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We demonstrate a non-volatile magnetoelectric magnonic memory (MEMM) that enables fully electrical write/read via direct magnon-driven sensing in an insulating antiferromagnet. A fabricated SrIrO3/La-BiFeO3/SrIrO3 trilayer exhibits sub-100…

Engineering phase change materials (PCM) to realize superior data storage devices requires a detailed understanding of crystallization kinetics and its temperature dependence. The temperature dependence of crystallization differs distinctly…

Materials Science · Physics 2021-03-12 Julian Pries , Julia Sehringer , Shuai Wei , Pierre Lucas , Matthias Wuttig

Pr1-xCaxMnO3 (PCMO) based resistance random access memory (RRAM) is attractive in large scale memory and neuromorphic applications as it is non-filamentary, area scalable and has multiple resistance states along with excellent endurance and…

Applied Physics · Physics 2020-04-15 Sandip Lashkare , Udayan Ganguly

Two-dimensional (2D) phase-change materials (PCMs) with moderate transition barriers and distinctly contrasting properties are highly desirable for multifunctional devices, yet such systems remain scarce. Using first-principles…

Materials Science · Physics 2025-10-27 Wenhui Wan , Xinyue Liu , Yanfeng Ge , Ziqang Li , Yong Liu

Transition metal dichalcogenides (TMDs) exist in various crystal structures with semiconducting, semi-metallic, and metallic properties. The dynamic control of these phases is of immediate interest for next generation electronics such as…

Materials Science · Physics 2026-01-21 Dante Zakhidov , Daniel A. Rehn , Evan J. Reed , Alberto Salleo

Due to stringent thermal budgets in cryogenic technologies such as superconducting quantum computers and sensors, minimizing the energy dissipation and power consumption of cryogenic electronic components is pivotal for large-scale devices.…

It is widely agreed that phase change materials (PCMs) are of high interest for sustainable energy future. Many of the applications require anti-leakage properties of PCM, that can be accomplished through PCM encapsulation. In this study,…

As modern computing gets continuously pushed up against the von Neumann Bottleneck -- limiting the ultimate speeds for data transfer and computation -- new computing methods are needed in order to bypass this issue and keep our computer's…

The attention mechanism is a key computing kernel of Transformers, calculating pairwise correlations across the entire input sequence. The computing complexity and frequent memory access in computing self-attention put a huge burden on the…

Hardware Architecture · Computer Science 2024-10-31 Ashkan Moradifirouzabadi , Divya Sri Dodla , Mingu Kang

We study the first order phase transition of the fixed-connectivity triangulated surface model using the Parallel Tempering Monte Carlo (PTMC) technique on relatively large lattices. From the PTMC results, we find that the transition is…

Soft Condensed Matter · Physics 2016-01-29 Satoshi Usui , Hiroshi Koibuchi

Extremely increased unstructured data brought by the large-scale intelligent sensing devices application have big challenges not only in data storing and processing but also power consumption surging. Therefore, to improve energy efficiency…

Neural and Evolutionary Computing · Computer Science 2025-05-28 Jialin Liu , Diansheng Liao

This work introduces a fully tunable, ultra-low power unipolar memory cell inspired by the Schmitt-trigger comparator and designed in CMOS using only nine transistors. The proposed circuit operates entirely in the current domain and…

Signal Processing · Electrical Eng. & Systems 2026-05-19 Arthur Fyon , Loris Mendolia , Jean-Michel Redouté , Alessio Franci , Guillaume Drion

Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from…

Memristive devices have been considered promising candidates for nature-inspired computing and in-memory information processing. However, experimental devices developed to date typically show significant variability and function at…

Applied Physics · Physics 2025-08-25 Yuriy V. Pershin , Liya Patel , Bapi Berra , Doug Aaron , Stephen A. Sarles

Recent advances in memory technologies, devices and materials have shown great potential for integration into neuromorphic electronic systems. However, a significant gap remains between the development of these materials and the realization…

The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but…

Emerging Persistent Memory technologies (also PM, Non-Volatile DIMMs, Storage Class Memory or SCM) hold tremendous promise for accelerating popular data-management applications like in-memory databases. However, programmers now need to deal…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-05 Ellis Giles , Kshitij Doshi , Peter Varman

A prominent characteristic of write operation in Phase-Change Memory (PCM) is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content…

Hardware Architecture · Computer Science 2020-05-12 Shihao Song , Anup Das , Onur Mutlu , Nagarajan Kandasamy

Among all the properties required for the design of the next generation of PCM (density, heat capacity, thermal expansion, latent energy, volume change upon melting, corrosion rate, etc.) the thermal transport properties are by far the…

Materials Science · Physics 2021-09-28 Anh Thu Phan , Aïmen E. Gheribi , Patrice Chartrand

With the help of quantum mechanics one can formulate a model of associative memory with optimal storage capacity. I generalize this model by introducing a parameter playing the role of an effective temperature. The corresponding…

Quantum Physics · Physics 2009-11-07 Carlo A. Trugenberger