Optoelectronic array of photodiodes integrated with RRAMs for energy-efficient in-sensor computing.

The rapid development of internet of things (IoT) urgently needs edge miniaturized computing devices with high efficiency and low-power consumption. In-sensor computing has emerged as a promising technology to enable in-situ data processing within the sensor array. Here, we report an optoelectronic array for in-sensor computing by integrating photodiodes (PDs) with resistive random-access memories (RRAMs).

Fully integrated multi-mode optoelectronic memristor array for diversified in-sensor computing.

In-sensor computing, which integrates sensing, memory and processing functions, has shown substantial potential in artificial vision systems. However, large-scale monolithic integration of in-sensor computing based on emerging devices with complementary metal-oxide-semiconductor (CMOS) circuits remains challenging, lacking functional demonstrations at the hardware level. Here we report a fully integrated 1-kb array with 128 × 8 one-transistor one-optoelectronic memristor (OEM) cells and silicon CMOS circuits, which features configurable multi-mode functionality encompassing three different modes of electronic memristor, dynamic OEM and non-volatile OEM (NV-OEM).

Reconfigurable Five-In-One Carbon Nanotube Optoelectronic Transistor for Intelligent Computing and Communication.

Advances in artificial general intelligence (AGI) necessitate the integration of diverse functionalities to address complex tasks. Carbon nanotubes (CNTs), with their unique physical properties, have broad applications in emerging research fields, providing a foundation for next-generation devices that could overcome the limits of Moore's Law. This work demonstrates a novel intelligent device that integrates five functions─sensors, memory, neuromorphic computing, logic, and communication─using CNT field-effect transistors (CNFETs) compatible with CMOS processes.

Giant Electroresistance in Ferroionic Tunnel Junctions.

Oxide-based resistive switching devices, including ferroelectric tunnel junctions and resistance random access memory, are promising candidates for the next-generation non-volatile memory technology. In this work, we propose a ferroionic tunnel junction to realize a giant electroresistance. It functions as a ferroelectric tunnel junction at low resistance state and as a Schottky junction at high resistance state, due to interface engineering through the field-induced migration of oxygen vacancies.

Artificial Synapses Emulated by an Electrolyte-Gated Tungsten-Oxide Transistor.

Considering that the human brain uses ≈10 synapses to operate, the development of effective artificial synapses is essential to build brain-inspired computing systems. In biological synapses, the voltage-gated ion channels are very important for regulating the action-potential firing. Here, an electrolyte-gated transistor using WO with a unique tunnel structure, which can emulate the ionic modulation process of biological synapses, is proposed.