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Introduction to Silicon Detectors G.Villani STFC Rutherford Appleton Laboratory Particle Physics Department 1.

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Presentation on theme: "Introduction to Silicon Detectors G.Villani STFC Rutherford Appleton Laboratory Particle Physics Department 1."— Presentation transcript:

1 Introduction to Silicon Detectors G.Villani STFC Rutherford Appleton Laboratory Particle Physics Department 1

2 Outlook Introduction to physics of Si and detection Examples of detectors Conclusions 2

3 Introduction The detection chain 3 Sensing/ Charge creation Charge transport and collection Conversion Signal processing Data TX E Si physical propertiesSi device propertiesSi device topologies properties Detector physics: Silicon physical and electrical properties Detection principles Transport mechanisms Conversion Detector examples: Microstrips CCD MAPS Detector system issues: Detection efficiency Power all the boxes of the detection chain process based upon Silicon

4 The crystalline structure is diamond cubic (FCC), with lattice spacing of 5.43 A Polysilicon consists of small Si crystals randomly oriented; in α-Si there is no long range order. The key to success of Si is related to its oxide SiO 2, an excellent insulator (BV ~ 10 7 V/cm). Micro crystals but the flexible bond angles make SiO 2 effectively an amorphous: its conductivity varies considerably (charge transport in SiO 2 via polaron hopping between non-bonding oxygen 2p orbitals) Introduction to Silicon After Oxygen, Silicon is the 2 nd most abundant element in Earth’s crust (>25% in mass) Si 1.48A 4

5 Silicon Band structure The electronic band structure calculation can be done ab-initio using variational approach (DFT) or empirical methods (kp) that solve 1 electron SE in a periodic potential neglecting electrons interaction. The approximate solution of many-body SE in presence of periodic potential of the crystal lattice are in the form of Bloch functions: Introduction to Silicon It can be regarded as a traveling wave associated with free motion of electrons modulated by the periodic solution u n,k. The energy E is periodic in k so is specified just within the 1 st unit WS cell of the reciprocal lattice (the Brillouin zone). The band diagram look complicated: 5

6 Introduction to Silicon 6 The appearance of Band Gap, separating CB and VB The 6 CB minima are not located at the center of 1 st Brillouin zone, INDIRECT GAP CBVB-HVB-L 1 st Brillouin zone of Diamond lattice CB VB Anisotropy in surface of E

7 Introduction to Silicon The detailed band structure is too complicated: quasi-equilibrium simplifications are needed to study the of mechanism charge transport. Assuming that the carriers reside near an extremum, the dispersion relationship E(k) is almost parabolic: Under the assumptions of small variation of the electric field, the carrier dynamics resembles that one of a free particle, with appropriate simplifications. The mobility of a particle is inversely related to its effective mass (or proportional to the curvature of E(k)). Similar approach used to calculate the E(k) for phonons. the effective mass approximation takes into account the periodic potential of the crystal by introducing an effective carrier mass (in 3D an average over different longitudinal and transverse masses): 7

8 Introduction to Silicon Once the band structure and simplified density of states is known, it is possible to determine the carrier density. This is essential to study the charge transport. The density of states g(E); The distribution function F(E); Only partly filled bands can contribute to conduction: carrier density in CB and VB. At equilibrium the carrier density is obtained by integrating the product: The density of states g D (E) depends on the dimension In intrinsic Si a creation of e in CB leaves behind a hole in VB, that can be treated as an e with positive charge and mobility of the band where it resides CB VB Fermi level: energy 50% occupancy 8

9 Introduction to Silicon Conduction of Si T = 300K: σ = q(μ n +μ p ) n i = 3.04x10 -6 mho-cm ->329kOhm-cm By adding atoms of dopants, which require little energy to ionize, we can change by many odg the carrier concentration. Doping concentration: to cm -3 In crystalline Si ~ 5*10 22 atomscm -3 In equilibrium and for non degenerate case the relationship between carrier concentration and E is the same as in the intrinsic case: Thermal energies at ambient temperature (~40meV) is enough to ionize the dopants 9

10 Detection Detection principles: A: Ionization: by imparting energy to break a bond, electrons are lifted from VB to CB then made available to conduction. Well established concept ( ionization chambers, microstrip, hybrid pixels, CCD, MAPS…) Bethe-Bloch formula for stopping power gives the rate of energy loss/unit length for charged particles through matter Photon interaction α MIP 10

11 Detection The indirect BG of Si requires higher energy for charge excitation, because energy and momentum must be conserved (Phonon-assisted pair creation/recombination) In Si an average of 3.6 eV is required for pair creation Ph  Q~10 7 m -1  Q~10 10 m -1  a 11

12 Detection A MIP forms an ionization trail of radius R when traversing Si, creating ~ 80e - /μm MIP charge density Low injection regime: The associated wavelength is much smaller than mean free path: Each charge is independent from each other; Carrier dynamics does not need QM The generated charge is too small to affect the internal electric field Photoelectric charge density An optical power of -60dBm (= 1nW) of 1keV photons generates ~ 6*10 6 e-/μm High injection regime: Plasma effects The internal electric field can be affected by the generated charge 12

