
  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

23

THANK YOU FOR YOUR ATTENTION

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SLIDE 24

Backup

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

24

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SLIDE 25

ATLAS Detector

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

25

z θ η ϕ R

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SLIDE 26

Run2 Pixel data taking conditions

  • M. Bomben - Pixel 2018, 10-14 December, Academia Sinica, Taipei, Taiwan

26