Lesson 17 - Oregon State Universityoregonstate.edu/instruct/ch374/ch418518/Detectors.pdf · Lesson...

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Lesson 17 Detectors

Transcript of Lesson 17 - Oregon State Universityoregonstate.edu/instruct/ch374/ch418518/Detectors.pdf · Lesson...

Page 1: Lesson 17 - Oregon State Universityoregonstate.edu/instruct/ch374/ch418518/Detectors.pdf · Lesson 17 Detectors. Introduction •When radiation interacts with matter, result is the

Lesson 17

Detectors

Page 2: Lesson 17 - Oregon State Universityoregonstate.edu/instruct/ch374/ch418518/Detectors.pdf · Lesson 17 Detectors. Introduction •When radiation interacts with matter, result is the

Introduction• When radiation interacts with matter,

result is the production of energeticelectrons. (Neutrons lead to secondaryprocesses that involve charged species)

• Want to collect these electrons todetermine the occurrence of radiationstriking the detector, the energy of theradiation, and the time of arrival of theradiation.

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Detector characteristics

• Sensitivity of the detector• Energy Resolution of the detector• Time resolution of the detector oritgs pulse resolving time

• Detector efficiency

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Summary of detector types

• Gas Ionization• Ionization in a Solid(Semiconductor detectors)

• Solid Scintillators• Liquid Scintillators• Nuclear Emulsions

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Detectors based on gas ionization

• Ion chambers

35 eV/ion pair→>105 ion pairs created.

Collect this charge using a capacitor, V=Q/C

NO AMPLIFICATION OF THE PRIMARY IONIZATION

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Uses of Ion Chambers

• High radiation fields (reactors)measuring output currents.

• Need for exact measurement ofionization (health physics)

• Tracking devices

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Gas amplification• If the electric fields are strong enough, the

ions can be accelerated and when they strikethe gas molecules, they can cause furtherionization.

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The Result

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Proportional counters• Gas amplification creates output pulse whose

magnitude is linearly proportional to energydeposit in the gas.

• Gas amplification factors are 103-104.• Will distinguish between alpha and beta

radiation

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Practical aspectsgas flow

typical gas: P10, 90% Ar, 10% methane

Sensitive to α,β, X-rays, charged particlesFast response, dead time ~ µs

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Geiger- Müller Counters

• When the gas amplification factor reaches 108, the sizeof the output pulse is a constant, independent of theinitial energy deposit.

• In this region, the Geiger- Müller region, the detectorbehaves like a spark plug with a single large discharge.

• Large dead times, 100-300µs, result• No information about the energy of the radiation is

obtained or its time characteristics.• Need for quencher in counter gas, finite lifetime of

detectors which are sealed tubes.• Simple cheap electronics

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Semiconductor RadiationDetectors

• “Solid state ionization chambers”• Most common semiconductor usedis Si. One also uses Ge fordetection of photons.

• Need very pure materials--usetricks to achieve this

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Semiconductor physics

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p-n junction

Create a region around the p-n junctionwhere there is no excess of either n or p carriers. This region is called the “depletionregion”.

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Advantages of Si detectors

• Compact, ranges of chargedparticles are µ

• Energy needed to create +- pair is3.6 eV instead of 35eV. Superiorresolution.

• Pulse timing ~ 100ns.

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Ge detectors• Ge is used in place of Si for detecting gamma

rays.• Energy to create +- pair = 2.9 eV instead of

3.6 eV• Z=32 vs Z=14• Downside, forbidden gap is 0.66eV, thermal

excitation is possible, solve by cooling detectorto LN2 temperatures.

• Historical oddity: Ge(Li) vs Ge

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Types of Si detectors

• Surface barrier, PIN diodes, Si(Li)• Surface barrier construction

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Details of SB detectors

• Superior resolution• Can be made “ruggedized” or forlow backgrounds

• Used in particle telescopes, dE/dx,E stacks

• Delicate and expensive

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PIN diodes

• Cheap• p-I-n sandwich• strip detectors

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Si(Li) detectors• Ultra-pure region created by chemical compensation,

i.e., drifting a Li layer into p type material.• Advantage= large depleted region (mm)• Used for β-detection.• Advantages, compact, large stopping power (solid),

superior resolution (1-2 keV)• Expensive• Cooled to reduce noise

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Ge detectors• Detectors of choice for detecting γ-rays• Superior resolution

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Scintillation detectors

• Energy deposit→light→signal• Mechanism (organic scintillators)

Note that absorption and re-emission have different spectra

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Organic scintillators• Types: solid, liquid (organic scintillator in

organic liquid), solid solution(organic scintillatorin plastic)

• fast response (~ ns)• sensitive (used for) heavy charged particles

and electrons.• made into various shapes and sizes

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Liquid Scintillators

• Dissolve radioactive material in thescintillator

• Have primary fluor (PPO) and wavelength shifter (POPOP)>

• Used to count low energy β• Quenching

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Inorganic scintillators(NaI (Tl))

Emission of light by activator center

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NaI(Tl)

• Workhorse gamma ray detector• Usual size 3” x 3”• 230 ns decay time for light output• Other common inorganicscintillators are BaF2, BGO

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NaI detector operation

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Nuclear electronics

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Nuclear statistics

Table 18-2 Typical Sequence of

Counts of a long-Lived Sample

(170Tm)*

Measurement

Number

cp0.1m xi-xm (xi-xm)2

1 1880 -18 324

2 1887 -11 121

3 1915 17 289

4 1851 -47 2209

5 1874 -24 576

6 1853 -45 2025

7 1931 33 10899

8 1886 -32 1024

9 1980 82 6724

10 1893 -5 25

11 1976 78 6084

12 1876 -22 484

13 1901 3 9

14 1979 81 6561

15 1836 -62 3844

16 1832 -66 4536

17 1930 32 1024

18 1917 19 361

19 1899 1 1

20 1890 -8 64

*We are indebted to Prof. R.A. Schmitt for providing these data.

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Distribution functionsMost general distribution describing radioactive decayis called the Binomial Distribution

P(x)=(n!/((n-x)!x!)px(1-p)

n-x

n=# trials, p is probability of success

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Poisson distribution• If p small ( p <<1), approximate

binomial distribution by Poissondistribution

P(x) = (xm)x exp(-xm)/x! where xm = pn

• Note that the Poisson distribution isasymmetric

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Example of use of statistics

• Consider data of Table 18.2• mean = 1898• standard deviation, σ, = 44.2 where

!

" 2 =

xi# x

m( )2

i=1

N

$

N #1

For Poisson distribution

= (x m)1/2

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Gaussian (normal) distribution

!

P(x) =1

2"xm

exp #x# x

m( )2

2xm

$

% & &

'

( ) )

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Interval distribution

!

I( t) =1

tm

exp(" t / tm)dt

Counts occur in “bunches”!!

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Table 18-3. Uncertainties for some common operations

Operation Answer UncertaintyAddition A+B (σA2+σB2)1/2Subtraction A-B (σA2+σB2)1/2

Multiplication A*B A*B((σA/A)2+(σB/B)2)1/2Division A/B A/B((σA/A)2+(σB/B)2)1/2

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Simple statistics

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Uncertainties for some common operationsOperation Answer Uncertainty

Addition A+B (σA2+σB

2)1/2Subtraction A-B (σA

2+σB2)1/2

Multiplication A*B A*B((σA/A)2+(σB/B)2)1/2 Division A/B A/B((σA/A)2+(σB/B)2)1/2