A novel detection scheme for large area imaging of low energy X-rays using amorphous silicon technology

Author(s):  
K. Aflatooni ◽  
A. Nathan ◽  
R.I. Hornsey ◽  
I.A. Cunningham
2012 ◽  
Vol 83 (5) ◽  
pp. 053105 ◽  
Author(s):  
T. R. Gentile ◽  
M. Bales ◽  
U. Arp ◽  
B. Dong ◽  
R. Farrell

2007 ◽  
Vol 85 (5) ◽  
pp. 479-485 ◽  
Author(s):  
M Cargnelli ◽  
T Ishiwatari ◽  
P Kienle ◽  
J Marton ◽  
E Widmann ◽  
...  

At the DAΦNE electron–positron collider of Laboratori Nazionali di Frascati we study kaonic atoms, taking advantage of the low-energy kaons produced in the Φ-meson decay. The low-energy kaon–nucleon interaction in kaonic hydrogen and kaonic deuterium can be investigated under favorable conditions. The DEAR (DAΦNE Exotic Atom Research) experiment at LNF delivered the most precise data on kaonic hydrogen up to now. DEAR and its follow-up experiment SIDDHARTA (Silicon Drift Detector for Hadronic Atom Research by Timing Application) are using X-ray spectroscopy of kaonic hydrogen and kaonic deuterium atoms to measure the strong interaction-induced shift and width of the ground state. From these quantities the isospin-dependent antikaon–nucleon scattering lengths can be determined, quantities useful for testing the understanding of chiral symmetry breaking in the strangeness sector. Within the SIDDHARTA project new X-ray detectors are being developed. We will use an array of large area silicon drift detectors (SDDs) having excellent energy resolution but also providing a timing capability that will result in a huge suppression of background and so overcome the precision limits of the former experiments.PACS Nos.: 36.10.k, 13.75.Jz, 32.30.Rj and 29.40.Wk


1983 ◽  
Vol 207 (3) ◽  
pp. 429-435 ◽  
Author(s):  
H.P. Von Arb ◽  
J. Böcklin ◽  
F. Dittus ◽  
R. Ferreira Marques ◽  
H. Hofer ◽  
...  

1993 ◽  
Vol 04 (04) ◽  
pp. 327-332
Author(s):  
M. D. BINNS ◽  
F. J. CLOUGH ◽  
S. C. J. GARTH

To apply neural networks to many engineering applications, large networks will be required. Such networks are difficult to build using standard crystalline silicon technology due to limitations in both the fabrication and packaging processes. An architecture is proposed where amorphous silicon photoresistors are used to store the synaptic weights. A single plate of amorphous silicon is able to contain up to 100 million photoresistors, exploiting readily available fabrication technology. Using an external light source, each photoresistor can be individually adjusted allowing them to be configured as programmable fixed-value resistors. The processing compatibility of polysilicon and amorphous silicon allows the same glass substrate to be used for large-area integration of the photosensors, the analogue neural network and the neurons. The integration of the photosensors and the rest of the network may be used to alleviate the interface problem at the inputs resulting in a design with a very simple architecture that is both elegant and simple to fabricate. This paper describes such a design in which amorphous silicon technology is applied to neural network hardware.


1980 ◽  
Vol 176 (1-2) ◽  
pp. 105-109 ◽  
Author(s):  
J. Böcklin ◽  
F. Dittus ◽  
R. Ferreira Marques ◽  
H. Hofer ◽  
F. Kottmann ◽  
...  

2010 ◽  
Author(s):  
Mohammad Y. Yazdandoost ◽  
Kyung W. Shin ◽  
Nader Safavian ◽  
Farhad Taghibakhsh ◽  
Karim S. Karim

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