SK hynix BSI technology: a leading light in the global mobile market

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A CIS (CMOS Image Sensor) is a sensor that converts the color and brightness of light captured through a lens into an electrical signal and transmits it to a processing unit. Consequently, these image sensors act as the eyes of mobile devices such as smartphones and tablets. Recently, CIS technology has gained attention as a key technology in the Fourth Industrial Revolution along with virtual reality (VR), augmented reality (AR), and autonomous vehicles. It is anticipated that the technology will not stop at simply becoming the eyes of a device, but will make further developments in its capabilities.

It has been 15 years since SK hynix launched a working group to develop CIS products. In addition to its core semiconductor memory business represented by DRAM and NAND flash, SK hynix has also been developing and producing non-memory semiconductor CIS to increase its competitiveness. SK hynix has developed numerous device and process technologies to narrow the technology gap with competitors, and the company has now reached the point of producing ultra-high-resolution CIS products featuring 50 million pixels or more with a pixel size of only 0.64μm. (micrometers). This article will introduce BSI (Backside Illumination) technology, a key element of CIS, based on the contents of the 10th SK hynix Academic Conference, which was held in November.

FSI technology and its limits

The pixels of early CIS products feature an FSI (Front-Ended Illumination) structure that places an optical structure on top of a CMOS.1 Process-based loop. This technology is applied to most CIS solutions with a pixel size of 1.12 μm or more and is used in various products including mobile devices, CCTV, dash cams, DSLR cameras, and vehicle sensors.

1) Complementary Metal Oxide Silicon (CMOS) – A complementary logic circuit consisting of pairs of n-channel and p-channel MOSFETs. CMOS devices consume minimal power and are used in DRAM and CPU products as they are capable of large-scale integration, independent of their complex processors.
Figure 1. FSI structure and pixel unit diagram

A high performance image sensor should be able to display bright images even in low light conditions, and this requires increasing Quantum Efficiency (QE)2 of the pixels. Therefore, the design of the metal wiring in the bottom circuit of the pixel should be based on the FSI structure to avoid light interference as much as possible.

2) Quantum Efficiency (QE): The measure of the effectiveness of an imaging device in converting incident photons into electrons. A sensor with 100% QE exposed to 100 photons would produce 100 signal electrons.
Figure 2. QE equation and FSI structure diagram

However, in general, diffraction3 Light occurs when continuous light waves pass through an opening or around objects. In the case of an aperture, as the size of the hole decreases, more light is scattered as diffraction increases.

3) Diffraction: The propagation of waves such as sound and light when they pass through an obstacle or opening. In the case of light, diffraction occurs when the size of the obstacle or aperture is equal to or less than the wavelength of the passing wave.

Similarly, diffraction is unavoidable even when external light hits a single pixel. In the case of the FSI structure, it is more vulnerable to diffraction as it is affected by the layer of metal wiring in the lower circuit. Even if the FSI pixel sizes are reduced, the area covered by the metal remains the same. Consequently, the area through which the light passes becomes smaller and diffraction intensifies, resulting in colors mixing in the image.

Figure 3. Diffraction of light (top) and diffraction enhancement due to pixel contraction (bottom)

However, it is not impossible to control the diffraction of the pixels. To improve diffraction in a single area, the distance between the microlens and silicon (Si) can be reduced according to the diffraction calculation formula. To this end, a BSI process was proposed in which metal interference was eliminated by flipping the wafer to use the rear. At SK hynix, the introduction of BSI technology began with products with a pixel size of 1.12 μm or less.

Birth of BSI-based pixel technology

In 2011, Apple introduced the iPhone 4, which was equipped with the first CIS applied with BSI. This BSI-based CIS was said to capture relatively higher amounts of light compared to existing FSI technology and therefore reproduce higher quality images.

The BSI process used by Apple and now throughout the industry is shown in the following flowchart. In the case of BSI technology, all circuit parts are first produced on one side of the wafer before the wafer is flipped and reversed to allow the creation of a light-collecting optical structure at the rear. As a result, it is It is possible to eliminate interference caused by metal cabling in FSI and widen the area where light can pass through to provide higher QE.

Figure 4. Flowchart of the BSI process
Figure 5. Comparison of distance between the microlens and the photodiode (PD) according to structure

Through said BSI technology, it became possible to apply a pixel size of 1.12 μm or smaller, and created a market for high-resolution products with 16 million pixels or more. Unlike the FSI structure, which suffered from interference caused by cabling, the optical process was able to have a higher degree of freedom. As a result, Various optical pixel structures such as BDTI, W Grid, and Air Grid have been developed, and these structures are used to increase the QE of products.

  • BDTI (Backside Deep Trench Insulation) Process

Although it is possible to have high QE with just a BSI structure that has overcome light diffraction, an additional pixel splitting structure was required to support the ever smaller pixel size and reduction of the F number.4 of smartphone cameras. A good example of an additional split structure is the BDTI that promotes Total Internal Reflection (TIR)5 in areas where light enters diagonally along the outside of a CIS chip, increasing the signal. This technology is currently applied to most of the BSI based CIS products.

4) F number: A value that determines the brightness of the aperture. The smaller the camera’s F value, the wider the aperture opens to collect more light, allowing the camera to take brighter photos in darker places while reducing image noise.
5) Total Internal Reflection (TIR): A total reflection of light within a medium, including water or glass, from surrounding surfaces back into the medium. TIR occurs when the angle of incidence is greater than the critical angle.
Figure 6. Conventional BSI structure and BDTI process as additional pixel division structure
  • Color Filter Isolation Structure

Parallel to the BDTI structure, another technique to improve the performance of BSI-based pixels is to insert physical barriers between the color filters. Since the distance between the microlens and the photodiode6 could no longer be reduced after BSI, this structure prevents diffraction caused by pixel shrinkage. Structures representative of the color filter isolation method include a W-shaped grid formation or SK hynix’s patented Air Grid structure. Unlike the W grid, which is a simple light-blocking structure, the Air Grid, which uses TIR, is expected to be a next-generation technology as it can even increase QE.

6) Photodiode (PD): Converts the light received by the CIS sensor into an electrical signal.
Figure 7. W grid structure and air grid structure

Bright future for SK hynix’s BSI-based pixel technology

Since BSI-based CIS products first appeared on the iPhone 4 in 2011, the gap between the best-performing CIS companies and the rest has widened, leading many CIS sensor companies to pull out of the market. mobile market. However, SK hynix quickly secured the BSI technology through its own capabilities and developed core element technologies including BDTI and Air Grid by applying them to products with a pixel size of 1.12 μm or less.

SK hynix BSI technology is constantly evolving. Recently, SK hynix succeeded in developing a hybrid junction technology that applies ‘Cu-to-Cu junction’ to TSV-based stacked sensors (via a silicon pathway), laying the foundation for further competitiveness in the size of the chip and the expansion of multilayer wafer bonding technology. . These technological achievements are expected to contribute to the expansion of the market by being used in the development of various sensors that support AI, medical devices, AR, and VR in the future.

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