Technical / research

Tetramem shows that its RRAM-powered analog computing SoC is capable of executing calculations with arbitrary precision

US-based Tetramem published a paper that shows its form of RRAM-powered analog computing is capable of executing calculations with arbitrary precision. It says the ability to perform high-precision multiplication within single electronic devices that can be readily formed in arrays offers scope to reduce the power consumption of machine learning when based on artificial neural networks.

The Tetramem device is made of a mixture of Al3O2, above a layer of HfO2 sandwiched between a tantalum/titanium top electrode and a platinum bottom electrode. Each of the bilayers is less than 1nm thick so that after being laid down they appear to form a mixed layer rather than two separate continuous layers. The device was fabricated in a 240-nm diameter via above the CMOS peripheral circuitry.

Read the full story Posted: Mar 13,2024

Perovskites enable novel light-emitting RRAM device

Researchers from Kyushu University and the National Taiwan Normal University developed a new RRAM device, readable through both electrical and optical methods. The device is based on perovskite quantum dots that enable to simultaneously store and visually transmit data.

All-inorganic perovskite quantum dot light-emitting memories image

By integrating a light-emitting electrochemical cell with a resistive random-access memory that are both based on perovskite, the team achieved parallel and synchronous reading of data both electrically and optically in a ‘light-emitting memory.’

Read the full story Posted: Aug 26,2021

The NEUROTEC project progresses, develops RRAM-based neuromorphic computer structures

The project NEUROTEC (“Neuro-inspired artificial intelligence technologies for the electronics of the future”) was launched in November 2019 to develop innovative "Beyond von Neumann" concepts for highly energy-efficient devices. The two-year project shows the great potential of a future neuromorphic computer.

Project NEUROTEC workpackages image

The project aims to fuse two major technologies - machine learning and artificial neural networks (ANNs) and memristive materials and devices - especially redox-based RRAM and phase change memories (PCM). The project's mandate is to develop a full-range of basic technologies ranging from dedicated material deposition technologies, integration technologies, measurement technologies, the development of simulation and modelling tools, up to the design and realization of novel AI circuits.

Read the full story Posted: Jul 25,2021

Researchers use graphene to enhance perovskite memristor devices

Researchers from the University of Groningen combined graphene with a perovskite ferroelectric material to design a new memristor device.

Graphene and perovskite ferroelectric memristor design (University of Groningen)

In the device, a graphene strip was placed on top of a flake of STO (strontium titanium oxide perovskite). The graphene strip addition enabled the usage of the STO material at higher temperatures than before. This research creates new insights into the adoption of STO materials in memristor devices.

Read the full story Posted: Nov 24,2020

New halid perovskite shows promise as an RRAN switching material

Researchers from Korea's Pohang University of Science & Technology (POSTECH) has designed a halide perovskite material for RRAM memory devices. The perovskite material offers low-operating voltage and high-performance resistive switching memory.

The researcher say they have succeeded in designing an optimal halide perovskite material (CsPb2Br5) that can be applied to a ReRAM device by applying first-principles calculation based on quantum mechanics.

Read the full story Posted: Jul 20,2020

NTU and GlobalFoundries to co-develop RRAM memories on 12" wafers

Singapore's Nanyang Technological University (NTU Singapore) and GlobalFoundries announced a partnership to jointly research next-generation RRAM memories. The two partners will invest $88 million USD with an aim to demonstrate RRAM memory devices produced on 12-inch wafers.

NTU and GF-Singapore are already collaborating on spintronics - the study of electron spin and its applications, including MRAM memory (NTU and GF are founding members of the Singapore Spintronics Consortium. In this new ReRAM project, 16 researchers will work together to research areas such as circuit design for next-generation smart devices and chip packaging for advanced IoT applications.

Read the full story Posted: Oct 21,2019

Weebit announced a collaboration project with the Technion Institue in Israel

Israel-based SiOx RRAM developer Weebit Nano has signed an agreement to collaborate with the Technion Institute in Israel. Weebit will work together with a team of researchers to examine the possible use of ReRAM devices in processing-in-memory that could speed up processing, memory transfer rate and memory bandwidth and decrease processing latency – while using less power.

Weebit Nano RRAM chip prototypes photo

Weebit and the Technion will also perform characterisation and implementation of logic operations using Weebit’s RRAM test chips, demonstrating basic logic operations on a RRAM array

Read the full story Posted: Feb 13,2019

Weebit Nano to collaboare with the Politecnico di Milano on a Neuromorphic AI project

Israel-based SiOx RRAM developer Weebit Nano launched a joint Neuromorphic ReRAM project with
Politecnico di Milano (Polimi). Weebit Nano's team will collaborate with researchers from the Poltecnico to test, characterize and implement its developed algorithms using Weebit’s ReRAM chip. The goal of the project is to demonstrate the capability of ReRAM-based hardware in neuromorphic and artificial intelligence applications.

This is the second Neuromorphic RRAM project that Weebit launches - only recently in November 2018 it announced that it will partner in a similar project with the Non-Volatile Memory Research Group of the Indian Institute of Technology Delhi (IITD).

Read the full story Posted: Jan 20,2019

Strategic Elements and USNW to optimize RRAM technology and develop demonstrator applications

Strategic Elements announces has signed an agreement with the University of New South Wales (UNSW) to further optimize the company's Nanocube Memory Ink flexible/transparent RRAM technology. UNSW and SER will also develop demonstrator applications for the new technology.
Strategic Elements glass-based transparent RRAMprototype

UNSW will begin the research by assessing potential demonstrator applications in areas such as multi-functional capacitive sensors that can detect the type and strength of external stimuli including curvature, pressure, strain, and touch with clear distinction. It will also look into developing memory arrays that will fulfill the growing requirement for local digital data storage on flexible sensors, tags, wearables and high value consumer packaging.

Read the full story Posted: Nov 28,2018