Industries worldwide face increasing pressure for higher accuracy and reliability in automated systems. Regulatory demands for safety in autonomous driving and stringent quality control in manufacturing necessitate sensors that perform flawlessly under diverse conditions. This technology meets these demands by providing superior signal quality and low-light performance, enabling breakthroughs in critical applications and offering a competitive edge in rapidly evolving global markets.
Enhances Signal Precision 10x: Minimizes total dark current at the node by canceling dark currents from the photoelectric conversion layer and floating diffusion capacitance, significantly reducing signal error and achieving 10 times higher precision pixel output compared to conventional methods.
Ensures Reliability in Low-Light Conditions: Enables clear, low-noise image acquisition even with extremely weak light or in low-light environments by suppressing dark current, providing high signal quality while maintaining high sensitivity.
Offers High Compatibility with Existing Processes: Integrates easily into CMOS-type pixel circuit designs without requiring major manufacturing line changes, efficiently suppressing development costs and time, and supporting rapid market entry.
This patent protects a robust design for solid-state image sensors, specifically covering the mechanism to minimize total dark current by canceling opposing dark currents from the photoelectric conversion layer and floating diffusion capacitance. It has successfully overcome examiner objections and was granted after comparison with eight prior art documents, indicating strong enforceability and low invalidation risk.
This patent focuses on pixel-level dark current cancellation. White space exists in integrating this sensor with advanced AI-driven image processing algorithms or developing novel optical systems that further enhance light capture and signal-to-noise ratios.
By introducing high-precision solid-state image sensors, the misjudgment rate in manufacturing line image inspections could be reduced from the current 5% to 0.5% (a 10x reduction). Assuming a product with an annual production value of ~$66.5M (AI est.) incurs 5% in defect and re-inspection costs due to misjudgments, this technology could achieve an annual cost reduction of approximately ~$1.5M (AI est.) (~$66.5M × 5% × (1 - 0.6) = ~$1.5M) (AI est.). This directly leads to improved production efficiency and strengthened quality assurance.
X: Signal Precision and Reliability
Y: Environmental Adaptability and Robustness