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Pasquale Emanuele Scopelliti
Silicon pixel detectors for
crystallography
and imaging of biological samples
On behalf of: A. Bulgheroni, M. Caccia,
Università degli Studi dell’Insubria
C. Cappellini, F. Risigo, M. Jastrzab
SUCIMA collaboration
Medipix collaboration: B. Mikulec,
September 24-29 - Perugia
Lukas Tlustos SIMBASilicon Innovative Monitors for
Biomedical Applications
Previous experiences
and knowledge in
the HEP domain
Applications
Crystallography
Bio-sample imaging
• Imaging of tritium labelled biological sample
• Protein microarray analysis and surface R&D
• Quantum imagingwith energy weighting
• Monolithic • squared pixels, 17 m pitch• 512 x 512 pixel matrix• analog output• 30 e- noise• 50 ke- dynamic range• 10 m thickness sensitive volume• readout frequency ~ 20 MHz
Silicon pixel detectors
MIMOSA V – back-thinned
Molecular structure reconstruction
Application in crystallography
• Monochromatic X-ray beam
• Elastic scatter produce a interference pattern
• Molecular single crystal
• Crystalline structure can be resolved from peak position
• Electron density distribution in a crystalline cell can be reconstructed from peak intensities
The challenge is a single crystal elemental analysis
mounted on the diffractometer head
Application in crystallography
?ng~ The choice of the sample is a
stochastic procedure
X-ray Diffraction X-ray Fluorescence
80
1%
10 mm²
100
NO
point-like
Scintillator Si(Li) QE
Energy resolution %
Area
QE
Energy resolution %
Area
• 10 minutes
• Some grams of sample
• Energy Resolution 300 eV
XRF Si(Li) commercial detector result – 4 g molecules with Cu and Br
Application in crystallography
Present in air
X –ray source
Elements in the crystal
Setup
Monochromatic X-ray beam
17.4 keV
Tunable intensity
5 mA < I < 40 mA
20 kV < V < 40 kV
Application in crystallography
X-ray tube
collimator
cristal
MIMOSA 5
Application in crystallography
12 h (30kevents) = 12.5 min Effective Exposure Time
1 h 5 kevent – 125 sec EET
• Cluster spectrum is good enough to determine how many elements are in the crystal
• Precise energy estimation is difficult because of charge collection inefficiency
• This analysis can be extremely fast
• This analysis can be enough for the crystallographer to confirm or refuse his hypothesis about the sample
• You can have something much more precise, but you need high statistics
Cluster spectrum
Cu
ArBr
Mo
Application in crystallography
Ratio seed/cluster charge collected
• Select 100% charge collection efficiency events
• Less than the 10 % of total events
• In theory 1 pixel cluster events ?
Seed spectrum 12 h
This effects is under investigation
• Temperature effect
• Left over
• Physical charge sharing
Ar Cu Br Mb
Application in crystallography
1 2
1 2
2
1
43
3
4
Peak(keV) Element(keV)
11.91 + 0.32 Br 11.92
8.09 + 0.35 Cu 8.05
2.61 + 0.37 Ar 2.9
17.01 + 0.41 Mo 17.4
• All compatible
• Energy resolution 350 eV !!!
3
Conclusions
• Direction where to go
Cooling
Application in crystallography
• Two analysis possibilities
Fast and dirty
Longer and accurate350 eV energy resolution
Duty cycle
• Note Companies extremely interested
3H 14C 32P 33P
3H is better and also the most challenging
Biological samples Imaging
Sensitive volume
Image blurring
MPV 3.8 keV
End point 18.6 keV
Mean 5.7 keV
θ
Autoradiography
Sample
Requirements for the application
• High sensitivity to low energy electrons
• Fast read-out
• High imaging capability
• Phosphor imaging plate
Sensitivity two orders of magnitude higher respect with films
Reusable
5 orders of magnitudes dynamic range
Low image resolution in case of low energy source
Only one label detectable
Existing devices
Biological samples Imaging
• Films
Very poor detection efficiency. Weeks of exposition are needed
Minimal sensitivity
Tritium Imaging
Tritium standards Slide with 14 dots
4X5 mm2
9.8 kBq 7.4 10-2kBq
4.86 kBq 4.0 10-2 kBq
2.76 kBq 2.1 10-2kBq
1.26 kBq 1.1 10-2kBq
7.3 10-1kBq 5.8 10-3kBq
3.3 10-1kBq 2.8 10-3kBq
1.6 10-1kBq 0 kBq
2.8 10-3kBq
12 h 100,000 frames – 9200 hits
Tritium ImagingImaging in function of z
0.60 mm 0.75 mm
1 mm 1.25 mm 1.5 mm
9.8 kBq Tritium dot activity
n° o
f hits
per
fram
e
distance [mm]
Tritium Imaging
Image quality
• Take the projection of the dot
• Calculate the slope of the projection
• The width of the slope function in corrispondence of the dot edges is a figure of merite of the image quality
Distance [mm]Distance [mm]
pixe
l
pixe
l
Tritium Imaging
Spectrum in function of z
0.62 mm 0.74 mm 1 mm 1.25 mm 1.5 mm
Tritium Imaging
3H vs. 14C Distance 0.2 mm
Spatial resolution = 115 micron
Spatial resolution = 340 micron
Tritium Imaging
Conclusions for tritium imaging
• Better image quality with 3H respect with 14C Importance of low-energy source Importance of thin sensitive volume
• The distance from the source is critical for: Image quality Spectrum quality Efficiency
• Sensitivity of the sensor is very high up to 2.8 10-3 kBq It is able to cover the range intensity needed in almost all the applications
• Next step Imaging of a real sample
•High spatial resolution with tritium 115 micronAt least comparable with other devices
• Spot dimensions are 50-200 microns diameter
Protein microarray
• There are 106 different proteins produced in human cells
• You need to study proteins properties and interactions
• You need high troughput low-cost analysis instrument
Fluorescence analysis
PMT
• No imaging capability
• Low-sensitivity
CCD
Protein microarray
• Single photon sensitivity
• Low QE = 20 %
• Imaging capability
• High QE
Requirements
• High QE
• High spatial resolution
• Imaging capability
• Fast readout
• Low-cost
• Scanning tecnique
Protein microarray
Two different isotopes with different decay energies replace the fluorescent markers
32P
33P
1710 keV 695 keV
249 keV 76 keV
End point Mean energy
Separablespectra
MAPS
• Single dacay sensitivity
• Real time
• High spatial resolution
• High image quality
Nano patterned surfaces
• High density
• High functionality
• Stability of the process
• High QE =100%
• Riproducibility
• Specific immobilisation
• Technique exploits CMOS sensors and nanostructured surfaces to detect radiolabelled proteins.
PEG (Poly Ethylene Glycol)
PAA (Poly Acrylic Acid)
Protein microarray – Surface
Traditional surface
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
COOH
NH 2
NH2
NH2
NH 2
NH2
NH2
NH2
NH2
NH 2
NH2
NH2
NH 2
NH2
NH2
NH2
NH2
NH 2
NH2
NH2
NH 2
NH2
NH2
NH2
NH2
NH 2
NH2
NH2
NH 2
NH2
NH2
NH2
NH2
NH2
NH2
NH2
NH2
NH2
NH2
NH2
NH 2
-COOH + -NH2 = CON
H
+ H2O
Amminic Binding
Activation Incubation Washing
• pH solution
• Temperature
• Time of reaction
• pH solution
• Temperature
• Time
• EDC and NHS quantity
• Temperature
• Method
• Solution
Thanks to Dr. Mila Silvia
PEG (Poly Ethylene Glycol)
PAA (Poly Acrylic Acid)
Surfaces by Joint Research Center – Ispra (Italy)
Protein microarray – Surface
Nanocraters
Valsesia et al. Adv. Funct. Mater. 2006,16, 1242
Atomic Force Miscroscope Imaging
Flu
ores
cenc
e (a
.u.)
Scan direction (nm)
Fluorescent confocal microscope BSA (Bovine Serum Albumin)
Protein microarray – Surface
Valsesia et al. Adv. Funct. Mater. 2006,16, 1242
• Hybrid• squared pixels, 55 m pitch• 256 x 256 pixel matrix• leakage current compensation• energy windowing with lower and upper thresholds, tunable on each pixel by a 3 bit DAC • 13 bit counter • max counting frequency ~ 1MHz• max readout frequency ~ 100 MHz• 250 m thickness sensitive volume
Medipix2
Best results obtained
Protein microarray - Results
• Medipix
Because very fast and real time
• Millimetric spot
Best results obtained
Protein microarray - Results
Y projection X projection
Protein microarray
Conclusions for protein microarray application
• High sensitive low-cost detection method is needed in this field in order to push surface R&D
• Results with the Medipix are very encouraging from the point of view of the sensor
• Surface properties investigation is going on
• Measure with MIMOSA 5 are coming
• Mesure with two separable spectra markers: energy weighted imaging
• non HEP applications may really be a great fun!
• HEP sensors most often are NOT what you really need but they are the “workhorse” for a demonstrator program and define the guidelines for application specific developments
Final Conclusion
• Thanks to the collegues of Department of Structural & Functional Biology, University of Insubria and to Ispra JRC researchers.
The End
Immobilisation chemestry
bAckUP
bAckUP
Example of diagnostic application of microarray
Calibration
G = 16.6 ± 0.6 e-/ADC
CCE = 73%
Application in crystallography- Imaging
Application in crystallography- Imaging
X-ray tube
collimator
attenuator
cristal
nail
MIMOSA 5I = 3.9 keV
Pd = 2.8 keV
EQ FY
70% 0.1
Lα
0.0585%
Diffraction peaks
S/B increased by a factor 10
Application in crystallography- Imaging
bAckUP
bAckUP