Polarization-sensitive in-sensor computing in chiral organic integrated 2D p-n heterostructures for mixed-multimodal image processing
Je‐Jun Lee, S.H. Han, Changsoon Choi, Chaewon Seo, Seungkwon Hwang, Jihyun Kim, Jung Pyo Hong, Jisu Jang, Jihoon Kyhm, Jung Ho Kim, Byoung‐Soo Yu, Jung Ah Lim, Gunuk Wang, Joohoon Kang, Yonghun Kim, Suk‐kyun Ahn, Jongtae Ahn, Do Kyung Hwang
Abstract
Sensor-based computing minimizes latency and energy consumption by processing data at the capture point, thereby eliminating extensive data transfer and enabling real-time decision-making. Here, we present a breakthrough in in-sensor computing via circularly polarized light detectors that integrate cholesteric liquid crystal reflectors with two-dimensional van der Waals p-n heterostructures. Our device exhibits a high dissymmetry factor (1.90), allowing effective separation of mixed circularly polarized images, along with a rapid photoresponse (4 μs) and wide linear dynamic range (up to 114.1 dB), suitable for analog multiply-and-accumulate operations in convolution-based in-sensor computing. Harnessing these detectors, we propose mixed-multimodal in-sensor computing using the chiral state of circularly polarized light to dynamically control responsivity, which enables the blending of two arbitrary image processing modes within a single, non-reconfigurable circuit. By effectively integrating polarization-sensitive detectors into the in-sensor computing framework, the proposed architecture preserves kernel optimization capabilities while simplifying circuit complexity. In-sensor computing minimizes latency by directly processing data at the point of capture. Here, authors optimize this process by integrating polarization-sensitive detectors into the computing framework, enabling the superposition of two filtering operations within a single circuit.