edfas.org ELECTRONIC DEV ICE FA I LURE ANALYSIS | VOLUME 24 NO . 4 10 PARAMETER EXTRACTION Following the previously mentioned steps will lead to a spectral photon emission result that can be trusted and from which accurate device or emission parameters can be derived. Electron temperature Te. Spectral distribution of a photon emission caused by acceleration and scattering of electronswithin an electrical field canbe approximatedby the Maxwell-Boltzmann distribution.[3] Thus, the spectral distribution follows the formula: Ispec(Eph) = I0 · e-Eph/kT Eq 7 where Eph is the considered photon energy or wavelength respectively, k is the Boltzmann constant, and T is the temperature, in this case it can be considered as electron temperature Te. A few transformations of Eq 7 lead to Te in relation to the slope, m, of the logarithmic plotted PE intensity. Whereas m can be graphically determined:[11] Te = -1/(km) Eq 8 Band gap. A Gaussian-shaped spectral distribution indicates that a band-band recombination process causes the photon emission. Such a shape couldbe used to determine the band gap of the analyzed material.[9] CONCLUSION A method for extracting precise photon emission spectra measured with InGaAs detectors was long overdue. It is nowavailable and is presented in this article. Basedonmeticulous SPEMsystemcalibration, thoroughly performed SPEM measurement and data handling, confidence in SPEM measurement results can be drastically increased. As the provided substitution-based step-bystep guide for calibrating a SPEM system combines the optical properties of the whole system into a single factor Csys, this method can easily deal with uncertainties for optical properties of individual system components. The provided step-by-step spectral data extraction guide shows that accurate handling of incorporated noise as well as handling the wavelength dependent bulk absorption can significantly influence the quality of the extracted spectral data. For accurate correction of the bulk absorption, thedoping concentrationof the substrate should be considered in more detail. This article discusses different types of errors that can occur during the calibration of a SPEM system and the subsequent data extraction, and their consequences for spectral evaluation. The most obvious impact of these errors can be identified in the spectral distribution. A non-exponential relationship between photon emission intensity and photon energy emanating from a FET in saturation is a proof of incomplete SPEM system calibration. Insufficient noise floor intermittency leads to a steep increase in the slope in the extracted spectra, due to the large systemtransformation factors Csys resulting fromthe decreasing detector sensitivity. With the system in good shape, it is possible to extract trustworthy spectral data from a SPEM measurement. A quantitative and trustworthy evaluation of the spectral data allows the extraction of the electron temperature (Te) as described in Reference 18 or the extraction of effective band-gap energy.[9] However, due to mechanical tolerances and aging components such as the light source or the detector, it is recommended to repeat the presented calibration procedure at regular intervals. This could be part of a system’s regular preventive maintenance schedule. REFERENCES 1. J. Phang, et al.: “A Review of Near Infrared Photon Emission Microscopy and Spectroscopy,” Proc. Int. Symp. Phys. Failure Anal. Integr. Circuits, 2005, p. 275–281. 2. A. Glowacki, C. Boit, P. Perdu, and Y. Iwaki: “Backside Spectroscopic Photon Emission Microscopy using Intensified Silicon CCD,” Microelectron. Reliab., 2014, Vol. 54, 9-10, p. 2105–2108, doi: 10.1016/j.microrel.2014.07.132. 3. I. Vogt, T. Nakamura, B. Motamedi, and C. Boit: “Device Characterization of 16/14 nm FinFETs for Reliability Assessment with Infrared Emission Spectra,” Microelectron. Reliab., 2018, 88-90, p. 11–15, doi: 10.1016/j.microrel.2018.07.012. 4. U. Kindereit, et al.: “Near-infrared Photon Emission Spectroscopy of a 45 nm SOI Ring Oscillator,” IEEE Int. Reliab. Phys. Symp. Proc., 2D.2.1-2D.2.7. 5. A. Toriumi, M. Yoshimi, M. Iwase, and K. Taniguchi: “Experimental Determinationof Hot-carrier EnergyDistribution andMinority Carrier Generation Mechanism due to Hot-carrier Effects,” IEEE Int. Electron Devices Meet., 1985, p. 56–59. 6. D.L. Barton, et al.: “Infrared Light Emission from Semiconductor Devices,” 1996, https://www.osti.gov/servlets/purl/390573. 7. S. Tan, et al.: “Detectivity Optimization of InGaAs Photon Emission Microscope Systems,” Proc. Int. Symp. Phys. Failure Anal. Integr. Circuits, 112006, p. 315–319. 8. C. Boit, “Fundamentals of Photon Emission (PEM) in Silicon— Electroluminescence for Analysis of Electronic Circuit and Device Functionality,” Microelectronics Failure Analysis: Desk Reference, 2004, p. 356–368. 9. A. Beyreuther, et al.: “Contactless Parametric Characterization of Bandgap Engineering in p-type FinFETs using Spectral Photon Emission,” Microelectron. Reliab., 2019, Vol. 92, p. 143-148, doi: 10.1016/j.microrel.2018.11.008. 10. N. Herfurth and C. Boit: “Meticulous System Calibration as a Key for Extracting Correct Photon Emission Spectra,” Proc. Int. Symp. Phys. Failure Anal. Integr. Circuits, 2021, p. 1–5. 11. A. Glowacki, C. Boit, P. Perdu, and Y. Yokoyama: “Electron Temperature - The Parameter to be Extracted fromBackside Spectral Photon Emission,” IEEE Int. Reliab. Phys. Symp. 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