Super Small, Sub 2μm Pixels for Novel CMOS Image Sensors

Pixel shrink is a driving force for novel CMOS image sensor development used in mobile and DSC applications. This paper describes the latest results in super small, sub 2μm pixel development at Micron Technology, Inc. Presented are results of optical and electrical characterization of super small pixels and their respective pixel arrays. The paper considers general light signal characteristics, spectral characteristics, quantum efficiency and crosstalk of super small pixels, and their effect on the final quality and signal-to-noise ratio of the color image post color processing. 1.75μm Pixel Development Micron demonstrated the first image from a 1.75μm pixel array in June 2005 [1]. In the two years since the first pixel arrays were demonstrated, significant progress has been made in 1.75μm pixel and process development. Several generations of 1.75μm pixels were created over this period of time, and a full line of image sensors with different array sizes (from 1.3Mp through 8Mp) are in production now. This paper will compare optical and electrical characteristics of 1.75μm pixels used in the first and current generations of pixel arrays and image sensors. To date, Micron’s development of the 1.75μm pixel has been focused on using our common element pixel architecture (CEPA) with 1.75and 1.5-equivalent transistors, per pixel. Early 1.75μm pixel generations utilized asymmetrical pixel structures, enabling a high conversion gain of the floating diffusion (up to 115uV/e for the 4-way CEPA), large photodiode fill factor, and a large pixel capacity (up to 9200 electrons for the linear full well). Current pixel designs focus more on symmetrical pixel architectures where metal openings and photodiodes are equally spaced for pixels within different color planes. Symmetrical architectures simplify pixel shading and color distortion compensation at the system level; however, keeping the same level of pixel performance in regards to fill factor and pixel capacity becomes a significant challenge. This is partially resolved by using an advanced 95nm manufacturing processes for the pixel array. Figure 1 presents photodiode fill factors and pixel capacities for different revisions of Micron’s 1.75μm pixel. The square, triangle, and circle data points represent versions of the pixel with an asymmetrical, quasi-symmetrical, and practically fully symmetrical design. Solid data points represent pixel capacity, and hollow data points fill factor. Arrows at the bottom of the plot indicate manufacturing process nodes used for the respective pixel designs. As can be seen from the plot, the latest pixels with a symmetrical design achieve similar fill factor and pixel capacity to their asymmetrical predecessors 43% fill factor and 9200 electrons for the linear full well. Quantum efficiency and crosstalk are two of the most important pixel characteristics that significantly affect sensitivity, general image quality, and signal-to-noise ratio after color processing. Optimization of the pixel was accomplished in several aspects: optimization of the optical path of the pixel, optimization of the pixel design/architecture, and optimization of the Si substrate. Optimization of the pixel optical path includes an advanced aluminum process with a reduced stack height of dielectric layers, a gapless microlens process, optimized metal routing, and embedded anti-reflective coatings. The total stack height between microlens and Si surface for the optimized process was reduced to less than 3.2μm, which provides a large-pixel acceptance angle of light as well as the ability to work with low-profile lenses with chief ray angles up to 27 degrees. By utilizing an advanced aluminum metal process, Micron eliminated the need to remove any light inhibiting diffusion barrier layers associated with copper processing. Figure 2 presents the results of a wave propagation simulation for the 1.75μm pixel with an optimized optical path for green light (550nm). As can be seen from the picture, light is well confined by pixel optics into the photodiode area. The pixel exhibits a large acceptance angle of light signal degradation is less than 20 percent for angles of incident light up to 25 degrees. Optimization of the Si substrate was conducted by using both traditional p-substrate and n-substrate approaches. Nsubstrates significantly reduce electrical crosstalk by collecting and sinking carriers that are created with deep absorbed photons. Use of n-substrates also reduces dark current from the substrate. However, reduced thickness of pEPI above the n-substrate can degrade QE for green and red pixels, resulting in degradation of overall sensitivity. Thus, optimization of the thickness of the pEPI layer needs to be done to assure optimal trade off between quantum efficiency and crosstalk from the SNR after color processing stand point. Resulting experimental spectral response data for the p-substrate and nsubstrate versions of a 1.75μm pixel currently in production are presented in Figure 3a and Figure 3b, respectively. These figures present both spectral response and crosstalk data calculated according to [2]. The p-substrate version of the pixel QE maximum is equal to 42%, 45%, and 38% for blue, green, and red pixels respectively. The n-substrate version of the pixel has QE maximum equal to 42%, 37%, and 29% for blue, green, and red pixels respectively. As will be shown later, in spite of the slight degradation of QE for the n-substrate version of the pixel, overall sensitivity of the sensor after color processing becomes higher due to a significant reduction of electrical crosstalk. Also, the n-substrate version of the pixel exhibits higher SNRmax when compared with the p-substrate pixel at the same full well capacity due to lower crosstalk. For comparison purposes, the earliest generations of 1.75μm pixels on the p-substrate exhibited QE maximum of 28%, 36%, and 23% for blue, green, and red pixels respectively. The progress in pixel development resulted in about a 50% improvement in QE and a 40% improvement in crosstalk. Note that nsubstrates may not provide an advantage for all pixel sizes, and the benefit of n-substrates becomes more advantageous in