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

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

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

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 below: 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 design and process improvements can benefit overall device performance.

Screenshot of full three-dimensional CMOS image sensor pixel microlens model, including color filters and microlenses, in FDTD Solutions.

More sophisticated pixel models can incorporate effects like surface roughness as measured via AFM measurements and imported into FDTD Solutions via the custom surface simulation primitive.

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.  The ability to visualize device performance helps designers understand the origins of light scattering that undermine device performance.

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

To measure spectral optical crosstalk, the downward power flow in adjacent sub-pixels can be calculated by integrating the Poynting vector.  Spectral optical crosstalk is generally minimized when optical efficiency is maximized, but at steep angles of incidence elevated levels of crosstalk are observed and are, to a certain extent, unavoidable.  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

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 the 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 below 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.