Micro-LED/van der Waals heterointegration for in-pixel processing display architecture
The rapid evolution of intelligent display technologies is driving the development of next-generation edge smart systems, yet conventional off-pixel processing architectures suffer from severe display latency and energy bottlenecks. Embedding in-memory computing features into pixel-level active drivers presents a promising strategy for co-locating image processing and display. In this work, we provide an in-pixel processed display-driven architecture that integrates micro-LEDs with MoS<sub>2</sub> in-memory transistors into a 16 × 16 active display array. Our in-pixel processing design exhibits high luminance (>3 × 10<sup>5 </sup>cd·m⁻<sup>2</sup>), high-speed operation (5000 Hz), and compact dimensions of 20 × 35 μm per pixel. Crucially, leveraging the segmented voltage-luminance response and the non-volatile multilevel conductance update characteristics of the design devices, we demonstrate in-situ image reconstruction and real-time display using in-pixel processed micro-LED arrays. The image reconstruction capability of the proposed design is validated through a neural network-based image recognition task, where the inference process is implemented directly on the pixel array by deploying the trained weights via non-volatile conductance modulation. The reconstructed images achieved a significantly higher accuracy of 99.29% compared to the original inputs (79.81%). These results highlight the significance of the in-pixel processed display architecture as a promising approach to realize high-performance intelligent display technologies.
Authors
- Zhaorui Liu (ORCID: https://orcid.org/0009-0005-7859-5918)
- Enlong Li
- Yuchun Wu
- Siqi Liu
- Zhu Yang
- Hongling Chu
- Fei Wang
- Jingjing Liu
- Jingbo Yang
- Luqiao Yin
- Mengjiao Li
- Jianhua Zhang
Institutions
- Shanghai University (CN)
- Shanghai Fudan Microelectronics (China) (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-02-21
- DOI
- https://doi.org/10.1038/s41467-026-69786-2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China