Feasibility of hard X-ray imaging using monolithic active pixel sensors (MAPS)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Argonne National Lab. (ANL), Lemont, IL (United States)
- California Inst. of Technology (CalTech), Pasadena, CA (United States)
Silicon detectors have been widely used in high energy physics (HEP) experiments. The outstanding properties of silicon detectors include radiation hardness, small material budget, fine spatial resolution, high speed and low cost. In this paper, we report initial results of using a single-bit Monolithic Active Pixel Sensor (MAPS), a leading candidate for the next generation trackers in high luminosity colliders, for hard X-ray imaging. The MAPS responses to X-ray with different energies are obtained and compared with simulation. The observed cluster sizes are larger than that predicted by the Continuous Slowing Down Approximation (CSDA) model, indicating that the charge diffusion process might play an important in the MAPS response to low energy electrons. In conclusion, this work paves the way towards multiple layer ultrafast silicon sensor applications in synchrotrons and XFEL beamlines.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC). Nuclear Physics (NP) (SC-26); USDOE Office of Science (SC), Nuclear Physics (NP)
- Grant/Contract Number:
- AC52-06NA25396; AC02-06CH11357
- OSTI ID:
- 1477668
- Alternate ID(s):
- OSTI ID: 1606504; OSTI ID: 1776902
- Report Number(s):
- LA-UR-18-25502
- Journal Information:
- Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 954; Conference: 2018 Symposium on Radiation Measurements and Applications (SORMA XVII), Ann Arborm MI (United States), 11-14 Jun 2018; ISSN 0168-9002
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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