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Modeling for Ultra Low Noise CMOS Image Sensors

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Modeling for Ultra Low Noise CMOS Image Sensors Thèse n° 7661 Modeling for Ultra Low Noise CMOS Image Sensors Présentée le 10 septembre 2020 à la Faculté des sciences et techniques de l’ingénieur Laboratoire de circuits intégrés Programme doctoral en microsystèmes et microélectronique pour l’obtention du grade de Docteur ès Sciences par Raffaele CAPOCCIA Acceptée sur proposition du jury Prof. E. Charbon, président du jury Prof. C. Enz, directeur de thèse Prof. A. Theuwissen, rapporteur Prof. E. Fossum, rapporteur Dr J.-M. Sallese, rapporteur 2020 Ma Nino non aver paura di sbagliare un calcio di rigore, non è mica da questi particolari che si giudica un giocatore, un giocatore lo vedi dal coraggio, dall’altruismo e dalla fantasia. — Francesco De Gregori To my family. Acknowledgements I would like to express my deep gratitude to my thesis advisor, Prof. Christian Enz. His guid- ance and support over the past few years helped me to expand my knowledge in the area of device modeling and sensor design. I am genuinely grateful for having taught me how important is to be methodical and to insist on the detail. My grateful thanks are also extended to Dr. Assim Boukhayma for his contribution and for having introduced me to the fascinating world of image sensors. His help and encouragement over the entire time of my Ph.D. studies daily motivated me to improve the quality of the research. I wish to thank Dr. Farzan Jazaeri for everything he taught me during my Ph.D. His passion for physics and device modeling has been a source of inspiration for the research. I would also like to express my deepest gratitude to Prof. Edoardo Charbon, Prof. Jean-Michel Salles, Prof. Eric Fossum and Prof. Albert Theuwissen for being part of my jury, evaluating my thesis and providing comments and remarks about my work. My gratitude also goes to Dr. Wei Gao for providing me with the opportunity to conduct an internship in an industrial environment and participate in projects beyond the scope of this thesis. In addition, I must also thank the whole sensor and camera team for giving me the possibility to join their team. I would like to thank Dr. Chiao Liu, Dr. Andrew Berkovich, Dr. Elliott Tsai, Dr. Ziyun Li, Dr. Syed Shakib Sarwar, Reid Pinkham, Tianyi Yang and Seth Hirsh. I would like to thank Prof. Leblebici and Dr. Akin for their help and encouragement that inspired me during my master thesis to purse a Ph.D. degree. During my PhD, I had the opportunity to work together with two master students, Tijmen Spreij and Alban Morelle. I would like to thank them for the collaboration we had and for their work, which is partially included in this thesis. Thanks also to Dr. Althaus for helping me editing this manuscript. Particular thanks go to all my colleagues from ICLAB, current and former, for making these past few years a memorable experience. I would like then to express my sincerest thanks to my of- fice mates, Arnout Beckers and Chunmin Zhang, for all the support we always gave each other. I also want to thank all my lab mates: Mattia Cacciotti, Francesco Chicco, Vladimir Kopta, i Acknowledgements Sammy Cerida, Alessandro Pezzotta, Huang Huaiqi, Raghavasimhan Thirunarayanan, Antonio D’Amico, Antonino Caizzone, Vincent Camus, Jérémy Schlachter, Minhao Yang, Daniel Bold, Marta Franceschini and Salvatore Collura for all the fun conversation we had. I am also thankful to all the friends I met in Switzerland and the fun time we had outside of EPFL. I must acknowledge Mikhail, Navid, Gain, Jonathan, Pamela, Cosimo, Giorgio, Chiara, Michela, Eleonora, Selma e Marta. At the same time I want to acknowledge my friends outside Switzerland for their continuous support, so I thank Beppe, Giulio, Inger, Biagio, Ellis, Ruben, Andrea, Peppe and Fabio. Finally, my deep gratitude to my family for their continuous love. I am grateful to my sister Marta for always being there for me as a friend, my brothers Francesco e Matteo for their unparalleled support, and my parents Paola and Arcangelo. I am forever indebted to them for giving me the opportunities that have made me who I am. Neuchâtel, 2020 Raffaele Capoccia ii Abstract The low-light performance of a CMOS image sensor (CIS) is one of the most important perfor- mance metrics in a camera, whether it is used in products for consumer electronics or in an image-acquisition system for machine vision or the Internet-of-Things (IoT). At very low levels of illumination, the image sensors are limited by the noise generated by the readout circuits used to convert the information stored in the photodetector element, the pinned photodiode (PPD). Thanks to the development of efficient noise reduction techniques, modern CISs offer extremely interesting performance with sub-electron input-referred noise values. However, further noise reduction is needed to enable the single photon counting capability, which will allow new opportunities in a large variety of scientific applications. This thesis focuses on the modeling of ultra-low noise CISs by exploring