Chrome Extension
WeChat Mini Program
Use on ChatGLM

Evaluation of sensors for the detection of energy resolved very soft x-ray fluorescence

X-Ray, Optical, and Infrared Detectors for Astronomy X(2022)

Cited 0|Views13
No score
Abstract
Energy-dispersive imaging spectroscopy of X-ray emission from the Earth's aurorae promises to further knowledge in the field of aeronomy. Time- and spatially-resolved observations of fluorescence from the dominant atmospheric components require the detection of X-rays as soft as 390 eV with a resolution of no more than 100 eV at these energies. The Auroral X-ray Imaging Spectrometer (AXIS) instrument of the Disturbed and quiet time Ionosphere-thermosphere System at High Altitudes (DISHA) mission is expected to perform these observations. The baseline instrument design has suggested the use of an electron-multiplying charge-coupled device (EMCCD). The EMCCD's electron-multiplying register can reduce the effective readout noise and enable the detection of signals as small as a single photoelectron. For the detection of soft X-rays, however, the noise penalty from the EM register's stochastic process degrades energy resolution. Emerging CMOS image sensors (CIS), particularly the Teledyne e2v CIS221-X test device, with back illumination, full depletion (with 36 mu m thickness), large pixel sizes (40 mu m), and low readout noise (3 e- rms effective) are expected to achieve the required performance without the effects of the EM register. Simple models for X-ray event sensitivity, detectability, and resolution, indicate that candidate CIS equal or better EMCCD performance. Furthermore, CIS offer other advantages including lower power consumption, higher operating temperature, and increased radiation hardness. However, these sensors introduce other behaviors that may impact their apparent benefits, which initial experimental testing and analyses are working to understand.
More
Translated text
Key words
CCD, EMCCD, CIS, Soft X-ray, AXIS, DISHA, imaging spectroscopy
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined