Related papers: Gate-tunable Memristive Phenonmena Mediated by Gra…
Microwave-field distribution, dissipation, and surface impedance are theoretically investigated for superconductors with laminar grain boundaries (GBs). In the present theory we adopt the two-fluid model for intragrain transport current in…
The operation of resistive and phase-change memory (RRAM and PCM) is controlled by highly localized self-heating effects, yet detailed studies of their temperature are rare due to challenges of nanoscale thermometry. Here we show that the…
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…
Memristors provide a tempting solution for weighted synapse connections in neuromorphic computing due to their size and non-volatile nature. However, memristors are unreliable in the commonly used voltage-pulse-based programming approaches…
The advance in designing arrays of ultrathin two-dimensional optical nano-resonators, known as metasurfaces, is currently enabling a large variety of novel flat optical components. The remarkable control over the electromagnetic fields…
Combined diverse two-dimensional (2D) materials for semiconductor interfaces are attractive for electrically controllable carrier confinement to enable excellent electrostatic control. We investigated the transport characteristic in…
We report electrical characterization of monolayer molybdenum disulfide (MoS2) devices using a thin layer of polymer electrolyte consisting of poly(ethylene oxide) (PEO) and lithium perchlorate (LiClO4) as both a contact-barrier reducer and…
Memristive devices have gained significant attention for their potential in next-generation non-volatile memory and neuromorphic computing architectures. Among emerging candidates, transition metal oxides have proven particularly promising.…
The review of studies on memristive properties or effect of resistive switchings in four classes of high temperature superconductors is presented in order to reveal functional properties of HTSCs which become apparent in the effects under…
In recent years, a considerable research effort has shown the energy benefits of implementing neural networks with memristors or other emerging memory technologies. However, for extreme-edge applications with high uncertainty, access to…
Comprehensive understanding of the world's most energy efficient powerful computer, the human brain, is an elusive scientific issue. Still, already gained knowledge indicates memristors can be used as a building block to model the brain. At…
Grain boundary (GB) migration stands as a linchpin process governing microstructural evolution in polycrystalline materials. Over the past decade, the concept of shear coupling, quantified through the shear coupling factor, has transformed…
The superior density of passive analog-grade memristive crossbars may enable storing large synaptic weight matrices directly on specialized neuromorphic chips, thus avoiding costly off-chip communication. To ensure efficient use of such…
The memristor is a device whose resistance changes depending on the polarity and magnitude of a voltage applied to the device's terminals. We design a minimalistic model of a regular network of memristors using structurally-dynamic cellular…
The sensitive dependence of electronic and thermoelectric properties of MoS$_2$ on the applied strain opens up a variety of applications in the emerging area of straintronics. Using first principles based density functional theory…
Grain boundaries (GBs) in polycrystalline materials are powerful sinks for irradiation defects. While standard theories assume that the sink efficiency of a grain boundary is defined solely by its character before irradiation, recent…
When transistor gate insulators have nanometer-scale equivalent oxide thickness (EOT), the gate capacitance ($C_\textrm{G}$) becomes smaller than the oxide capacitance ($C_\textrm{ox}$) due to the quantum capacitance and charge centroid…
Artificial intelligence is widely used in everyday life. However, an insufficient computing efficiency due to the so-called von Neumann bottleneck cannot satisfy the demand for real-time processing of rapidly growing data. Memristive…
Van der Waals heterostructure based on layered two-dimensional (2D) materials offers unprecedented opportunities to create materials with atomic precision by design. By combining superior properties of each component, such heterostructure…
Cuprate superconductors are strongly sensitive materials to disorder and oxygen stoichiometry; even minute variations of those parameters drastically change their electronic properties. Here we exploit this characteristic to engineer a…