13 Detection Intrinsic resolution of Si and Ge based detectors The variance in signal charge σ i associated to the ionization process is related to the phonon excitation High resolution requires smaller band gap (ε i ), direct or small phonon excitation energy Fano factor ~0.1 in Si 13

14 Detection B: Excitation: Charge or lattice (acoustic or optical phonons) some IR detectors, bolometers Dispersion relation for phonons in Si Phonon excitation energy ~ 10 meV : much lower threshold 60meV EcEc EFEF EVEV EFEF ~10’s meV Eigenvalues separation in quantized structures ~ 10’s meV SiSiO 2 Poly Si 14

15 Charge transport Charge transport: Once the charge has been created in the material, the next step is its collection: The charge transport description relies on semi-classical BTE (continuity equation in 6D phase space) The distribution function f(r,k) can be approximated near equilibrium: equilibrium Near equilibrium k0 Q conservation P conservation E conservation 15

16 Charge transport Under (many) simplifying assumptions the 1 st momentum of BTE gives the DD model (The semiconductor equations): DD expresses momentum conservation: it becomes invalid when sharp variation in energy of carriers occur (due to F for example: deep submicron devices) When feature size is 0.’sμm the DD model becomes invalid: higher momentum required Even in low injection regime, a small F renders the drift term >> diffusion term Diffusion term Drift term 16

17 Half summary Under conditions of quasi stationary conditions non degenerate semiconductor not small feature size low injection … Sensing/ Charge creation Charge transport and collection Conversion E Si physical propertiesSi device properties Charge generation: Ionization: Small injection, QM not needed; Stopping power, average ionization energy Charge transport: Big devices, DD adequate; Small injection, electric field as static; The processes in the detection chain can be simplified: Physical characteristics: Quasi equilibrium; Homogeneity; ‘Room’ temperature; Non degenerate Si; 17

18 Signal conversion: The pn junction Homojunction: consider two pieces of same semiconductor materials with different doping levels: In equilibrium, the Fermi level equalizes throughout the structure The thermal diffusion of charge across the junction leaves just the ionized dopants : an electric potential develops In equilibrium J = 0: using DD model A ‘positive’ voltage increases (exponentially) the charge concentration: high direct current. A ‘negative’ voltage decreases it (down to leakage): the current reduces and at the same time widens the depleted region. Unidirectional of current characteristics Near the interface, the carrier concentration exponentially drops: a depletion region (empty of free charge) is formed. 18

19 Signal conversion: The pn junction An electric field F is present in the depletion region of a junction, sustained by the ionized dopants The electric field in the depletion region contributes to the charge drift, when generated, and helps the collection process. PN junction signal converter: A capacitor with a strong F across A device with a large depleted region can be used to efficiently collect radiation generated charge ( Solid state ionization chamber) W To achieve large W high field region: Low doping (high resistivity) Silicon is needed Large voltages Conversion: Q to V // Q to I 19

20 The bipolar transistor device A bipolar transistor can be thought of as a two diode system, connected in anti series; One is forward biased; The other is reverse biased The bipolar transistor can be (and it is) used as a high gain detector Main limitations arising from speed: the minority carriers diffuse through the base ( relatively low speed) 20

21 Detectors examples Strip detectors Scientific applications Charge Coupled Devices (CCD) Imaging, scientific and consumer applications Monolithic Active Pixel Sensors (MAPS) Imaging, consumer applications RAL PPD has (is) actively involved with all these detector technologies 21

22 Detectors examples Array of long silicon diodes on a high resistivity silicon substrate A strong F in the high resistivity Si region helps collect charge efficiently. The transversal diffusion of charge implies a spread of signal over neighbouring strips The high resistivity Si is not usually used in mainstream semiconductor industry: Hybrid solution: detector connected (wirebonded) to the readout electronic (RO) P ++ N + (high res) V bias ~10’sV F Strip detectors768 Strip Sensors RO electronic Power supply 80μm 300μm Wires 22

23 Detectors examples ATLAS SCT 4 barrel layers,2 x 9 forward disks 4088 double sided modules Total Silicon surface 61.1m² Total 6.3 M channels Power consumption ~ 50kW 768 Strip Sensors RO module 23

24 Detectors examples High events rate require fast signal collection: Estimate of charge collection time in strip detector: For a detector thickness of 300um and overdepleted V b = 50V and 10kohm resistivity t coll(e) ≈ 12ns t coll (h)≈ 35ns The fast collection time helps the radiation hardness: Radiation damage to the Si bulk increases the recombination rate. To avoid signal loss the charge has to be collected quickly, before it recombines. 24

25 Detectors examples RO electronic 3T ( 3MOS) MAPS structure 2D array of pixels Monolithic solution: Detector and readout integrated onto the same substrate ≈10’s  m RO electronic MAPS detectors 25

