The rapid increase in information in the big-data era calls for changes to information-processing paradigms, which, in turn, demand new circuit-building blocks to overcome the decreasing cost-effectiveness of transistor scaling and the intrinsic inefficiency of using transistors in non-von Neumann computing architectures. Accordingly, resistive switching materials (RSMs) based on different physical principles have emerged for memories that could enable energy-efficient and area-efficient in-memory computing. In this Review, we survey the four physical mechanisms that lead to such resistive switching: redox reactions, phase transitions, spin-polarized tunnelling and ferroelectric polarization. We discuss how these mechanisms equip RSMs with desirable properties for representation capability, switching speed and energy, reliability and device density. These properties are the key enablers of processing-in-memory platforms, with applications ranging from neuromorphic computing and general-purpose memcomputing to cybersecurity. Finally, we examine the device requirements for such systems based on RSMs and provide suggestions to address challenges in materials engineering, device optimization, system integration and algorithm design. Resistive switching materials enable novel, in-memory information processing, which may resolve the von Neumann bottleneck. This Review focuses on how the switching mechanisms and the resultant electrical properties lead to various computing applications.

Resistive switching materials for information processing

Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)-based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.

https://science.sciencemag.org/content/sci/early/2019/08/21/science.aay0291.full.pdf

Phase-change heterostructure enables ultralow noise and drift for memory operation

Memory materials and devices: From concept to application

Recent Advances on Neuromorphic Devices Based on Chalcogenide Phase-Change Materials

Fifty years after its discovery, the ovonic threshold switching (OTS) phenomenon, a unique nonlinear conductivity behavior observed in some chalcogenide glasses, has been recently the source of a real technological breakthrough in the field of data storage memories. This breakthrough was achieved because of the successful 3D integration of so-called OTS selector devices with innovative phase-change memories, both based on chalcogenide materials. This paves the way for storage class memories as well as neuromorphic circuits. We elucidate the mechanism behind OTS switching by new state-of-the-art materials using electrical, optical, and x-ray absorption experiments, as well as ab initio molecular dynamics simulations. The model explaining the switching mechanism occurring in amorphous OTS materials under electric field involves the metastable formation of newly introduced metavalent bonds. This model opens the way for design of improved OTS materials and for future types of applications such as brain-inspired computing.

Toward ultimate nonvolatile resistive memories: The mechanism behind ovonic threshold switching revealed

In phase-change memory devices, a material is cycled between glassy and crystalline states. The highly temperature-dependent kinetics of its crystallization process enables application in memory technology, but the transition has not been resolved on an atomic scale. Using femtosecond x-ray diffraction and ab initio computer simulations, we determined the time-dependent pair-correlation function of phase-change materials throughout the melt-quenching and crystallization process. We found a liquid–liquid phase transition in the phase-change materials Ag4In3Sb67Te26 and Ge15Sb85 at 660 and 610 kelvin, respectively. The transition is predominantly caused by the onset of Peierls distortions, the amplitude of which correlates with an increase of the apparent activation energy of diffusivity. This reveals a relationship between atomic structure and kinetics, enabling a systematic optimization of the memory-switching kinetics.

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Pererik Andreasson

Papers

Femtosecond x-ray diffraction reveals a liquid–liquid phase transition in phase-change materials