Demonstrates improved energy efficiency in sensor-level processing applications, suggesting a novel hardware approach.
In‐sensor processing is a key enabler for edge computing because it allows sensor data to be processed locally, thereby reducing data movement and improving the efficiency of complex workloads. In particular, emerging computationally intensive applications such as explainable artificial intelligence (XAI) further increase the demand for dedicated in‐sensor hardware capable of efficient sensor‐level processing. Here, we report an optoelectronic memtransistor (OEMT) that integrates a photoresponsive indium zinc oxide (IZO) channel with a NbO x /AlO x charge‐trapping gate stack, enabling optical sensing, electrical masking, and non‐volatile memory within a single three‐terminal device architecture. We experimentally demonstrate sensor‐level vision explainable artificial intelligence (VXAI) operation using a 3 × 3 OEMT array and validate its scalability through hardware‐based simulations. Compared with a conventional sensing–processing pipeline, the OEMT‐based framework achieves a 21‐fold improvement in system‐level energy efficiency, highlighting its strong potential for efficient sensor‐level processing.
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Lee et al. (2026) studied this question.
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