4T CMOS Active Pixel Sensors under Ionizing Radiation

4T CMOS Active Pixel Sensors under

Ionizing Radiation

4T CMOS Active Pixel Sensors under

Ionizing Radiation

Proefschrift

ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,

op gezag van de Rector Magnificus prof. ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties,

in het openbaar te verdedigen op maandag 15 april 2013 om 10:00 uur

door

Jiaming TAN

Prof. dr. ir. A.J.P. Theuwissen

Samenstelling promotiecommissie:

Rector Magnificus voorzitter

Prof. dr. ir. A.J.P. Theuwissen Technische Universiteit Delft, promotor Prof. dr. C.I.M. Beenakker Technische Universiteit Delft

Prof. dr. P.J. French Technische Universiteit Delft Prof. dr. C. Claeys KU Leuven, België

Prof. dr. P. Magnan ISAE, Frankrijk

Prof. dr. ir. R. Dekker Technische Universiteit Delft Dr. S. Nihtianov Technische Universiteit Delft

ISBN: 978-94-6191-684-6

Printed by: Ipskamp Drukker B.V., Enschede, The Netherlands Copyright © 2013 by Jiaming TAN

Cover design: ZHANG Qin

All rights reserved. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the author.

To my great family and Zhang Qin 献给我亲爱的家人和张沁

Chapter 1 Introduction to CMOS Image Sensors in Radiation Environments... 1

1.1 Development of Image Sensors and Photography... 1

1.1.1 Early History of Photography and Cameras ... 1

1.1.2 CMOS Image Sensors: Past, Present and Future ... 2

1.2 CMOS Image Sensors in Radiation Environments ... 6

1.2.1 Space Application of CMOS Image Sensors ... 7

1.2.2 Medical Application of CMOS Image Sensors... 7

1.3 Basics of Radiation Sources and Damage ... 9

1.4 Motivation and Objectives... 12

1.5 Thesis Structure ... 14

1.6 References ... 15

Chapter 2 Device Characteristics and Radiation Effects of 4T CMOS Image Sensors.... 19

2.1 CMOS Image Sensor Pixels ... 19

2.2 Noise Sources in Pinned Photodiode 4T Pixel ... 25

2.2.1 Fixed-Pattern Noise ... 26

2.2.2 Temporal Noise ... 26

2.3 Spectral Response of 4T Pixels ... 29

2.4 Other Performance Parameters of the 4T Pixel ... 33

2.5 Dark Current in 4T Pixels... 34

2.5.1 Device Physics for Dark Current Generation... 35

2.5.2 Spatial Dark Current Composition within the 4T Pixel ... 45

2.5.3 Dark Current from STI... 47

2.6 Radiation Effects on the 4T Pixel... 48

2.6.1 Radiation Interaction with Silicon and Silicon Oxide... 49

2.6.2 Ionizing Radiation Damage Mechanism on Metal-Oxide-Silicon Devices . 51 2.6.3 Radiation-Induced Degradation on the 4T Pixel... 55

2.7 Radiation Hardened Techniques ... 56

2.8 Conclusion... 58

2.9 References ... 58

Chapter 3 Analysis of Ionizing Radiation Degradation of 4T CMOS Image Sensors ... 63

3.1 Background of Radiation Effects Study on 4T Pixels ... 63

3.2 Ionizing Radiation Degradation Measurements ... 64

3.2.1 Test Structures ... 64

3.2.2 Radiation Settings and Measurement Details ... 66

3.3 Ionizing Radiation Effects on CMOS Image Sensors and Elementary Test Devices ... 67

3.3.1 Radiation Performance of In-Pixel Test Devices... 67

3.3.2 Pixel Dark Signals Regarding Radiation Degradation... 71

Chapter 4 Pixel Bias Study and Microscopic View of Degradation for 4T Pixels under

Radiation... 85

4.1 Research Motivation... 85

4.2 Measurement Setting ... 86

4.3 Radiation Degradation with 4T Pixel Bias Condition and Trapped Charges ... 88

4.4 Microscopic Degradation Mechanism of Ionizing Radiation... 93

4.5 Conclusion ... 96

4.6 References ... 97

Chapter 5 Radiation-Hardened 4T CMOS Image Sensor Pixel Design ... 99

5.1 Radiation-Hardening-by-Design of CMOS Image Sensors... 99

5.2 Sensor Design and Measurement Set-up ... 100

5.3 4T Pixel Performance with Radiation-Hardened Techniques... 104

5.4 Ionizing Radiation Effects on Radiation-Hardened CMOS Image Sensors ... 109

5.5 Optical Performance of Radiation-Hardened 4T Pixels ... 112

5.6 Conclusion ... 113

5.7 References ... 115

Chapter 6 General Conclusions and Future Work ... 117

6.1 General Conclusions... 117

6.1.1 Radiation-Induced Degradation in 4T CMOS Image Sensors ... 117

6.1.2 Radiation-Hardening-by-Design of 4T Pixels... 120 6.2 Future Work ... 121 6.3 References ... 123 Summary... 125 Samenvatting ... 129 Abbreviation... 133 Acknowledgement... 135 List of Publications... 137

Chapter 1

Introduction to CMOS Image Sensors in

Radiation Environments

The invention of solid-state image sensors revolutionized photography by replacing traditional film with digital imaging. In today’s world, we enjoy the unprecedented convenience of making, sharing and archiving pictures by means of digital cameras. CMOS image sensors, which are conventionally found in consumer electronics, are also gradually being applied as a means to introduce digital work flows in high-end fields, such as medicine, space, etc. However, medical/space applications introduce a new challenge to the design of CMOS image sensors: harsh radiation environments. Visible light, which is a fundamental type of electromagnetic radiation for image sensors, has no major impact on the reliability of performance of the imager. However, in medical applications, other types of electromagnetic radiation, such as X-ray radiation, do have undesired effects on the image quality. The same is true for some other radiation sources in space. Consequently, this thesis studies the effects of radiation on CMOS image sensors during application and aims to design a radiation-hardened CMOS image sensor, strengthening the competitiveness of CMOS image sensors used in radiation environments so as to better promote digitalization in the relevant fields. 1.1 Development of Image Sensors and Photography

Generally speaking, photography is the practice of producing images by the action of light or another radiant energy on a light-sensitive material [1.1]. Therefore, to some extent, the development of a light-sensitive material determines the progress which photography can make. With the advances in photographic film, image quality has achieved great improvement. The invention of solid-state image sensors took photography into a new era starting in the 1960s [1.2]. The electronic recording and storing of images has marked an enormous change and boost in photography, as compared with traditional photographic film, which also meets the needs of an information age. In order to provide an overview of how image sensors are currently applied in photography, this section presents a brief introduction to the development of solid-state image sensors and photography.

1.1.1 Early History of Photography and Cameras

Nicéphore Niépce in 1822 by the single action of light on a glass plate coated with bitumen. This image became damaged later on when Niépce attempted to reproduce it. Nevertheless, in 1826, Niépce produced the first known permanent photograph on a polished pewter plate covered with bitumen. The picture quality was so poor that it was difficult to identify the objects. Moreover, the exposure lasted eight hours.

Niépce formed a partnership with Louis Daguerre to improve the photography process. In 1839 Daguerre announced that he had developed an effective and convenient method for photography by using silver on a copper plate, which is called a daguerreotype. The daguerreotype not only greatly reduced the exposure time to thirty minutes from the previous eight hours, but also showed a clearer image than ever before.

Daguerreotypes were difficult to reproduce and the photographic plates were fragile. In 1841, the calotype process was invented by Fox Talbot using paper coated with silver iodide, which was able to overcome the drawbacks of daguerreotypes. The calotype paper only needed to be exposed for a minute or two for an intermediate negative image to form on it. The translucent negative image on the calotype paper could be used to make additional multiple positive prints by contact printing, which is similar to the working principle of today’s photography films.

With the invention of wet plate collodion photography in 1851 by Frederick Scott Archer, the negative process was able to produce high-quality, detailed prints. Furthermore, the ease of reproduction continued to increase, which made photography much less expensive.

After a series of advances in refining the photographic process, a revolutionary improvement ultimately came about when George Eastman invented rolled photography film in 1884 [1.3]. The emergence of roll film made way for a true modern camera without the need to carry all the aforementioned photographic plates and chemicals. In 1888, George Eastman introduced the world’s first camera designed for roll film, the KODAK camera, to the market. Another milestone was reached in 1900 when the first of the famous BROWNIE cameras became a fixture of the mass market. Ever since, virtually anyone could take photographs without having to understand the complex photographic process [1.3].

1.1.2 CMOS Image Sensors: Past, Present and Future

Traditional cameras using photographic film continued evolving after 1900 in terms of the lens, exposure modes, optical viewer, etc. The camera stepped into an entirely new era with the digital camera age when photographic film was replaced with a solid-state image sensor. From that point on, it has been possible to store images electronically. This section presents an introduction to image sensors and their past, present and future, with a focus on CMOS image sensors.

electronic signals which utilize the photoelectric effect. Light, as a form of electromagnetic radiation, has a feature of wave-particle duality. The light-quantum theory proposed by Einstein in 1905 is an important theory basis for the particle feature of light as well as the photoelectric effect of semiconductor materials [1.4].

Complementary metal-oxide semiconductor (CMOS) image sensors and charge coupled device (CCD) sensors are the two main types of image sensors on the market. For a long time CCD sensors had the edge over CMOS image sensors in terms of high-quality imaging and market share. George Smith and Willard Boyle invented the first charge coupled devices (CCDs) at Bell Labs in 1970 [1.5]. Subsequent to developments in the aerospace industry in the 1970s, the first CCD was applied in the field of astronomy to replace the cosmic-ray-sensitive photographic film which was equipped in the space vehicles. However, the commercial success of CCDs began in the 1980s, which was driven by the camcorder market. In 1981, Sony released the first Sony Mavica camera, which was a video camera that adopted a CCD sensor [1.6]. Although the early Sony Mavica was not a true digital camera in consideration of its analog video output in the NTSC (National Television System Committee) format, it marked the beginning of the digital camera revolution. From then on CCDs gradually took over the field of imaging. Because of its superior image quality and sensitivity, CCDs even nowadays continue to find acceptance in high-end digital photography and military application.

Even though CCDs overwhelmed CMOS image sensors in terms of market share for a long time due to their high-quality image, MOS-technology-based image sensors had in fact appeared earlier than CCDs. The development of MOS-based image sensors was just abandoned later until the 1990s. The invention of the first transistor in 1947 initiated the development of electronic components using solid-state materials instead of vacuum tubes [1.7]. Image sensors were firstly developed with MOS technology despite the technology limitation of that day also hindering the progress of MOS image sensors.

In 1967, Weckler proposed the operation of charge integration on a photon-sensing p-n junction [1.8]. This charge integration technology is still being utilized in the current CMOS image sensors, so Weckler’s invention can be recognized as a CMOS image sensor prototype to some extent. In the same year, 1967, Weimer et al. presented a self-scanned solid-state image sensor with a 180x180 element array fabricated with thin-film technology [1.2]. Shortly thereafter, Weckler together with Dyck proposed an image sensor with a photodiode array in the passive pixel structure in 1968 [1.9]. It was also in 1968 that the work of Noble pushed the development of the MOS image sensor one big step forward. In Noble’s image sensor, the in-pixel source-follower buffer and charge-integrating amplifier were integrated on-chip [1.10], which laid a solid foundation for the development of modern CMOS image sensors. However, even in the late 1960s, process technology had not yet advanced far enough that the

transistors suffered from variation in threshold voltage and instability of their on-resistance. Accordingly, the high non-uniformity of the devices in the photon-sensing array resulted in a large fixed pattern noise (FPN). The early development of MOS image sensors in the 1960s was thus impeded because of the excess of noise and poor quality of the image. The appearance of the CCD sensors in 1970 and the success of its performance in digital imaging made matters worse for MOS image sensors. The development of MOS image sensors remained stagnant from the late 1960s until the early 1990s.

Since the 1990s, CMOS technology has progressed a great deal and has become reliable enough to meet the demands of the microprocessor and the logic units. The advantages offered by CMOS technology, such as low power, high integration capability and low cost, opened the door to a second surge in CMOS image sensor development. Additionally, the camera phone market became a strong driving force for CMOS image sensor development in the later 1990s and 2000s.

In 1993, Eric Fossum et al. from JPL developed the first CMOS active pixel image sensor [1.11]. The sensor fabrication adopted the widely available standard CMOS process of that time. Correlated double sampling (CDS) was performed to lower the readout noise. The technique of in-column FPN reduction was also introduced, which greatly improved the noise performance of the sensor. These also laid the foundation for almost all modern CMOS image sensors.

The first high-performance photodiode-type CMOS image sensor, which was described by JPL in 1995, could achieve a 72dB dynamic range and a 116μV rms noise level [1.12]. As compared with the previous versions, this sensor included on-chip timing and digital control circuitry, which initiated the trend toward the development of the camera-on-a-chip digital imaging with CMOS technology. Also in 1995, the pinned photodiode was first applied to the active pixel sensor using CMOS/CCD process technology in a JPL/Kodak collaboration [1.13]. This work also demonstrated the push to overcome the dark current problem faced by CMOS image sensors.

With the numerous improvements in CMOS technology, CMOS image sensors have achieved a great deal of progress in imaging performance. Thus, the gap has been dramatically narrowed between CCDs and CMOS image sensors in terms of image quality, especially over the last few years. Additionally, the advantages of CMOS image sensors in camera-on-a-chip imaging systems, namely fabrication costs and power consumption, are at a premium for the current consumer market. Besides the conventional camera phone market, market demand has grown for application in mobile computing, tablets and even emerging automotive technologies in recent years. Due to the high readout speed, CMOS image sensors are a force nowadays in the market of high-speed videography. As of 2012, a CMOS image sensor output can reach a readout speed of up to 12500 frames per second (fps) with a resolution of 1024×1024 pixels and higher frame rates at a reduced resolution [1.14]. As for sensor resolution, with the rapid scaling of CMOS technology, the pixel pitch has shrunk significantly over the last few years

so that the sensor resolution has increased dramatically within the same chip area. In 2010, Canon announced the first APS-H-size CMOS image sensor with a record-high resolution of 120 megapixels [1.15]. The resolution of the traditional roll film corresponds to 100 megapixels. Thus, in recent years the development of CMOS image sensors has surpassed its main opponent, CCDs, and even roll film cameras. In terms of the market, CMOS image sensors are pushing CCDs out of the picture. Figure 1-1 illustrates the development and performance of both CMOS image sensors and CCD image sensors over time. From the 1990s, the performance of CMOS image sensors developed much faster than CCDs. Moreover, Figure 1-2 shows the recent imaging sensor market share and a forecast for the future.

Figure 1-1. Development and performance of CMOS image sensors and CCDs over time.

2010 2011 2012 2013 2014 2015 0 20 40 60 80 100 Im ag e Sen so r M ar ket S har e ( % ) Year CCD Image Sensor CMOS Image Sensor

Prediction

Figure 1-2. Image sensor market share in recent years and in the future.

Since the current image quality of CCDs is still superior to that of CMOS image sensors, the future development of CMOS image sensors will still aim to improve the image quality further with emerging technologies. In the meantime, the pixel

pitch will continue to shrink and step into a sub-1µm era in order to increase sensor resolution and/or lower cost. The high integration capability of CMOS technology also provides more possibilities to develop smart image sensors.

However, as the pixel becomes smaller, the sensor performance degrades in terms of sensitivity. Image capturing in low-light conditions has always been a hurdle for CMOS image sensors. Fortunately, the challenges faced by CMOS image sensors are continuously being overcome by technological progress. The third generation of Aptina A-Pix technology enables mobile phone cameras to capture quality images even in low-light conditions by enhancing quantum efficiency and minimizing crosstalk. The A-Pix technology features front-side illumination (FSI) with light-guides and deep photodiodes [1.16]. In contrast to FSI, back-side illumination (BSI) CMOS image sensors, which were first developed by Sony commercially in 2008, is another technology that enhances image quality by improving sensitivity [1.17]. The BSI technology could meet the ongoing requirements for miniaturizing pixel size and improving overall image quality. In 2012, Aptina announced the planned mass production of a fast BSI sensor based on their A-PixHS technology, which is a technology that combines the BSI pixel with an advanced high-speed pixel and sensor architecture [1.16]. Based on the advances made with the present CMOS technology, Sony has recently announced their plan to distribute a sample of a next-generation stacked BSI CMOS image sensor [1.18]. The stacked BSI sensor will place the BSI pixel array on top of a signal processing chip. This technology can further reduce the size of the image sensor chip, and the large-scale signal processing chip allows for better chip functionality and higher image quality. Generally speaking, CMOS image sensors continue to drive the evolution of digital imaging in terms of image quality and functionalities with the help of advances in CMOS technology.

1.2 CMOS Image Sensors in Radiation Environments

Soon after they were invented, solid-state image sensors were deployed in radiation environments for space applications [1.19] and medical applications [1.20]. As described in the previous sub-section, many applications in radiation-harsh environments previously relied mainly on CCD sensors. However, with the improvement of CMOS image sensor’s performance in electro-optics, such as dark current, quantum efficiency, resolution, and modulation transfer function (MTF), CMOS image sensors are nowadays a strong, competitive alternative to application in radiation environments. Moreover, CMOS image sensors also offer superior advantages with respect to system complexity and functionality and are inherently resistant to radiation damage compared to CCD counterparts. However, it is the application in radiation environments that has led to the radiation study on CMOS image sensor degradation caused by total ionizing dose effects and displacement damage.

1.2.1 Space Application of CMOS Image Sensors

Increasingly more CMOS image sensors can be found in orbit. Cypress’ HAS2 image sensor was implemented on a star tracker and is now in space on the Proba-2 satellite [1.21]. The STAR-250, also from Cypress, is being used on a digital sun sensor developed by TNO of the Netherlands [1.21]. CMOS image sensors are playing a growing role in space applications due to the inherent advantages offered by CMOS technology.

CMOS image sensors feature low power consumption, which is tens of mW compared to hundreds of mW for a CCD with an equivalent format [1.22]. Considering the limited amount of power supplied by the solar system to the whole space vehicle, the low-power CMOS image sensor is a very attractive option.

Additionally, CMOS image sensors allow the programmable timing control functions and signal processing circuits to be integrated on-chip. As compared to the charge-transfer mechanism and power-consuming off-chip signal processing in CCDs, the data readout of CMOS image sensors is more flexible so that the access to sub-windows and individual pixels becomes fast and simple. Consequently, CMOS image sensors are popular for use in star trackers, where randomly reading multiple sub-windows is needed to track a number of targets simultaneously [1.23].

Regarding the advantages of CCDs in quantum efficiency, fill factor and resolution for space remote sensing, CMOS technology can provide a hybridization approach to optimize, respectively, the photon-sensitive pixel array and processing circuits. Backside thinning can highly improve the quantum efficiency of CMOS image sensors [1.24], which makes it feasible to replace CCDs for hyperspectral imaging. The integrated processing circuits in the architecture of CMOS image sensors allow for low noise, large full-well capacitance, high readout speed and readout of the spectral line of interest. What is worth mentioning is that there is no frame shift smear for CMOS image sensors, which is useful for hyperspectral imaging application. However, smear is always a problem for CCDs in space as it degrades the image quality. The demand is to avoid the problems faced by CCDs while achieving or even surpassing CCD-like performance in space application. Thus, there is also a great deal of motivation to deploy high-end CMOS image sensors in the field of hyperspectral earth observation and remote sensing [1.25].

1.2.2 Medical Application of CMOS Image Sensors

The innovation of digital radiography has revolutionized medical X-ray imaging by replacing conventional film radiography and analog video imaging techniques with a digital workflow. Digital X-ray imaging can greatly raise the operation efficiency. Once the image is digital, it can be accessed not only in real-time but

also simultaneously in multiple locations with the help of modern digital communication technology. It also makes result sharing and remote peer review simpler and more efficient. Digital images are more convenient to archive than film, and can be easily used to set an electronic record. Advanced digital processing of digital images can even provide computer-aided diagnoses. In addition, digital radiography technologies reduce the dose utilization while significantly improving the image quality.

Digital X-ray technology includes computed radiography (CR), image intensified CCDs (II-CCDs) and flat panel detectors (Direct and Indirect Detection). Detective quantum efficiency (DQE) and the modulation transfer factor (MTF) are usually used to compare the imaging system performance of different digital radiography technologies. In terms of DQE and MTF, CR shows a poor performance. Furthermore, CR uses a separate scanning operation to read the information in digital format from the phosphor imaging plates and therefore cannot be used for real-time X-ray imaging. Thus, flat panel detectors and II-CCDs are the main forms of digital radiography in wide use. State-of-art digital radiography uses the flat panel detector. Flat panel detectors have significant advantages over the image-intensified CCDs in terms of physical size and weight. The II-CCD is bulky and large due to its optical system. Moreover, the flat panel detector can usually provide a smaller detector pitch and a larger field of view (FOV), which is suitable for dentomaxillofacial imaging [1.26]. Considering image quality, the X-ray image generated by the image intensifier has geometrical distortion and veiling glare because the signal conversion in an II-CCD undergoes many stages and may suffer from distortion in between. However, a flat panel detector generates neither distortion nor veiling glare [1.26]. Due to the on-chip electronics integration, the flat panel detector also makes it possible to access regions-of-interest by simply addressing certain columns and rows. Therefore, flat panel detectors are nowadays becoming increasingly popular in digital X-ray imaging applications because of the aforementioned advantages.

Depending on the X-ray conversion methodology, a flat panel detector can be classified as either direct or indirect. The flat direct X-ray imager converts X-rays directly into electrons for image capturing, making use of conversion materials, like amorphous selenium (a-Se). Selenium is a material that suffers from instability over time and temperature, and has image lag. Consequently, the flat direct X-ray imager is not suitable for real-time imaging application. Thus, the modern flat panel detector mainly relies on indirect X-ray imaging, where the scintillator first converts X-rays into visible light and then either an amorphous silicon thin-film-transistor (TFT) panel or a CMOS image sensor captures the light in order to generate digital image [1.27].

Table 1-1. Parameter comparison between a CMOS X-ray imager and an amorphous silicon TFT X-ray imager [1.28].

CMOS X-Ray Imager Amorphous Silicon TFT X-Ray Imager

Readout Noise Low High

Readout Speed High Low

Image Lag Almost Absent Serious

Fill Factor High High

DQE High Low

On-Chip Integration Yes No

The flat panel indirect X-ray imager is usually on the same scale with the object because X-rays cannot be easily focused. Since amorphous silicon TFT arrays can be fabricated in a large area and at a low cost, the TFT arrays were favored by the previously used flat panel indirect X-ray imager. However, a large-scale CMOS X-ray imager is available nowadays as well with the CMOS stitching technology. In fact, CMOS X-ray imagers have become increasingly popular in the field of flat panel X-ray imagers due to their inherent advantages over flat panel TFT detectors [1.29]. Table.1-1 shows a performance comparison between CMOS X-ray imagers and amorphous silicon TFT X-ray imagers.

Present-day CMOS X-ray imagers can provide improved image quality with a dose reduction, and thus they have become prevalent in the field of medical imaging. Moreover, the capability of CMOS X-ray imagers in real-time imaging broadens their application in dynamic imaging, like dental panoramic X-rays, surgery, etc.

However, the CMOS X-ray imager is prone to X-ray damage during the application even though the on-chip periphery electronics can be shielded and protected by a thick metal layer. The X-ray-induced radiation effects can consequently degrade the image quality and lead to failure of the entire imager over time. Therefore, a study of the radiation effects on CMOS image sensors must first be conducted to show that a radiation-hardened CMOS image sensor can be implemented for demanding medical applications.

1.3 Basics of Radiation Sources and Damage

As discussed in the previous section, the application of CMOS image sensors in a radiation-harsh environment is becoming popular even though the radiation can induce some undesirable effects on the imager performance. Thus, it is necessary to become acquainted with the radiation environment in space and in medicine. This section presents a brief introduction to the sources of radiation and types of radiation damage which CMOS image sensors suffer from during their application. When CMOS image sensors are applied in space, a variety of radiation sources are encountered, which mainly consist of energetic particles. These energetic

particles include neutrons, photons, electrons, protons, ions, etc., which vary in origin, energy and flux. They can be categorized into three groups based on origin: trapped radiation, solar flares, and cosmic rays [1.30].

1) Trapped Radiation

Although the universe is a radiation-harsh environment, the atmosphere protects the earth from radiation damage by absorbing and reflecting a large fraction of radiation. The charged particles are trapped in the magnetosphere, forming a radiation belt also called the Van Allen belt. The earth has two radiation belts: the inner radiation belt and the outer radiation belt, which are composed of different constituents. The inner radiation belt extends from an altitude of 1.2 to 3 earth radii (RE) above the equator and its center is located around 1.5 earth radii. This belt is mainly composed of protons of energies in the 10-100 MeV range [1.30], but there are also small populations of other particles, like electrons, heavy ions, and oxygen ions, with energies of 1-100keV. The outer radiation belt extends from 3 to 10 earth radii above the earth’s surface and its center is around 4-5 earth radii. The main constituent within this belt is an electron with energy around 1MeV, while there are also a small number of protons, alpha particles and heavy ions.

2) Solar Flares

Solar flares take place when accumulated magnetic energy in the solar atmosphere is suddenly released, which is the largest type of explosion in the solar system. When the magnetic energy is released, protons and electrons of energy above 1MeV are emitted. Furthermore, the other radiation sources, such as radio waves, X-rays and gamma rays, are also emitted across almost the entire electromagnetic spectrum [1.30]. The intense radiation from solar flares is dangerous to electronic instruments in space, including CMOS image sensors.

3) Cosmic Rays

A cosmic ray is a type of high-energy radiation that impacts the earth. Cosmic radiation comes from outer space and it intensifies as the altitude increases. Galactic cosmic rays, solar cosmic rays and terrestrial cosmic rays are the three main types of cosmic rays. Galactic cosmic rays originate from a galaxy outside the solar system and consist of about 85% protons, 14% alpha particles and 1% heavier nuclei with a high energy up to GeV range [1.30]. Solar cosmic rays, which come from the sun, are mainly comprised of protons of energy up to 1MeV. Galactic and solar cosmic rays that penetrate the atmosphere after a collision generate secondary radiation. These bursts of secondary radiation are terrestrial cosmic rays that can reach the earth’s surface. The terrestrial cosmic rays mainly consist of protons, electrons, neutrons, pions and muons with energy ranging into MeV [1.31].

medical imaging purposes, X-rays are the main radiation source. The different densities and composition of various materials of an object allow the penetration of different proportions of X-rays. The varying amount of X-ray radiation that passes through can then form an image on the digital detector in grayscale levels for diagnostic use.

X-rays are a form of electromagnetic radiation that is emitted by bombarding a metal target with accelerated electrons. X-rays have a wavelength ranging from 0.01nm to 10nm and energies in the range of 100eV to 100keV. X-rays with energies up to 10keV are defined as soft X-rays, which can hardly penetrate the substance. X-rays with energies from 10keV to greater than 100keV are called hard X-rays. Hard X-rays can penetrate solids and liquids, hence their use in medical imaging.

In fact, X-ray imaging is also used for industrial radiography in order to inspect industrial products, following the same principle used in medical imaging. Additionally, airport security and border control deploy digital X-ray imaging as well to inspect the interior of objects.

Another type of electromagnetic radiation, gamma rays, the energies of which are greater than X-rays, are another possible radiation source during the application of CMOS image sensors in medicine and industry.

Thus, the aforementioned radiation sources which CMOS image sensors may encounter comprise of X-rays, gamma rays, protons, electrons, heavy ions, neutrons. In general, these can be mainly classified into photons and charged particles. Photons are electromagnetic radiation which is electrically neutral. With the increase in energies carried by different types of photons, the energy loss mechanism resulting from the interactions between photons and matter varies from the photoelectric effect and Compton scattering to pair production. As for charged particles, the interaction with matter mainly occurs with Coulomb scattering, which loses energy via the ionization and excitation of atoms. In addition, the primary interaction between highly energetic particles and matter can result in secondary electromagnetic radiation [1.32].

Despite the different radiation interaction mechanisms, the radiation effects on CMOS image sensors induced by different radiation sources can be mainly reduced to cumulative effects and single event effects. The cumulative effects can be further divided into total ionizing dose effects (TID) and displacement damages. Figure 1-3 shows a diagram of the classification of radiation effects on electronic instruments, including CMOS image sensors. Cumulative effects gradually degrade electronic device performance and ultimately cause them to fail until the accumulated total ionizing dose or displacement damage reaches the critical value that the device can tolerate. However, what describes the failure induced by the energy deposition coming from one single particle is a single event effect, which is transient and can happen at any moment. A TID is a measure of the ionizing energy deposition in silicon oxide and silicon in terms of the build-up of trapped charge and defects. Details about total ionizing dose effects are further discussed in the following chapter. The unit to measure the TID can be either rad or Gray (Gy). The equivalent relationship between two units is given as: 1Gy = 100rad. Since rad has been popularly adopted by the electronics community, the total ionizing dose in this thesis is expressed in terms of rad. Even though the displacement damage occurs during the entire process when the device is irradiated, which is the same with TID effects, the displacement damage is measured by its effects on the electronics. It is provided by the particle fluence and expressed in particles/cm2.

A single particle, e.g. a heavy ion or highly energetic proton, can create electron-hole pairs along its incidence track in the silicon, which can induce localized radiation effects in terms of single event effects. The generated electron-hole pairs recombine in the bulk silicon, but they can be separated and collected to form a current spike in a depletion region. These collected charges may induce a change-of-state at a sensitive node of a circuit, known as a single event upset, which is a soft error that causes no permanent damage. However, the generated charges introduced by a single particle can also result in the latch up of the parasitic n-p-n and p-n-p bipolar transistors in the bulk CMOS, which can cause hard errors and permanent damage [1.32].

In this thesis, X-rays are the main radiation source used for CMOS image sensor measurements in medical applications. Therefore, the total ionizing dose effects, known as cumulative effects, are studied. In fact, the knowledge attained from TID effects can also be beneficial for the study of CMOS image sensors in space because there X-rays and gamma rays are also emitted in space.

1.4 Motivation and Objectives

As discussed in the sections above, CMOS image sensors have some superior advantages over CCDs which have consequently made them an alternative for X-ray imaging and space-borne imaging in radiation environments, achieving a comparable performance as CCDs. Particularly, the introduction of a 4-Transistor

(4T) CMOS image sensor with a pinned photodiode has largely improved the CMOS imaging quality in terms of dark current and noise [1.33]. Nevertheless, CMOS image sensors are vulnerable and sensitive to radiation damage. This is because the signals that CMOS image sensors are usually required to detect can be as low as in the pico-ampere range while the radiation damage can worsen the detectability by raising the sensor offset level. Consequently, the study of radiation effects on CMOS image sensors began after their application in radiation environments.

There have been many studies carried out on the effects of radiation on both CMOS devices [1.30][1.32] and 3-Transistor (3T) CMOS image sensors [1.34][1.35][1.36]. However, this thesis aims to present a comprehensive study on the radiation effects on the electro-optical performance of 4T CMOS image sensors fabricated in a commercial 0.18μm technology, since very little research has been conducted on this topic. Only X-ray ionizing radiation is studied with respect to the promising application of 4T CMOS imagers in medicine.

This work covers not only a macroscopic radiation study on in-pixel test devices and pixel arrays, but also a study on the microscopic degradation mechanism. The radiation effects are to some extent dependent on the process technology. With the progress and scaling of CMOS technology, previous knowledge about radiation effects that are based on old technologies cannot be directly transposed to present CMOS image sensor (CIS) technologies. Particularly for technology scaling, a large variety of device parameters are induced, such as gate oxide thickness and junction capacitance, which are also sensitive to radiation. Thus, the radiation study on the current 0.18μm in-pixel test devices can help to update the list of elementary radiation effects of this technology. Furthermore, the pinned photodiode (PPD) and transfer-gate (TG) employed in the 4T pixel dramatically reduce the pixel dark current and noise compared to a 3T pixel. They may also cause the radiation-induced pixel degradation mechanism to differ from that of a 3T pixel. In addition, the macroscopic pixel parameter degradation is usually used as a tool to evaluate the radiation effects. This thesis therefore aims to look into microscopic pixel degradation mechanisms induced by X-rays. The ionizing radiation-induced charge and defect build-up in CMOS image sensors is subject to the electrical bias condition on the power supply node. What is presented in this work is the bias-dependent effect on the radiation degradation of 4T CMOS image sensors, since few such studies have been carried out on CIS devices before.

This thesis work is highly motivated by the aforementioned goals and challenges, and it ultimately aims to devote a detailed study of radiation-induced degradation effects on 4T CMOS image sensors applied in radiation environments and furthermore to design a radiation-hardened CMOS image sensor.

Therefore, the primary objective of this work is to study the radiation-induced degradation effects on each element of the 4T pixel and on different sensor characteristics. The test structures used in this study rang from in-pixel MOSFETs and pixel arrays to the entire sensor. In the meantime, both electrical performance

and optical performance of 4T pixels are investigated. The main degradation nodes of a 4T pixel after radiation are also identified, since the similar knowledge obtained from the 3T pixel is no longer applicable.

After obtaining insights into the radiation-induced problems and degradation mechanisms, the following objective is to establish radiation-hardening-by-design (RHBD) techniques to protect the sensor from radiation damage, especially at the pixel-weak nodes. These physical design techniques, which are determined by the pixel design parameters in a particular technology, should be also compatible with other CIS technologies.

Last but not least, the final objective is to apply those hardening-by-design techniques to a radiation-hardened 4T CMOS image sensor design for verification. Further screening by relative comparison can achieve more effective techniques. Since the radiation-hardened 4T CMOS image sensors in this work are fabricated in a commercial 0.18µm CIS technology, the custom hardening-by-design should strictly obey the design rules issued by the foundry. Thus, on the basis of the design rules, the combination of different radiation-hardening-by-design techniques aim to achieve the highest radiation tolerance to ionizing radiation for a 4T pixel.

1.5 Thesis Structure

This section outlines the thesis structure and provides an overview of each chapter. The thesis is comprised of six chapters.

Chapter 2 presents not only a primary overview of 4T CMOS image sensors in terms of device characteristics and physics but also the applicable fundamentals of radiation effects on MOS devices, including 4T pixels. It first introduces the basic architecture of CMOS image sensors and different pixel structures with a focus on the pinned photodiode 4T pixel. Different electro-optical parameters of the 4T pixel are discussed in the subsequent sections of the chapter. The dark current generation mechanisms in the pixel are addressed in detail, which leads to a brief description of the spatial distribution of dark current sources in the 4T pixel. Finally, Chapter 2 also provides a comprehensive introduction to the total ionizing dose effects on MOS devices and 4T pixels, covering charge and defect build-up, radiation damage recovery, and radiation-hardened technology.

Chapter 3 discusses the measurement results regarding the radiation-induced degradation on the electrical and optical performance of different devices that comprise CMOS image sensors. The effect of ionizing radiation on in-pixel MOSFETs is demonstrated in terms of an increase in leakage current. Different designs of MOSFETs are used to illustrate the radiation-tolerance options in order to realize a radiation-hardened design. The main pre-radiation and post-radiation dark current sources in the 4T pixel are identified in Chapter 3. The variation of pixel geometrical and electrical parameters has an effect on the radiation degradation, which is also discussed in Chapter 3. In addition, Chapter 3 presents

the degradation of the sensor optical characteristics due to X-rays.

The dark current increase is the most common tool used to evaluate the radiation effects from a macroscopic viewpoint. Chapter 4 proposes an interesting study on the microscopic degradation mechanism behind the macro dark current increase caused by radiation, in terms of the generation of micro trap. Moreover, the effect of bias conditions on radiation-induced pixel degradation is also evaluated in Chapter 4 through experiments.

Chapter 5 demonstrates a radiation-hardened 4T CMOS image sensor to verify the effectiveness of the radiation-hardening-by-design techniques which are obtained from the study of radiation degradation mechanisms in Chapter 3. The radiation-hardened pixel shows an obvious improvement in the post-radiation dark signal increase compared with the reference pixel. Pixel arrays with different design techniques provide the possibility to investigate further the radiation effects on radiation-hardened designs. In the meantime, a trade-off of the radiation-hardened pixel is also presented in Chapter 5 in terms of degradation decrease in the pixel spectral response.

In Chapter 6, the main thesis achievements are summarized. In addition, some suggestions and guidelines are given for future studies on the effect of radiation on CMOS image sensors as well as further improvements in the design of radiation-hardened 4T CMOS image sensors.

1.6 References

[1.1] http://www.merriam-webster.com/dictionary/photography

[1.2] P. K. Weimer et. al. “A self-scanned solid-state image sensor,” Proc. IEEE, vol. 55, no. 9, pp. 1591-1602, 1967.

[1.3] http://www.kodak.com/ek/US/en/Our_Company/History_of_Kodak/Imagi ng-_the_basics.htm

[1.4] A. Einstein, “Über einen die Erzeugung und Verwandlung des Lichtes betreffenden heuristischen Gesichtspunkt,” Annalen der Physik 17 (6), pp. 132-148, 1905.

[1.5] W. S. Boyle and G. E. Smith, “Charge coupled semiconductor devices,”

Bell System Technical Journal, vol. 49, pp. 587-593, 1970.

[1.6] http://www.sony.net/SonyInfo/CorporateInfo/History/sonyhistory-g.html [1.7] http://www.nobelprize.org/nobel_prizes/physics/laureates/1956/shockley-b

io.html

[1.8] G. P. Weckler, “Operation of p-n junction photodetectors in a photon flux integrating mode,” IEEE Journal of Solid-State Circuits, vol. 2, no. 3, pp. 65-73, 1967.

[1.9] R. Dyck and G. Weckler, “Integrated arrays of silicon photodetectors for image sensing,” IEEE Trans. Electron Devices, vol. ED-15, pp. 196-201, 1968.

[1.10] P. Noble, “Self-scanned silicon image detector arrays,” IEEE Trans.

Electron Devices, vol. ED-15, pp. 202-209, 1968.

[1.11] S. Mendis, S. Kemeny and E. R. Fossum, “A 128×128 CMOS active pixel image sensor for highly integrated imaging systems,” IEEE IEDM Tech.

Dig., pp. 583-586, 1993.

[1.12] R. H. Nixon, S.E. Kemeny, C. O. Staller and E. R. Fossum, “128×128 CMOS photodiode-type active pixel sensor with on-chip timing, control and signal chain electronics,” Charge-Coupled Devices and Solid-State

Optical Sensors V, Proc. SPIE, vol. 2415, pp. 117-123, 1995.

[1.13] P. K. Lee, R. C. Gee, R. Guidash, T-H. Lee and E. R. Fossum, “An active pixel sensor fabricated using CMOS/CCD process technology,” IEEE

Workshop on CCDs and Adv. Image Sensors, pp. 115-119, 1995.

[1.14] http://www.photron.com/index.php?cmd=whatsnew&id=21#21 [1.15] http://www.canon.com/news/2010/aug24e.html [1.16] http://www.aptina.com/products/technology/aptina_a-pix.jsp [1.17] http://www.sony.net/SonyInfo/News/Press/200806/08-069E/index.html [1.18] http://www.sony.net/Products/SC-HP/cx_news/vol68/pdf/sideview_vol68. pdf

[1.19] C. H. Sequin, “Image recording using charge-coupled devices,” NASA

SP-338, pp. 51-68, 1972.

[1.20] M. Hoheisel “Review of medical imaging with emphasis on X-ray detectors”, Nucl. Instr. Meth. Phys. Res. A, vol. 563, pp. 215-224, 2006. [1.21] http://investors.cypress.com/releasedetail.cfm?ReleaseID=429709

[1.22] E. R. Fossum, “CMOS image sensors: electronic camera-on-a-chip,” IEEE

Trans. Electron Devices, vol. 44, pp. 1689-1698, 1997.

[1.23] F. Larnaudie et al., “Development of 750×750 pixel CMOS image sensors for tracking applications,” 5th International Conference on Space Optics, pp. 809-816, 2004.

[1.24] J. Janesick, “Charge coupled CMOS and hybrid detector arrays,” Proc.

SPIE, vol. 5167, pp. 1-18, 2003.

[1.25] J. Bogaerts et al., “Radiometric performance enhancement of hybrid and monolithic backside illuminated CMOS APS for space-borne imaging,”

International Image Sensor Workshop, pp. 151-154, 2007.

[1.26] R. Baba, K. Ueda and M. Okabe, “Using a flat-panel detector in high resolution cone beam CT for dental imaging,” Dentomaxillofacial

Radiology, vol. 33, pp. 285-290, 2004.

[1.27] R. Street, J. P. Lu and S. Ready, “New materials and processes for flat panel X-ray detectors,” IEE Proc.-Circuits Devices Syst., vol. 150, pp. 250-257, 2003.

[1.28] J. Bosiers, L. Korthout and I. Peters, “Medical X-ray imaging using wafer-scale CMOS imagers,” 6th Fraunhofer IMS Workshop on CMOS

[1.29] H. Jang et al., “Hole based CMOS active pixel sensor for medical X-ray imaging,” 2011 IEEE Nuclear Science Symposium Conference Record, N21-5, pp. 1060-1064, 2011.

[1.30] A. Holmes-Siedle and L. Adams, Handbook of Radiation Effects, Oxford University Press, New York, ISBN: 0198563477, pp. 16-45, 1993.

[1.31] J. F. Ziegler, “Terrestrial cosmic rays,” IBM Journal on Res. Develop, vol. 40, pp. 19-39, 1996.

[1.32] C. Claeys and E. Simoen, Radiation Effects in Advanced Semiconductor

Materials and Devices, Springer-Verlag, Berlin, ISBN: 3540433937, pp.

9-36, 2002.

[1.33] R. M. Guidash et al., “A 0.6µm CMOS pinned photodiode color imager technology,” IEEE IEDM Tech. Dig., pp. 927-929, 1997.

[1.34] J. Bogaerts, “Radiation-induced degradation effects in CMOS active pixel sensors and design of radiation-tolerant image sensor,” Ph.D. Thesis, ISBN 9056823388, 2002.

[1.35] V. Goiffon et al., “Total dose evaluation of deep submicron CMOS imaging technology through elementary device and pixel array behavior analysis,” IEEE Trans. Nucl. Sci., vol. 55, pp. 3494-3501, 2008.

[1.36] V. Goiffon et al., “Ionization versus displacement damage effects in proton irradiated CMOS sensor manufactured in deep submicron process,” Nucl.

Chapter 2

Device Characteristics and Radiation Effects of

4T CMOS Image Sensors

This chapter starts with a brief description of the advantages in terms of noise and dark current of the pinned photodiode 4-Transistor (4T) pixel over the other main pixel type, the 3-Transistor (3T) pixel. It also explicates the thesis motivation behind choosing the 4T pixel as a carrier for the study on the ionizing radiation effects. In order to analyze quantitatively the radiation-induced degradation of the 4T pixel, a comprehensive study on the 4T pixel performance parameters is provided as a basis from which the physical origins of the problem can be understood. Therefore, the different noise sources in the 4T pixel are briefly discussed ranging from spatial noise to temporal noise. In addition, the spectral characteristics of the 4T pixel together with the relevant measurements are also addressed in this chapter. Section 2.5 lays out the device physics for dark current generation in the 4T pixel, attributing the presence of traps at the Si-SiO2 interface as the main origin of the generation current (leakage current) in the 4T pixel. The ionizing radiation degradation, as an external cause of the increase in the pixel dark current, is carefully investigated in Section 2.6 with a discussion of the build-up mechanism of the trapped charges and interface traps. In the final section, a short introduction to the radiation-hardened techniques is presented in accordance with the ionizing radiation effects.

2.1 CMOS Image Sensor Pixels

Complementary Metal Oxide Semiconductor (CMOS) image sensors (CIS) can be mainly categorized into two groups: passive pixel sensors (PPS) and active pixel sensors (APS). The passive pixel structure is composed of a photodiode and one switching transistor. Since a large capacitive load is connected to each pixel during readout, the PPS suffers from, e.g., a high RC time constant, low readout speed and high pixel readout noise [2.1][2.2]. To compensate for the recognized drawbacks of the PPS, a pixel structure with an active amplifier (a source follower) within each pixel was proposed, which was called an active pixel sensor [2.3]. The reduced capacitance in an APS lowers the readout noise while increasing the dynamic range and the signal-to-noise ratio (SNR) as well.

Most state-of-art CMOS image sensors employ the active pixel structure. Fig. 2-1 shows the general architecture of an APS array and a schematic of a common pixel. The principal blocks within an APS array consist of a photon-sensing region, a column and row decoder, a sample-and-hold section and a readout amplifier.

Once the column and row decoder are active, a pixel is addressed. The selected pixel signal is buffered by the amplifier before being sent to the column bus. This signal is then sampled and later held in the sample-and-hold capacitor, which is connected to each column bus. Finally, the stored signal is removed from the chip by an output amplifier. With the help of a sample-and-hold circuit, the correlated double sampling (CDS) operation can be performed. CDS can effectively help to cancel the pixel reset noise, pixel fixed-pattern noise and flicker noise [2.4].

Photon Sensing Region Amplifier Column Bus Reset Select Selected Pixel

Active Pixel Array

Column Decoder Row De code r Capacitance GND Switch Vout Sample/Hold & CDS Circuit Buffer Output

Figure 2-1. Architecture of CMOS active pixel sensor (APS).

The pixel structures used in the APS mainly include a photo-gate pixel architecture and photodiode pixel architecture [2.5]. Initially, the most studied common pixel type is the traditional 3T pixel. The basic 3T APS pixel employs a photodiode, a reset transistor (RST), a source follower transistor (SF) and a row selector transistor (RS). Fig. 2-2 shows a schematic of a 3T pixel.

pixel area that is photon-sensitive is reduced. The pixel fill factor (the percentage of the light-sensitive area over the whole pixel region) is lowered compared to the simple passive pixel structure. Moreover, due to the random variation of the threshold voltage of the reset transistor and the source follower from one pixel to the other, a spatial offset is introduced which is known as fixed-pattern noise [2.6]. The operation of the 3T pixel consists of two main stages. The first stage is to charge the photodiode capacitor to a reset voltage through a reset transistor (RST). The second stage is to discharge the photodiode capacitor by integrating the photon-generated electrons during the exposure. The RST is turned off during light integration. Therefore, a bright pixel gives a low analog signal voltage while the dark pixel delivers a high analog signal voltage. Because the readout of all pixels cannot be operated in parallel, a row-by-row readout technique is applied to the 3T APS. The actual pixel readout sequence is as follows: first the photon-signal voltage after the exposure of the previous frame is read out, and then the pixel is reset, after that the reset voltage is read out [2.7].

Figure 2-2. 3T pixel schematic.

The signal voltage and the reset voltage are sequentially transferred to the sample-and-hold (S/H) capacitance in a CDS circuit. The signal level is then subtracted from the reset level during CDS operation. The main purpose of CDS is to eliminate the aforementioned fixed-pattern noise, the kTC noise of the photodiode capacitance, and the 1/f noise in the circuit by subtracting two correlated signals [2.4][2.8]. However, the double sampling in the 3T APS is not correlated. The two samples in fact come from two different frames. The sampling process operated in the 3T APS is then called delta double sampling (DDS). Fig. 2-3 shows the timing of the readout operation and the delta double sampling for a 3T pixel. Therefore, the kTC noise cannot be eliminated and becomes the major readout noise source, and the performance of the 3T pixel is consequently limited by the high temporal noise.

In 3T pixels, the photodiodes are composed of reverse-biased p-n junctions, as shown in the cross section of Fig. 2-2. The pixel dark current in the 3T pixel mainly originates from the thermal generation current and the diffusion current in the depletion region of the photodiode. The dark current density also depends on the scale of the contact area between the depletion region and the Si-SiO2 interface. Most of the 3T pixel photodiodes have depletion regions that are in contact with the SiO2 layer. Because the Si-SiO2 interface is not perfectly passivated due to the limitations of the technology, there are some interface states remaining. The surface generation current can be strengthened via these interface states when the surface depletion region is in contact with the SiO2 [2.9]. Therefore, the dark current performance of the 3T pixel faces a big obstacle: the large surface generation current from the photodiode.

Integration Time Sample after Integration Sample after Reset RS RST Output

Figure 2-3. Timing of the readout operation and delta double sampling in a 3T pixel. In order to address the main problems of 3T pixels i.e. the rather high temporal noise and the large photodiode dark current, the 4T pixel structure is introduced. A detailed discussion on 4T pixels will be presented in the following.

A pinned photodiode 4T pixel is a derivation of the 3T pixel that is able to overcome the aforementioned problems of 3T pixels. The pinned photodiode was initially invented to improve the image lag performance of interline CCD image sensors with an n+/p photodiode [2.10]. When later applied in CMOS image sensors, a low dark current performance was reported, which was comparable to that of CCDs [2.11][2.12]. Therefore, the study of the 4T pixel has become popular. Fig. 2-4 shows a schematic of a typical 4T pixel with a cross section of the pinned photodiode and the transfer gate transistor. The 4T consists of a reset transistor (RST), a source follower transistor (SF), a row selector transistor (RS), a transfer gate transistor (TG), a pinned photodiode (PPD) and a floating diffusion node (FD).

Vrst p+ n-well _p-epi p-sub Transfer Gate Floating Diffusion Node RS Vout RST Vdd SF

Figure 2-4. 4T pixel schematic.

Fig. 2-5 shows a SENTAURUS device simulation of the PPD, the TG and the RST [2.13]. There is a highly doped p implantation layer on top of the n/p-epi junction in the pinned photodiode. Hence, the photon collection area in a pinned photodiode consists of two depletion regions from the p+/n junction and n/p-epi junction. As shown in the simulation, the photon collection area in a pinned photodiode is dragged away from the surface because the p+/n junction forces its depletion region to move deeper into the silicon bulk. On the other hand, due to a geometric extension of the p+ layer over the n layer, the photodiode depletion region is prevented from having contact with the SiO2. As a result, the 4T pixel dark current with the pinned photodiode is largely reduced by inhibiting the photodiode surface generation current. The reported 4T pixel dark current is as low as that of CCD sensors [2.14][2.15].

The two depletion regions in the PPD, the p+/n junction and n/p-epi junction, eventually merge with each other and form back-to-back diodes by optimizing the photodiode doping profile. Hence, the PPD is fully depleted and is pinned at a certain voltage, called the pinning voltage [2.16]. The PPD reset level is then well determined by the pinning voltage when there are no electrons remaining in the diode. The performance of photodiode reset noise and image lag are also accordingly improved for the pinned photodiode 4T pixel. The reset noise from the FD capacitance in the 4T pixel can also be reduced, which is discussed later in this section. The readout sequence of a 4T pixel firstly starts with the integration of charges in the pinned photodiode during the exposure time. After the charge integration, the FD node first needs to be reset so that any remaining charges can be removed and the dark current can also be minimized. Right after resetting the FD, the charges are transferred to the FD node by switching on the TG gate. The CDS circuit is used to sample and hold not only the reset level of FD but also the resulting signal level after the charge transfer. The reset sample pulse and the signal sample pulse are operated within a very short time interval. Any reset noise included in these two samples is from the same frame and is therefore correlated. As a result, the reset noise from the FD node can be removed by subtracting the sampled reset level from the signal level through the CDS operation. Fig. 2-6 illustrates the timing of the readout operation and the correlated double sampling for a 4T pixel.

Figure 2-6. Timing of the readout operation and the correlated double sampling in a 4T pixel.

The temporal noise of the 4T pixel becomes rather low compared with the 3T pixel when the photodiode reset noise is absent due to the pinned photodiode working principle, and the FD reset noise is eliminated by a CDS operation. The 1/f noise from the in-pixel source follower becomes the dominant noise source in a 4T pixel. Aiming at lowering the 4T pixel noise further, efforts have been undertaken to study the implementation of an in-pixel buried-channel source follower together with digital correlated multiple sampling (CMS). The conclusion is that the 4T pixel is quite promising in harsh applications where a low noise performance is crucial [2.17].

With the introduction of the 4T pixel, CMOS image sensors have reached a new development stage, presenting low noise and low dark current, which are improvements on the main drawbacks of 3T pixels. Moreover, the 4T pixel quantum efficiency (QE) performance is also enhanced particularly in the shortwave length region because the upper p+/n junction in the pinned photodiode is very close to the Si-SiO2 interface so that it shows a good response to blue light.

However, the 4T pixel still has some trade-offs. Compared to the 3T pixel, the 4T pixel fill-factor is further lowered due to the extra transistor and increased number of controlling lines inside the pixel. Furthermore, the full well capacity of a PPD is limited by its own pinning voltage, which is usually smaller than that of a reverse-biased photodiode of equivalent size. The pinning voltage of the PPD needs a very well-optimized doping profile which is not always that easy to obtain with the current CMOS image sensor technology.

