Memory devices

Researchers from ITMO University, Ioffe Institute of Physics and Technology and Harbin University of Engineering have developed a stable perovskite nanomemristor that can withstand more than 1,500 rewrite cycles and does not degrade after months. In addition, the researchers achieved record-low values of size and energy consumption - 70-80 nanowatts for a 130-160 nanometer perovskite single crystal. 

(a) A schematic illustration of a perovskite nanomemristor based on a single crystal on indium tin oxide (ITO) contacted with boron-doped diamond (BDD). (b) Scanning top view of the perovskite nanocrystals array. (c) Electron diffraction image of an individual CsPbBr₃ nanocrystal. (d) Raman spectra obtained from the single-crystals array. Image from: Opto-Electronic Advances 

This achievement could pave the way for ultracompact memristors and enable faster and more energy-efficient ultra-compact processors for neuromorphic computing. 

The properties of 3D halide perovskites, such as mixed ionic–electronic conductivity and feasible ion migration, have enabled them to challenge traditional memristive materials. However, issues like poor moisture stability and difficulty in controlling ion transport due to their polycrystalline nature have hindered their use as a neuromorphic hardware. Recently, 2D halide perovskites have emerged as promising artificial synapses owing to their phase versatility, microstructural anisotropy in electrical and optoelectronic properties, and excellent moisture resistance. However, their asymmetrical and nonlinear conductance changes still limit the efficiency of training and accuracy of inference. 

Now, researchers from Seoul National University, Korea University, Sungkyunkwan University, Pohang University of Science and Technology and University of Southern California have achieved highly linear and symmetrical conductance changes in Dion–Jacobson 2D perovskites. 

As an increasing amount of multimodal sensors are used in intelligent electronics, energy expenditure gets more massive. Consequently, researchers aim to develop efficient computing paradigms or integrate energy harvesting from ambient sources. Halide perovskites possess unique photophysics and coupled ionic-electronic dynamics that actualize memory devices for brain-inspired computing. Synergizing the computing capability with their conventional light harvesting efficacy could address this issue. 

Researchers from Singapore's Nanyang Technological University and Hong Kong's City University of Hong Kong recently examined the use of halide perovskite photovoltaics for in-sensor reservoir computing (RC). 

Researchers from China's Shenzhen Campus of Sun Yat-sen University have reported a new type of two-terminal self-rectifying memristor that gets rid of asymmetric complex structures by using CsPbBr₃ perovskite nanocrystals (NCs). The integration of rectifying effects with resistance switching in a self-rectifying memristor offers the opportunity to suppress the sneak current in high-density crossbar arrays for energy-efficient neuromorphic computing.

This study demonstrates the possibility of constructing controllable self-rectifying memristors without involving asymmetric complex structures, paving a new way for resolving the sneak current issue in crossbar arrays of memristors. 

Researchers from Japan's Tohoku University and University of Tsukuba have reported a breakthrough in the development of non-volatile phase change memory−a type of electronic memory that can store data even when the power is turned off−using a perovskite-derivative nickelate material.

Until now, phase change memory has primarily been developed using chalcogenides, a group of materials known to exhibit reversible electrical changes when they transition between their crystalline and amorphous states. However, in their recent study, the researchers reported thermally reversible switching of room-temperature electrical resistivity in a layered nickelate−potentially offering better performance and superior sustainability.

The human brain can effortlessly process complex sensory information and learn from experiences, while a computer cannot. And, the brain does all this by consuming less than half as much energy as a laptop. One of the reasons for the brain's energy efficiency is its structure. The individual brain cells – the neurons and their connections, the synapses – can both store and process information. In computers, however, the memory is separate from the processor, and data must be transported back and forth between these two components. The speed of this transfer is limited, which can slow down the whole computer when working with large amounts of data.

One possible solution to this problem are novel computer architectures that are modeled after the human brain. To this end, scientists are developing 'memristors': components that, like brain cells, combine data storage and processing. A team of researchers from Empa, ETH Zurich and the Politecnico di Milano has developed a memristor based on perovskite materials that is more powerful and easier to manufacture than its predecessors.

Researchers from National Taiwan Normal University and Kyushu University have developed a new memory device, readable through both electrical and optical methods, that needs only perovskites to simultaneously store and visually transmit data.

Schematic of the CsPbBr3 QD-based LEM device. Image from Nature Communications

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.'

A research team led by Professor Jang-Sik Lee of Pohang University of Science and Technology (POSTECH) has developed a halide perovskite-based memory with ultra-fast switching speed.

Resistive switching memory is a promising contender for next-generation memory device due to its advantages of simple structure and low power consumption. Various materials have been previously studied for resistive switching memory. Among them, halide perovskites are receiving much attention for use in the memory because of low operation voltage and high on/off ratio. However, halide perovskite-based memory devices have limitations like slow switching speed which hinder their practical application in memory devices.

Researchers at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) have reported a breakthrough in energy-efficient phototransistors - devices that could someday help computers process visual information similarly to the human brain and be used as sensors in applications like self-driving vehicles.

The structures rely on metal-halide perovskites. Jeffrey Blackburn, a senior scientist at NREL and co-author of a new paper outlining the research, said: 'In general, these perovskite semiconductors are a really unique functional system with potential benefits for a number of different technologies'. 'NREL became interested in this material system for photovoltaics, but they have many properties that could be applied to whole different areas of science.'

Researchers at Linköping University in Sweden have announced the development of an optoelectronic magnetic double perovskite. The discovery could open the door to combining spintronics with optoelectronics for rapid and energy-efficient information storage.

The team explains that one type of perovskite that contains halogens and lead has recently been shown to have interesting magnetic properties, opening the possibility of using it in spintronics. Spintronics is thought to have huge potential for the next generation of information technology, since information can be transmitted at higher speeds and with low energy consumption. However, magnetic properties of halide perovskites have until now been associated only with lead-containing perovskites, which has limited the development of the material for both health and environmental reasons.