two main research topics. The first is the modeling of the PPD device together with the transfer gate (TG). The interface between these two structures limits performance in many advanced applications and requires a deep understanding of the charge transfer process. The core of the first compact model for the charge transfer in PPDs is reported here. The second evaluates the impact of different techniques on total noise reduction. In particular, the in-pixel source follower (SF) optimization, the combination of the column-level gain with the correlated multiple sampling (CMS) order and the effect of technology downscaling are analyzed and then verified by software simulations and experimental results. The core of a physics-based compact model for the charge transfer in PPDs for CIS is presented in this dissertation. A set of analytical expressions is derived for the 2D electrostatic profile, the PPD capacitance, and the charge transfer current. The proposed model relies on the thermionic emission current mechanism, the barrier modulation and the full-depletion approximation to obtain the charge transfer current. The model is fully validated with station- ary and opto-electrical technology computer-aided design (TCAD) simulations. The charge transfer model is validated experimentally by the expression of the total amount of the trans- ferred charges derived from the charge transfer current and evaluated for different values of light intensity, TG voltage and transfer time. The result is a proven resource for CIS pixel designers in the analysis, simulation and optimization of PPD-based pixel in CISs. The main circuit-level technique for noise reduction studied in this thesis is the CMS, which is used to reduce the thermal noise and the residual flicker noise originated in the in-pixel SF.To verify the impact of the combination of the column-level gain and the analog CMS on the readout noise, a readout chain with variable gain and variable CMS order has iii Abstract been integrated in a standard 180 nm CIS process. The match between the measurement and the noise model results validates experimentally the model itself. Based on transient noise simulation results, the combination of an optimized pMOS source follower (SF), a column- level gain equal to 64 and a CMS of order 8 allows the noise to be reduced to the value of 0.20 erms, with a readout time of 43 &s. Key words: Charge Transfer Current, CMOS Image Sensors (CIS), Compact Device Modeling, Correlated Double Sampling (CDS), Correlated Multiple Sampling (CMS), Flicker noise, Passive Switched Capacitor, Photon Shot Noise, Photon Transfer Curve (PTC), Pinned Photodiode (PPD), Readout Noise, Temporal Noise, Thermal noise, Thermionic Emission Theory. iv Abstract Le prestazioni a bassa luminosità dei sensori di immagini CMOS sono una delle metriche più importanti per la caratterizzazione di fotocamere utilizzate nell’elettronica di consumo o in sistemi per l’acquisizione di immagini processate da elaboratori o nell’internet delle cose (IdC o IoT). A livelli molto bassi di illuminazione, i sensori di immagini sono limitati dal rumore originato dai circuiti elettronici di lettura, utilizzati a loro volta per convertire l’informazione immagazzinata nel dispositivo fotosensibile, il fotodiodo pinned o pinned photodiode (PPD). Grazie allo sviluppo di efficienti tecniche di riduzione del rumore, i moderni sensori CMOS offrono performance estremamente interessanti con valori di rumore espresso in carica elettrica e riferito all’ingresso del circuito al di sotto del singolo elettrone. Tuttavia, una riduzione addizionale del rumore è necessaria per permettere il conteggio dei singoli elettroni generati durante l’illuminazione, il quale aprirebbe ad una serie di nuove opportunità in diverse applicazioni scientifiche. Questa tesi si concentra sul modelllo dei sensori CMOS a bassa luminosità esplorando due ambiti principali di ricerca. Il primo è il modello del dispositivo PPD insieme al gate di trasferimento (o transfer gate (TG)). L’interfaccia tra queste due strutture limita le prestazioni in molte applicazioni avanzate e necessita di una comprensione profonda del processo di trasferimento di carica. Il nucleo del primo modello compatto per il trasferimento di carica nei PPD è presentato in questo dissertazione. Il secondo argomento valuta l’impatto delle diverse tecniche di riduzione del rumore. In particolar modo, l’ottimizzazione dell’inseguitore di tensione (o source follower (SF)) presente in ciascun pixel, la combinazione del guadagno in tensione applicato per ogni colonna dell’array del sensore con il campionamento multiplo correlato (Correlated Multiple Sampling (CMS)) e l’effetto dello scaling tecnologico sono analizzati e verificati con simulazioni software e risultati sperimentali. Il nucleo del modello compatto qui presentato è basato sulla fisica del dispositivo e descrive il trasferimento di carica nei PPD usati nei CIS. Un insieme di espressioni analitiche è derivato partendo dal profilo elettrostatico in due dimensioni (2D), insieme alla capacità del PPD e alla corrente di trasferimento.
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