Nevertheless, the advantages of a 4T pixel still prevail over its drawbacks. Hence, numerous studies have been dedicated to the application of 4T pixels in the field of space remote sensing, medical imaging, etc. [2.18][2.19]. A detailed radiation study on the pinned photodiode 4T pixel is discussed in Chapter 3 and Chapter 4.

2.2 Noise Sources in Pinned Photodiode 4T Pixel

Noise dictates the minimum signal strength that a sensor can detect. Radiation is believed to increase the image sensor noise level [2.20]. Hence, noise is an important issue for CMOS image sensors when detecting low-level signals in a radiation environment. Noise in pinned photodiode CMOS image sensors can be mainly classified into two categories: spatial noise and temporal noise. The fixed-pattern noise (FPN) due to the non-uniformity of pixels and columns is referred as spatial noise, since it spatially varies from pixel to pixel or from column to column [2.6]. However, the noise in an individual pixel, such as reset or kTC noise, 1/f noise, thermal noise, or dark current shot noise, are temporal noise, which varies with time. There will be a brief introduction to the different noise characteristics of pinned photodiode CMOS image sensors in the following sections.

2.2.1 Fixed-Pattern Noise

Depending on the illumination condition, fixed-pattern noise consists of dark fixed-pattern noise and/or light fixed-pattern noise. Dark fixed-pattern noise originates from the non-uniformities on the dark current generation in each pixel, and the minor differences among in-pixel transistors. Hence, fixed-pattern noise creates a spatial noise pattern on the sensor. The in-pixel transistor parameter, such as the threshold voltage, may vary from one pixel to another due to the fabrication uniformity limitation [2.6]. In APS pixels, the in-pixel transistors usually refer to the source follower and the reset transistor. Because of the in-pixel transistor parameter mismatch, the pixel array has a pixel-level FPN. In 4T pixels, correlated double sampling (CDS) can make the pixel-level dark FPN negligible by sampling and subtracting two correlated pixel outputs, since the same pixel offset within two samples can be canceled through subtraction. Fixed-pattern noise under illumination is called light fixed-pattern noise, also known as photo-response non-uniformity (PRNU). Light FPN is proportional to the amount of illumination, and it mainly arises from the non-uniformities on the pixel photo-response. Nevertheless, light FPN is also influenced by the same problems as dark FPN, such as transistor parameter variations and pixel offset differences [2.21].

2.2.2 Temporal Noise

Compared to fixed-pattern noise, some types of temporal noise in the 4T pixel are more difficult to eliminate because of their inherent physical limitations. In this section, different temporal noise sources are discussed and the possible corresponding countermeasures for noise reduction are proposed.

(a) Reset or kTC Noise

Reset noise in CMOS image sensors, also known as kTC noise in analog circuits, is the uncertainty of the voltage on a capacitor right after that capacitor has been charged by turning off the reset transistor [2.22]. In the 4T pixel, depending on the gate-to-drain voltage (VGD) of the reset transistor, the reset operation can be a hard reset or soft reset [2.7]. When VGD is set lower than the threshold voltage of the reset transistor, a soft reset is implemented. During a soft reset, charges move in a unidirectional way between the FD node and the reset voltage node. Therefore, the reset noise expressed in an rms value for a soft reset can be given as [2.21]:

2 soft D kT Vres C  , (2-1) where Vressoft is the soft reset noise in voltage, k is Boltzmann’s constant, T

is absolute temperature, and CD is the diode capacitor. If the VGD is higher than the reset transistor threshold voltage, the FD node is hard reset. Charges move bidirectionally between the FD node and the reset voltage

node. Hence, the reset noise for a hard reset is increased by a factor of 2, which is given as [2.21]: _hard D kT Vres C  . (2-2) where Vreshard is the hard reset noise in voltage. However, the reset noise

reduction with a soft reset comes at the expense of image lag [2.23]. Moreover, according to Eq. (2-1) and Eq. (2-2), the reset noise can also be easily reduced by increasing the capacitor, CD. However, this benefit also

downgrades the conversion factor of the photon-sensing node. The conversion factor defines the efficiency of converting an electron to an electronic signal (voltage, current, digital number in case an ADC is used), and it is inversely proportional to the diode capacitance, the details of which will be addressed later in Section 2.3. Therefore, as mentioned above, correlated double sampling (CDS) in the 4T pixel is believed to be an efficient solution to eliminate the reset noise.

(b) Photon Shot Noise and Dark Current Shot Noise

The partition and absorption of an incident photon flux in the photodiode is a stochastic process so that the number of photons falling on a pixel and the resulting number of thermally generated electrons are random variables, following a Poisson distribution. Photon shot noise is the noise that describes this statistical variation of the number of incident photons and photon-generated electrons. The value of photon shot noise equals the square root of photon-generated electrons, complying with the Poisson distribution, which is given as [2.21]:

_p  N_p , (2-3) where p is the photon shot noise and Np represents the photon-generated

electrons.

The existence of photon shot noise in CMOS image sensors is unavoidable since it is due to the theoretical limit and the fundamental laws of physics [2.24]. Hence, the reduction of the photon shot noise cannot rely on the improvement of the pixel design and technology.

Contrary to the photon-induced electron-hole pair generation, even without light there are still a certain number of charges generated by thermal excitation flowing inside the image sensor, forming the so-called dark current [2.25]. Physically, the generation of electrons and holes in the depletion region of the sensor in the dark is a random process, which consequently induces a statistical variation of dark current. Thus, the noise originating from dark current, which is known as dark current shot noise, can also be modeled by the Poisson distribution, as is the case with photon shot noise. The value of the dark current shot noise is given as [2.21]:

_d  N_d , (2-4) where d is the dark current shot noise and Nd is the dark current expressed

in electrons. Dark current shows an exponential relationship with temperature [2.25], which is given below:

0exp( a) D E I D kT   , (2-5) where ID is the dark current in electron/sec, D0 is the pre-exponential

frequency factor, Ea is the activation energy, k is Boltzmann’s constant, and T is the absolute temperature. As shown in Eq. (2-5), lowering the temperature can greatly reduce the dark current, which as a result can minimize the dark current shot noise. In addition, the dark current shot noise can also be improved by suppressing the dark current itself with advances in pixel technology and layout design optimization [2.14].

(c) 1/f Noise

Another important noise source in 4T CMOS image sensors is 1/f noise, which is a kind of low frequency noise mainly coming from the in-pixel source follower. The 1/f noise voltage power can be expressed as:

1/ f OX K V C WLf   , (2-6) where V1/f is the 1/f noise in voltage, K is a process-dependent constant,

COX is the gate oxide capacitance, f is the frequency, and W and L are the

MOSFET channel width and length, respectively [2.26]. As shown in Eq. (2-6), 1/f noise is inversely proportional to the frequency. Thus, at low frequencies, it can become considerable. Since 1/f noise in the 4T pixel is mainly contributed by the source follower transistor [2.27], the introduction of a buried-channel source follower to the 4T pixel together with CDS achieves a good 1/f noise performance at the sensor level [2.28]. (d) Thermal Noise

Thermal noise, also called Johnson noise, mainly originates from the resistors and the channel of MOSFETs. As for a pixel, the in-pixel source follower is the main source of thermal noise [2.21]. The value of thermal noise can be given as [2.21]:

4

i kTg BWm

   . (2-7) where σi is the thermal noise in ampere, k is Boltzmann’s constant, T is the

absolute temperature, gm is the transistor transconductance, and analog BW

is the bandwidth. As presented in Eq. (2-7), a small bandwidth is favorable to lower the thermal noise. Furthermore, lowering the temperature can also be used to reduce the thermal noise. Therefore, the aforementioned two methods can be taken as countermeasures to minimize the pixel thermal noise.