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Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition

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Atomic Layer-Deposited HfAlOx-Based RRAM with Low Operating Voltage for Computing In-Memory Applications.

Zhen-Yu He¹, Tian-Yu Wang¹, Lin Chen²

¹State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, 200433, China.

Nanoscale Research Letters

|February 9, 2019

Summary

Resistive random-access memory (RRAM) offers a solution to the limitations of traditional computing architectures. HfAlOx-based RRAM devices demonstrate efficient in-memory computing with low power consumption and high-speed logic operations.

Keywords:

Computing in-memory Implemented RRAM Switching

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Area of Science:

Materials Science
Computer Engineering
Electrical Engineering

Background:

Moore's Law is approaching its physical limits, challenging traditional von Neumann architectures.
Computing-in-memory (CIM) architectures, particularly resistive random-access memory (RRAM), are emerging as a solution to the von Neumann bottleneck.
CMOS-compatible RRAM fabrication is crucial for next-generation computing.

Purpose of the Study:

To fabricate and characterize HfAlOx-based RRAM devices for memory-computing applications.
To demonstrate the feasibility of implementing in-memory computing (IMC) logic using RRAM.
To evaluate the performance of RRAM-based logic operations in terms of speed and power consumption.

Main Methods:

Fabrication of HfAlOx-based RRAM using atomic layer deposition (ALD).
Selection of Silver (Ag) and Tantalum Nitride (TaN) as top electrodes (TE).
Experimental implementation of in-memory processing (IMP) logic using low-voltage pulses.

Main Results:

Ag/HfAlOx/Pt RRAM devices exhibited advantages for memory-computing, including low set voltage (0.33–0.6 V) and good uniformity.
High-speed in-memory processing (IMP) logic was successfully implemented using 100-ns, low-voltage pulses (0.3 V and 0.6 V).
NAND logic operations were achieved after two steps of IMP implementation.

Conclusions:

HfAlOx-based RRAM is a promising candidate for overcoming the von Neumann bottleneck due to its low power consumption and high-speed operation.
The demonstrated IMP logic implementation highlights the potential of RRAM for efficient, integrated memory and computing.
This research paves the way for developing advanced, energy-efficient computing systems.