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Signal processing for time resolved photoluminescence spectroscopy

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EN
Abstrakty
EN
Accurate determination of material parameters, such as carrier lifetimes and defect activation energy, is a significant problem in the technology of infrared detectors. Among many different techniques, using the time resolved photoluminescence spectroscopy allows to determine the narrow energy gap materials, as well as their time dynamics. In this technique, it is possible to observe time dynamics of all processes in the measured sample as in a streak camera. In this article, the signal processing for the above technique for Hg1-xCdxTe with a composition x of about 0.3 which plays an extremely important role in the mid-infrared is presented. Machine learning algorithms based on the independent components analysis were used to determine components of the analyzed data series. Two different filtering techniques were investigated. In the article, it is shown how to reduce noise using the independent components analysis and what are the advantages, as well as disadvantages, of selected methods of the independent components analysis filtering. The proposed method might allow to distinguish, based on the analysis of photoluminescence spectra, the location of typical defect levels in HgCdTe described in the literature.
Twórcy
  • Military University of Technology, 2 Kaliskiego St., Warsaw 00-908, Poland
  • Military University of Technology, 2 Kaliskiego St., Warsaw 00-908, Poland
  • Military University of Technology, 2 Kaliskiego St., Warsaw 00-908, Poland
  • Military University of Technology, 2 Kaliskiego St., Warsaw 00-908, Poland
autor
  • Military University of Technology, 2 Kaliskiego St., Warsaw 00-908, Poland
Bibliografia
  • [1] Kopytko, M. et al. High-operating temperature MWIR nBn HgCdTe detector grown by MOCVD. Opto-Electron. Rev. 21, 402–405 (2013). https://doi.org/10.2478/s11772-013-0101-y
  • [2] Kopytko, M., Kebłowski, A., Gawron, W. & Madejczyk, P. Different cap-barrier design for MOCVD grown HOT HgCdTe barrier detectors. Opto-Electron. Rev. 23, 143–148 (2015). https://doi.org/10.1515/oere-2015-0017
  • [3] Rogalski, A. HgCdTe infrared detector material: History, status and outlook. Rep. Prog. Phys. 68, 2267–2336 (2005). https://doi.org/10.1088/0034-4885/68/10/R01
  • [4] Bhan, R.-K. & Dhar, V. Recent infrared detector technologies, applications, trends and development of HgCdTe based cooled infrared focal plane arrays and their characterization. Opto-Electron. Rev. 27, 174–193 (2019). https://doi.org/10.1016/j.opelre.2019.04.004
  • [5] Izhnin, I. et al. Photoluminescence of HgCdTe nanostructures grown by molecular beam epitaxy on GaAs. Opto-Electron. Rev. 21, 390–394 (2013). https://doi.org/10.2478/s11772-013-0103-9
  • [6] Madejczyk, P. et al. Control of acceptor doping in MOCVD HgCdTe epilayers. Opto-Electron. Rev. 18, 271–276 (2010). https://doi.org/10.2478/s11772-010-1023-x
  • [7] Martyniuk, P., Koźniewski, A., Kebłowski, A., Gawron, W. & Rogalski, A. MOCVD grown MWIR HgCdTe detectors for high operation temperature conditions. Opto-Electron. Rev. 22, 118–126 (2014). https://doi.org/10.2478/s11772-014-0186-y
  • [8] Piotrowski, J. et al. Uncooled MWIR and LWIR photodetectors in Poland. Opto-Electron. Rev. 18, 318–327 (2010). https://doi.org/10.2478/s11772-010-1022-y
  • [9] Wang, H., Hong, J., Yue, F., Jing, C. & Chu, J. Optical homogeneity analysis of Hg1−xCdxTe epitaxial layers: How to circumvent the influence of impurity absorption bands? Infrared Phys. Technol. 82, 1–7 (2017). https://doi.org/10.1016/j.infrared.2017.02.007
  • [10] Yue, F., Wu, J. & Chu, J. Deep/shallow levels in arsenic-doped HgCdTe determined by modulated photoluminescence spectra. Appl. Phys. Lett. 93, 131909 (2008). https://doi.org/10.1063/1.2983655
  • [11] Yue, F.-Y. et al. Optical characterization of defects in narrow-gap HgCdTe for infrared detector applications. Chin. Phys. B 28, 17104 (2019). https://doi.org/10.1088/1674-1056/28/1/017104
  • [12] Hyvärinen, A. & Oja, E. Independent component analysis: Algorithms and applications. Neural Netw. 13, 411–430 (2000). https://doi.org/10.1016/S0893-6080(00)00026-5
  • [13] Grodecki, K. et al. Enhanced Raman spectra of hydrogen-intercalated quasi-free-standing monolayer graphene on 4H-SiC(0001). Physica E 117, 113746 (2020). https://doi.org/10.1016/j.physe.2019.113746
  • [14] Grodecki, K. & Murawski, K. New data analysis method for time-resolved infrared photoluminescence spectroscopy. Appl. Spectrosc. 75, 596-599 (2020). https://doi.org/10.1177/0003702820969700
  • [15] Hong-Yan, L., Zhao, Q.-H., Ren, G.-L. & Xiao, B.-J. Speech enhancement algorithm based on independent component analysis. in 5th Int. Conf. on Natural Computation (ICNC 2009) 2, 598–602 (2009). https://doi.org/10.1109/ICNC.2009.76
  • [16] Wen, S. & Ding, D. FASTICA-based firefighters speech noise reduction. in Proc. 2015 of 8th Int. Congress on Image and Signal Processing (CISP 2015) 1423–1426 (2016). https://doi.org/10.1109/CISP.2015.7408106
  • [17] Yue, F.-Y. et al. Optical characterization of defects in narrow-gap HgCdTe for infrared detector applications. Chin. Phys. B 28, 17104–017104 (2019). https://doi.org/10.1088/1674-1056/28/1/017104
  • [18] Zhang, X. et al. Infrared photoluminescence of arsenic-doped HgCdTe in a wide temperature range of up to 290 K. J. Appl. Phys. 110, 043503 (2011). https://doi.org/10.1063/1.3622588
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ae26ab8c-1d36-4e8f-8aed-41f82abc6395
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