Two-dimensional fully ferroelectric-gated hybrid computing-in-memory hardware for high-precision and energy-efficient...

Computing in memory (CIM) breaks the conventional von Neumann bottleneck through in situ processing. Monolithic integration of digital and analog CIM hardware, ensuring both high precision and energy efficiency, provides a sustainable paradigm for increasingly sophisticated artificial intelligence (AI) applications but remains challenging. Here, we propose a complementary metal-oxide semiconductor-compatible ferroelectric hybrid CIM platform that consists of Boolean logic and triggers for digital processing and multistage cell arrays for analog computation. The basic ferroelectric-gated units are assembled with solution-processable two-dimensional (2D) molybdenum disulfide atomic-thin channels at a wafer-scale yield of 96.36%, delivering high on/off ratios (>10⁷), high endurance (>10¹²), long retention time (>10 years), and ultralow cycle-to-cycle/device-to-device variations (~0.3%/~0.5%). Last, we customize a highly compact 2D hybrid CIM system for dynamic tracking, achieving a high accuracy of 99.8% and a 263-fold improvement in power efficiency compared to graphics processing units. These results demonstrate the potential of 2D fully ferroelectric-gated hybrid hardware for developing versatile CIM blocks for AI tasks.