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Computing inspired by the human brain requires a massive parallel architecture of low-power consuming elements of which the internal state can be changed. SrTiO3 is a complex oxide that offers rich electronic properties; here Schottky…

Applied Physics · Physics 2018-10-17 A. S. Goossens , A. Das , T. Banerjee

It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive…

Neural and Evolutionary Computing · Computer Science 2012-11-26 Farnood Merrikh-Bayat , Saeed Bagheri Shouraki , Iman Esmaili Paeen Afrakoti

In this paper, we present the numerical analysis and simulations of a multi-dimensional memristive device model. Memristive devices and memtransistors based on two-dimensional (2D) materials have demonstrated promising potential for…

Memristors are emerging as key electronic components that retain resistance states without power. Their non-volatile nature and ability to mimic synaptic behavior make them ideal for next-generation memory technologies and neuromorphic…

Mesoscale and Nanoscale Physics · Physics 2025-10-28 Tongxin Chen , Yinyu Nie , Yafei Hao , Shengchun Shen , Jiajun Pan , Xiaoguang Li , Yuan Lu

Memristors have been intensively studied in recent years as promising building blocks for next-generation non-volatile memory, artificial neural networks and brain-inspired computing systems. Even though the environment adaptability of…

Materials Science · Physics 2019-02-26 Nan Yang , Zhong-Qi Ren , Zhao Guan , Bo-Bo Tian , Ni Zhong , Ping-Hua Xiang , Chun-Gang Duan , Jun-Hao Chu

The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric…

Materials Science · Physics 2016-06-23 Jianxin Shen , Junzhuang Cong , Dashan Shang , Yisheng Chai , Shipeng Shen , Kun Zhai , Young Sun

Heavy computational demands from artificial intelligence (AI) leads the research community to explore the design space for functional materials that can be used for high performance memory and neuromorphic computing hardware. Novel device…

Materials Science · Physics 2024-09-04 Xinye Li , Padma Srivari , Sayani Majumdar

Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention in neuromorphic computing since they can be used as a tool…

Optimization and Control · Mathematics 2024-09-24 Marieke Heidema , Henk van Waarde , Bart Besselink

Spintronics has gone through substantial progress due to its applications in energy-efficient memory, logic and unconventional computing paradigms. Multilayer ferromagnetic thin films are extensively studied for understanding the domain…

Using metal-ferroelectric junctions as switchable diodes was proposed several decades ago. This was shown to actually work in PbZr(1-x)TixO3 (PZT) by Blom et al. [P.W. M. Blom et al., Phys. Rev. Lett. 73, 2107 (1994)], who reported…

Materials Science · Physics 2012-12-04 Saeedeh Farokhipoor , Beatriz Noheda

Smart electronic circuits that support neuromorphic computing on the hardware level necessitate materials with memristive, memcapacitive, and neuromorphic-like functional properties; in short, the electronic response must depend on the…

Neuromorphic computing architectures enable the dense co-location of memory and processing elements within a single circuit. This co-location removes the communication bottleneck of transferring data between separate memory and computing…

Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility features, they are characterized by computationally relevant physical properties, such as…

Emerging Technologies · Computer Science 2018-07-18 Melika Payvand , Manu V Nair , Lorenz K. Muller , Giacomo Indiveri

While two-terminal HfOX (x<2) memristor devices have been studied for ion transport and current evolution, there have been limited reports on the effect of the long-range thermal environment on their performance. In this work,…

Artificial neural networks (ANNs) have had an enormous impact on a multitude of sectors, from research to industry, generating an unprecedented demand for tailor-suited hardware platforms. Their training and execution is highly…

Applied Physics · Physics 2025-02-18 Daniele Nazzari , Lukas Wind , Masiar Sistani , Dominik Mayr , Kihye Kim , Walter M. Weber

My research is dedicated to the electronic properties of functional oxides. My activity specifically focuses on ferroelectric tunnel junctions in which an ultrathin layer of ferroelectric material is intercalated between two metallic…

Materials Science · Physics 2020-11-17 Vincent Garcia

The transition to smart wearable and flexible optoelectronic devices communicating with each other and performing neuromorphic computing at the edge is a big goal in next-generation optoelectronics. These devices should perform their…

The ever-increasing amount of data from ubiquitous smart devices fosters data-centric and cognitive algorithms. Traditional digital computer systems have separate logic and memory units, resulting in a huge delay and energy cost for…

Applied Physics · Physics 2025-03-17 Qiming Shao , Zhongrui Wang , Yan Zhou , Shunsuke Fukami , Damien Querlioz , Leon O. Chua

Memristive circuit elements constitute a cornerstone for novel electronic applications, such as neuromorphic computing, called to revolutionize information technologies. By definition, memristors are sensitive to the history of electrical…

In the quest for reliable and power-efficient memristive devices, ferroelectric tunnel junctions are being investigated as potential candidates. CMOS-compatible ferroelectric hafnium oxides are at the forefront. However, in epitaxial tunnel…