Dark Current Random Telegraph Signals in Solid-State Image Sensors

This paper focuses on the Dark Current-Random Telegraph Signal (DC-RTS) in solid-state image sensors. The DCRTS is investigated in several bulk materials, for different surface interfaces and for different trench isolation interfaces. The main parameter used to characterize the DC-RTS is the transition maximum amplitude which seems to be the most appropriate for studying the phenomenon and identifying its origin. Proton, neutron and Co-60 Gamma-ray irradiations are used to study DC-RTS induced by both Total Ionizing Dose (TID) and Displacement damage (Dd) dose. Conclusions are drawn by analyzing the correlation between the exponential slope of the transition maximum amplitude histogram and the location of the DC-RTS-induced defects. The presented results can be extrapolated to predict DC-RTS distributions in various kinds of solid state image sensors

Dark Current Spectroscopy in neutron, proton and ion irradiated CMOS Image Sensors

The dark current spectroscopy is tested on twenty CMOS image sensors irradiated with protons, neutrons and various ions at different energies. The aim of this work is to differentiate the effect of coulomb and nuclear interactions on the radiation-induced dark current distribution and to identify the main radiation-induced defects responsible for the dark current increase for each type of interaction. For low-energy protons and low-energy light ions (which produce well-separated low energy coulomb interactions), we find that most of the pixels belong to a quantized dark current spectrum at low dark current. In these pixels, the dark current increase seems mainly dominated by specific point defects such as the divacancy and the vacancy-phosphorus complex. Thus, these simple defects seem to form when the displacement damage is rather low and sparse. On the contrary, for nuclear interactions (with neutrons or high-energy protons) producing high coulomb NIEL silicon PKAs or for low energy heavy ions (also having high coulomb NIEL), the DCS spectrum is not visible and all the pixels belong to an exponential hot pixel tail which extends to very high dark current. In these pixels, the dark current increase is mainly dominated by defects with close-to-midgap energy levels. These defects seem more complex than point defects because they can have many different generation rates (explaining the smooth hot pixel tail) and because they tend to form when the displacement damage is high and dense

Validation of a model for Dark Current Non Uniformity generated by Displacement Damage Dose in irradiated CMOS Image Sensors

Validation of a model for Dark Current Non Uniformity generated by Displacement Damage Dose in irradiated CMOS Image Sensors

Dark Current Spectroscopy on Alpha Irradiated Pinned Photodiode CMOS Image Sensors

Dark Current Spectroscopy (DCS) is tested for the first time on irradiated Pinned PhohoDiode (PPD) CMOS Image sensors (CIS) to detect and identify radiation-induced silicon bulk defects in the depleted volume of the pixels. Two different CIS are tested: a 5MP Commercial-Off-The-Shelf (COTS) CIS from OmniVision (OV5647) and a 256x256 pixels custom CIS. These CISs are irradiated with alpha particles at various fluences and two different particle energies are tested on the custom CIS (4 MeV and < 500 keV). Several types of defects are detected in both CIS (up to five defects in the custom CIS). The dark current is measured at various temperatures to extract the activation energy and deduce the energy levels of the defects. The defect formation rate per unit fluence is calculated. In the custom CIS, the annealing behavior of the defects is also studied by performing an isochronal annealing. Two different defects are identified: the divacancy and the vacancy-phosphorus. This work proves that the DCS technique can be used on irradiated CIS to detect and identify radiation-induced defects in silicon

Dark Current Spectroscopy in neutron, proton and ion irradiated CMOS Image Sensors: from Point Defects to Clusters

The dark current spectroscopy is tested on twenty CMOS image sensors irradiated with protons, neutrons and various ions at different energies. The aim of this work is to differentiate the effect of coulomb and nuclear interactions on the radiation-induced dark current distribution and to identify the main radiation-induced defects responsible for the dark current increase for each type of interaction. For low-energy protons and low-energy light ions (which produce well-separated low energy coulomb interactions), we find that most of the pixels belong to a quantized dark current spectrum at low dark current. In these pixels, the dark current increase seems mainly dominated by specific point defects such as the divacancy and the vacancy-phosphorus complex. Thus, these simple defects seem to form when the displacement damage is rather low and sparse. On the contrary, for nuclear interactions (with neutrons or high-energy protons) producing high coulomb NIEL silicon PKAs or for low energy heavy ions (also having high coulomb NIEL), the DCS spectrum is not visible and all the pixels belong to an exponential hot pixel tail which extends to very high dark current. In these pixels, the dark current increase is mainly dominated by defects with close-to-midgap energy levels. These defects seem more complex than point defects because they can have many different generation rates (explaining the smooth hot pixel tail) and because they tend to form when the displacement damage is high and dense

Dark Current Blooming in Pinned Photodiode CMOS Image Sensors

This paper demonstrates the existence of dark current blooming in pinned photodiode CMOS image sensors with the support of both experimental measurements and TCAD simulations. It is usually assumed that blooming can appear only under illumination, when the charge collected by a pixel exceeds the full well capacity (i.e. when the photodiode becomes forward biased). In this work, it is shown that blooming can also appear in the dark by dark current leakage from hot pixels in reverse bias (i.e. below the full well capacity). The dark current blooming is observed to propagate up to nine pixels away in the experimental images and can impact hundreds of pixels around each hot pixel. Hence, it can be a major image quality issue for state-of-the-art pinned photodiode CMOS Image Sensors used in dark current limited applications such as low-light optical imaging and should be taken into account in the dark current subtraction process. This work also demonstrates that one of the key parameter for dark current optimization, the transfer gate bias during integration, has to be carefully chosen depending on the application because the optimum bias for dark current reduction leads to the largest dark current blooming effects

Multidetector computed tomography angiography for assessment of in-stent restenosis: meta-analysis of diagnostic performance

<p>Abstract</p> <p>Background</p> <p>Multi-detector computed tomography angiography (MDCTA)of the coronary arteries after stenting has been evaluated in multiple studies.</p> <p>The purpose of this study was to perform a structured review and meta-analysis of the diagnostic performance of MDCTA for the detection of in-stent restenosis in the coronary arteries.</p> <p>Methods</p> <p>A Pubmed and manual search of the literature on in-stent restenosis (ISR) detected on MDCTA compared with conventional coronary angiography (CA) was performed. Bivariate summary receiver operating curve (SROC) analysis, with calculation of summary estimates was done on a stent and patient basis. In addition, the influence of study characteristics on diagnostic performance and number of non-assessable segments (NAP) was investigated with logistic meta-regression.</p> <p>Results</p> <p>Fourteen studies were included. On a stent basis, Pooled sensitivity and specificity were 0.82(0.72–0.89) and 0.91 (0.83–0.96). Pooled negative likelihood ratio and positive likelihood ratio were 0.20 (0.13–0.32) and 9.34 (4.68–18.62) respectively. The exclusion of non-assessable stents and the strut thickness of the stents had an influence on the diagnostic performance. The proportion of non-assessable stents was influenced by the number of detectors, stent diameter, strut thickness and the use of an edge-enhancing kernel.</p> <p>Conclusion</p> <p>The sensitivity of MDTCA for the detection of in-stent stenosis is insufficient to use this test to select patients for further invasive testing as with this strategy around 20% of the patients with in-stent stenosis would be missed. Further improvement of scanner technology is needed before it can be recommended as a triage instrument in practice. In addition, the number of non-assessable stents is also high.</p