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CMOS image sensor pixel optical efficiency and optical crosstalk optimization using FDTD Solutions

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The cost of CMOS image sensor digital camera systems is being reduced through the use of smaller pixel sizes. Ideally, the reduction in size of CMOS image sensor pixels can be achieved with an improvement in image resolution and without a significant decrease in signal to noise. As image sensor pixel sizes continue to decrease, there is the risk of a reduction in optical efficiency, as well as an increase in optical crosstalk between adjacent image sensor pixels. These effects can be mitigated through suitable pixel design and placement of microlenses above each photodiode to redirect and focus the light onto the active detector regions.

 

How FDTD Solutions Performs

"Diffraction effects due to decreasing pixel sizes substantially affect photon collection and invalidate a ray tracing model. A more fundamental description is required, and we chose FDTD Solutions from Lumerical.
F. Hirigoyen, STMicroelectronics

 

Step 1. Construct the FDTD Solutions model of the CMOS image sensor pixel microlens array

Screenshot of full three-dimensional CMOS image sensor pixel microlens model in FDTD Solutions.

Screenshot of full three-dimensional CMOS image sensor pixel microlens model in FDTD Solutions.

More advanced pixel models can incorporate effects like surface roughness as measured via AFM measurements and imported into FDTD Solutions.

More advanced pixel models can incorporate effects like surface roughness as measured via AFM measurements and imported into FDTD Solutions.

The layout editor shows the 3D layout of the CMOS image sensor microlens array.

 

Each image sensor pixel model includes color filters, parametrized microlenses, metallic interconnects and sometimes light shields above the silicon active regions and substrate.  Each individual pixel is composed of four sub-pixels as can be seen in the figure to the left: two green, a red and a blue.

 

Comparisons between the simulated performance of the idealized device relative to the device as it would be manufactured – here, incorporating surface roughness as measured via AFM measurements – can help pinpoint where process improvements can benefit overall device performance.

 

Step 2. Improve your understanding of CMOS image sensor pixel performance and design challenges by studying how it operates

To gain insight into the sources of scattered light in the CMOS image sensor, use the built-in movie monitor in FDTD Solutions to capture the field dynamics of the simulation.  A properly designed image sensor pixel microlens focuses light between the metallic interconnects, avoiding unwanted scattering and crosstalk while maximizing detector efficiency.

 

Light focuses through the light shield in one pixel, and is blocked by the color filter in the adjacent pixel.  The light shield reduces optical crosstalk between pixels.

Light focuses through the light shield in one pixel, and is blocked by the color filter in the adjacent pixel. The light shield reduces optical crosstalk between pixels.

Absorption takes place in the active region underneath each pixel

Absorption takes place in the active region underneath each pixel

Complicated scattering results from light incident on the high index contrast interfaces within the image sensor pixel, especially at non-normal incidence.

Complicated scattering results from light incident on the high index contrast interfaces within the image sensor pixel, especially at non-normal incidence.

Scattering from interconnects at non-normal incidence leads to optical crosstalk between pixels

Scattering from interconnects at non-normal incidence leads to optical crosstalk between pixels

 



Step 3. Optimizing  the angular response of CMOS image sensors: increasing optical efficiency and reducing spectral optical crosstalk

Optical efficiency of the green sub-pixels at a wavelength of 550nm as a function of incident angle and microlens shift from the center of the pixel.

Optical efficiency of the green sub-pixels at a wavelength of 550nm as a function of incident angle and microlens shift from the center of the pixel.

Spectral optical crosstalk measured – here, under the red sub-pixel – at a wavelength of 550nm as a function of incident angle and microlens shift from the center of the sub-pixel.

Spectral optical crosstalk measured – here, under the red sub-pixel – at a wavelength of 550nm as a function of incident angle and microlens shift from the center of the sub-pixel.

Optical efficiency versus microlens shift at incident angles of 0, 10, 20, and 30 degrees.

Optical efficiency versus microlens shift at incident angles of 0, 10, 20, and 30 degrees.

To measure spectral optical crosstalk, the downward power flow in adjacent sub-pixels can be calculated by integrating the Poynting vector.  The middle-left figure shows that the spectral optical crosstalk is generally minimized where the optical efficiency is maximized, but that at steep angles of incidence elevated levels of crosstalk are observed.  More sophisticated device designs, in which other sub-pixel elements (e.g. interconnects) are also shifted, may provide a means by which overall crosstalk levels can be reduced.

 

By examining cross sections of the above data, it is straightforward to determine what shift is required to optimize the optical efficiency.  The measured optical efficiency (i.e. transmission) into the active region underlying the green sub-pixel shows that for a 10 degree incident angle, a shift of about 350nm is required, and that as the angle of incidence increases to 30 degrees, shifts approaching 1 micron are required.  Initially, a good design could be achieved by assuming that the CRA is equivalent to the angle of incidence used in this analysis.  A more complete analysis of this data could incorporate effects due to the incident light cone without requiring one to run more simulations.

 

Step 4. Point spread function calculation via FDTD Solutions for CMOS image sensors

Each pixel is composed of four sub-pixels: two green, one red, and one blue.

Each pixel is composed of four sub-pixels: two green, one red, and one blue.

Spatial distribution of power flux recorded at the silicon surface shown on a logarithmic scale.

Spatial distribution of power flux recorded at the silicon surface shown on a logarithmic scale.

Relative photocurrent generated within each photodiode.

Relative photocurrent generated within each photodiode.

Spatial optical crosstalk can be characterized via the point spread function – which quantifies how much an incoming signal is blurred through the CMOS imaging system.  In these simulations, we illuminate a central pixel (composed of four sub-pixels – two green, one red, and one blue) with green light at a wavelength of 550nm through a lens system with a numerical aperture of 0.25.

 

Owing to imperfect color filters, the finite-sized incident beam, and scattering, refraction and diffraction taking place within the image sensor pixel, incoming green light illuminates the silicon surface above the photodiodes of the illuminated pixel, and adjacent pixels.  The figure to the left shows the downward power flux into the silicon substrate over the pixels as indicated.  While the incoming signal is brightest over the two central green sub-pixels, residual signal is observed over the illuminated red and blue sub-pixels, and on nearby green sub-pixels.

 

Integrating over the active region underneath each sub-pixel region, it is straightforward to calculate the device response.  The figure to the left shows that, as expected, the two central green sub-pixels indicate a large amount of incident light.  The next largest signal is recorded on the adjacent green sub-pixels.  Finally, there is a very slight signal recorded on the nearby red and blue sub-pixels owing to the extra absorption that takes place in the red and blue color filters for the incident green light.  The underlying asymmetry of the sub-pixel structure leads to an asymmetric point spread function.

 

We gratefully acknowledge the collaboration and assistance of Axel Crocherie, Flavien Hirigoyen, Jérôme Vaillant and Yvon Cazaux of STMicroelectronics, France.

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