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Related Experiment Video

Updated: Jul 17, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

Monolithic 3D Integration of Analog RRAM-Based Computing-in-Memory and Sensor for Energy-Efficient Near-Sensor

Yiwei Du¹, Jianshi Tang¹, Yijun Li¹

¹School of Integrated Circuits, Beijing Advanced Innovation Center for Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.

Advanced Materials (Deerfield Beach, Fla.)

|August 31, 2023

Summary

This study introduces a novel near-sensor computing (NSC) architecture, M3D-SAIL, integrating photosensors and analog computing-in-memory (CIM). This innovation significantly enhances energy efficiency and processing speed for data-intensive IoT applications.

Keywords:

InGaZnOx field‐effect transistor computing‐in‐memory monolithic 3D integration near‐sensor computing resistive random‐access memory

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Last Updated: Jul 17, 2025

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Area of Science:

Materials Science
Electrical Engineering
Computer Science

Background:

The Internet of Things (IoT) generates massive data, straining bandwidth and energy efficiency.
Current computing architectures face limitations in processing data at the source.
Near-sensor computing (NSC) offers a solution by processing data closer to where it's generated.

Purpose of the Study:

To demonstrate a monolithic three-dimensional (M3D) integrated NSC architecture (M3D-SAIL).
To combine photosensor arrays, analog computing-in-memory (CIM), and Si complementary metal-oxide-semiconductor (CMOS) logic circuits.
To achieve high energy efficiency and processing speed for sensor data.

Main Methods:

Developed a M3D integration of Si CMOS logic, InGaZnOₓ field-effect transistor (IGZO-FET) and resistive random-access memory (RRAM) based CIM, and IGZO-FET photosensor arrays.
Utilized a 1k-bit 1T1R array for analog CIM.
Verified the structural integrity and functionality of each integrated layer.

Main Results:

Successfully implemented NSC using the M3D-SAIL architecture.
Achieved 96.7% classification accuracy for video keyframe extraction.
Demonstrated a 31.5x reduction in energy consumption and a 1.91x increase in computing speed compared to 2D counterparts.

Conclusions:

The M3D-SAIL architecture enables highly efficient NSC.
This approach addresses critical bandwidth and energy challenges in IoT data processing.
M3D integration offers a promising pathway for advanced, in-situ sensor data analysis.