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AI boost for CMOS image sensors with three layer integration

AI boost for CMOS image sensors with three layer integration

Technology News |
By Nick Flaherty

Cette publication existe aussi en Français


CEA-Leti in France has developed a process for combining hybrid bonding and high density through-silicon vias (TSVs) to add AI into CMOS image sensors.

The integration of AI by CEA-Leti allows new generation of CMOS image sensors (CIS) that can exploit all the image data to perceive a scene, understand the situation and intervene

The project developed a three-layer test vehicle that featured two embedded Cu-Cu hybrid-bonding interfaces, face-to-face (F2F) and face-to-back (F2B), and with one wafer containing high-density TSVs.

The details were shown at the ECTC 2024 conference in Denver this week and build on previous work on stacking three 300 mm silicon wafers. 

Demand for smart sensors is growing rapidly because of their high-performance imaging capabilities in smartphones, digital cameras, automobiles and medical devices. This demand for improved image quality and functionality enhanced by embedded AI has presented manufacturers with the challenge of improving sensor performance without increasing the device size.

“Stacking multiple dies to create 3D architectures, such as three-layer imagers, has led to a paradigm shift in sensor design,” said Renan Bouis, researcher at CEA-Leti in Grenoble.

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“The communication between the different tiers requires advanced interconnection technologies, a requirement that hybrid bonding meets because of its very fine pitch in the micrometer & even sub-micrometer range,” he said.

“High-density through-silicon via (HD TSV) has a similar density that enables signal transmission through the middle tiers. Both technologies contribute to the reduction of wire length, a critical factor in enhancing the performance of 3D-stacked architectures.”

 “The papers present the key technological bricks that are mandatory for manufacturing 3D, multilayer smart imagers capable of addressing new applications that require embedded AI,” said Eric Ollier, project manager at CEA-Leti and director of IRT Nanoelec’s Smart Imager program. The CEA-Leti institute is a major partner of IRT Nanoelec.

“Combining hybrid bonding with HD TSVs in CMOS image sensors could facilitate the integration of various components, such as image sensor arrays, signal processing circuits and memory elements, with unparalleled precision and compactness,” said researcher Stéphane Nicolas.

The test vehicle is a key milestone because it demonstrates both feasibility of each technological brick and also the feasibility of the integration process flow. “This project sets the stage to work on demonstrating a fully functional three-layer, smart CMOS image sensor, with edge AI capable of addressing high performance semantic segmentation and object-detection applications,” he said.

Last year CEA-Leti scientists reported a two-layer test vehicle combining a 10-micron high, 1-micron diameter HD TSV and highly controlled hybrid bonding technology, both assembled in F2B configuration. The recent work then shortened the HD TSV to six microns high, which led to development of a two-layer test vehicle exhibiting low dispersion electrical performances and enabling simpler manufacturing.

“Our 1-by-6-micron copper HD TSV offers improved electrical resistance and isolation performance compared to our 1-by-10-micron HD TSV, thanks to an optimized thinning process that enabled us to reduce the substrate thickness with good uniformity,” said researcher Stéphan Borel.

“This reduced height led to a 40 percent decrease in electrical resistance, in proportion with the length reduction. Simultaneous lowering of the aspect ratio increased the step coverage of the isolation liner, leading to a better voltage withstand,” he added.

“With these results, CEA-Leti is now clearly identified as a global leader in this new field dedicated to preparing the next generation of smart imagers,” said Ollier. “These new 3D multi-layer smart imagers with edge AI implemented in the sensor itself will really be a breakthrough in the imaging field, because edge AI will increase imager performance and enable many new applications.”

www.leti-cea.com;  https://irtnanoelec.fr/actualites/smart-imager-from-imaging-to-vision-sensing/

 

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