26 Detectors examples MAPS detectors The charge generated in the thin active region moves by diffusion mainly: ‘Long’ collection time Small signal Different implants arrangements for charge collection optimization Circuit topologies for low noise N ++ (low res) P ++ (low res) P + (low-med res) V bias ~V’s Mechanical substrate 100’s μm Active region ‘s μm Electronics 0.’s μm 26

27 Detectors examples Charge collection time (s) in MAPS vs. perpendicular MIP hit TPAC 1 pixel size 50x50um2 Chip size ~1cm 2 Total pixels 28k >8Meg Transistors Example of charge collection in MAPS: 27

28 Detectors examples Example of charge collection in MAPS: simulated MIP vs.1064nm laser 2x2um 5ns pulse 28

29 Detectors examples Once the charge has been generated, it accumulates in the potential well, under the capacitor. The control circuitry shifts the accumulated charge to the end of the row, to the input of a charge amplifier. The sensor is fabricated in a optimized, dedicated process and the RO on a separate chip. Superior imaging quality but less integration and speed. Nobel Prize 2009 for Physics to inventors Boyle and Smith CCD detectors 29

30 Detectors examples In-situ Storage Image Sensor: ISIS CCD in CMOS process 0.18μm Charge collection under a PG then stored under a 20 pixels storage CCD RG RD OD RSEL Column transistor On-chip logic On-chip switches Global Photogate and Transfer gate ROW 1: CCD clocks ROW 2: CCD clocks ROW 3: CCD clocks ROW 1: RSEL Global RG, RD, OD Imaging pixel 5  m 80  m 55 Fe  source Mn(K   Mn(K   30

31 Signal conversion: The unipolar MOS device By applying a voltage to the G with respect to the Substrate an electric field develops across the SiO 2 : a charge channel is formed between Source and Drain. The Ids characteristics depends on the Vgs applied. The CMOS process refers to the minimum feature size achievable i.e. the channel length) Currently 45nm: the modelling of the characteristics of the device of this size is non-trivial: Quantization effects at the boundary; QM tunnelling across the gate; Hot carriers near the D/S junction; … Metal Oxide Semiconductor device are unipolar devices based on voltage modulation of charge. The control gate is physically separated by the active region where the charge moves by a thin (nm) layer of SiO 2. P ++ N ++ SiO 2 NMOS 31

32 LET in SiO 2 for different particles Generation rate in SiO2 vs. electric field The SiO 2 is a very good insulator: a strong electric field can be applied to it and the charge generated in SiO 2 by ionizing radiation efficiently collected Sensor devices: The unipolar MOS device However SiO 2 is a polar material: the recombination processes are stronger than in Si. Furthermore, hole Transport is non Gaussian (low ‘mobility’) and traps form near Si interface. 32

33 Addition of a Floating Gate (FG): the electrical characteristics of the device are controlled by the charge stored in the FG. The electric field in the SiO 2 due to the FG drifts charge towards/away from it. The discharge of the FG alters the device electrical characteristics FG Si O 2 FG Si O 2 Sensor devices: The unipolar MOS device Floating Gate Control Gate Conversion: Q to I Pre-rad Post-rad Reprog I ds (A) Chip #2 100Gy Std dev Radiation sensitivity The MOS structure easily allows excitation based radiation detection 33

34 Detector systems Detection efficiency: MAPS pixel structure can host complex electronics Estimated power consumption MAPS Calice:  10 μW/pixel x = 10 7 W Assuming V cc =2V 5*10 6 A 10μW continuous -> 10μJ energy Energy deposited by a particle: 0.2 – 10fJ Noise occupancy 1% : hit pixel fires/100sec Required energy/deposited energy >> !!! Extremely huge energy inefficiency SF CA RC-CR SF Vth 50μm 34

35 Detector systems = At pixel level, power consumption could be optimized by using a non linear approach: The positive feedback structure is biased near threshold (variable) A small signal triggers the structure Power reduction at detector level 35

36 Detector systems The ATLAS SCT (semiconductor tracker) detector. The thick red cables on show feed the detector with half of its power – adding more will take up even more space Power optimization at system level A serial powering or DC2DC approach can increase efficiency in power distribution compared to a parallel approach Alternative powering schemes: SP DC2DC 36

37 The field of semiconductor detectors encompasses different scientific and technology fields: solid state physics, EM, QM, electrical engineering, nuclear and particle physics… Some of the issues relevant to radiation detectors: Development of new detection techniques based on novel and well established semiconductor material: ( phonon-based detectors, quantum detectors, compounds, low dimensional) Integration with electronics (monolithic solution to achieve more compactness and reduce cost) 3D structures Topologies optimization (power reduction, noise reduction) Radiation hardness Conclusions 37

38 Backup slides Quantization effects due to band bending in Si-SiO2 interface: excitation based detection Si-polySi-sub SiO 2 Q-effects A


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