Two-Phase Thermal Management of Silicon Detectors for High Energy Physics

Author(s):  
Paolo Petagna ◽  
Bart Verlaat ◽  
Andrea Francescon
2022 ◽  
Vol 17 (01) ◽  
pp. C01022
Author(s):  
T. Croci ◽  
A. Morozzi ◽  
F. Moscatelli ◽  
V. Sola ◽  
G. Borghi ◽  
...  

Abstract In this work, the results of Technology-CAD (TCAD) device-level simulations of non-irradiated and irradiated Low-Gain Avalanche Diode (LGAD) detectors and their validation against experimental data will be presented. Thanks to the intrinsic multiplication of the charge within these silicon sensors, it is possible to improve the signal to noise ratio thus limiting its drastic reduction with fluence, as it happens instead for standard silicon detectors. Therefore, special attention has been devoted to the choice of the avalanche model, which allows the simulation findings to better fit with experimental data. Moreover, a radiation damage model (called “New University of Perugia TCAD model”) has been fully implemented within the simulation environment, to have a predictive insight into the electrical behavior and the charge collection properties of the LGAD detectors, up to the highest particle fluences expected in the future High Energy Physics (HEP) experiments. This numerical model allows to consider the comprehensive bulk and surface damage effects induced by radiation on silicon sensors. By coupling the “New University of Perugia TCAD model” with an analytical model that describes the mechanism of acceptor removal in the multiplication layer, it has been possible to reproduce experimental data with high accuracy, demonstrating the reliability of the simulation framework.


2003 ◽  
Vol 50 (4) ◽  
pp. 1121-1128 ◽  
Author(s):  
A. Candelori ◽  
D. Bisello ◽  
R. Rando ◽  
A. Kaminski ◽  
J. Wyss ◽  
...  

1999 ◽  
Vol 11 (6) ◽  
pp. 1281-1296
Author(s):  
Marco Budinich ◽  
Renato Frison

We present two methods for nonuniformity correction of imaging array detectors based on neural networks; both exploit image properties to supply lack of calibrations and maximize the entropy of the output. The first method uses a self-organizing net that produces a linear correction of the raw data with coefficients that adapt continuously. The second method employs a kind of contrast equalization curve to match pixel distributions. Our work originates from silicon detectors, but the treatment is general enough to be applicable to many kinds of array detectors like those used in infrared imaging or in high-energy physics.


Author(s):  
Chakresh Jain ◽  
Geetika Jain ◽  
Ranjeet Dalal ◽  
Ashutosh Bhardwaj ◽  
Kirti Ranjan ◽  
...  

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