相关论文: Electric Field Driven Memristive Behavior at the S…
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their electrical resistance in response to stimuli, similar to…
Both analog and digital resistive switching are essential components in the neuromorphic computing system. This work reports the influence of Cu ions for the transformation of analog to digital resistive switching in ITO/NiO/Ag memristor…
Ferroelectric polar displacements have recently been observed in conducting electron-doped BaTiO3. The co-existence of a ferroelectric phase and conductivity opens the door to new functionalities which may provide a unique route for novel…
Memristors are an electronic device whose resistance depends on the voltage history that has been applied to its two terminals. Despite its clear advantage as a computational element, a suitable transport model is lacking for the special…
We have investigated electron transport in Nb doped SrTiO$_3$ single crystals for two doping densities. We find that the resistivity and mobility are temperature dependent in both whereas the carrier concentration is almost temperature…
The memristive device is one of the basic elements of novel, brain-inspired, fast, and energy-efficient information processing systems in which there is no separation between memorization and information analysis functions. Since the first…
Memristors are considered key building blocks for the development of neuromorphic computing hardware. For ferroelectric memristors with a capacitor-like structure, the polarization direction modulates the height of the Schottky barriers --…
The areal footprint of memristors is a key consideration in material-based neuromorophic computing and large-scale architecture integration. Electronic transport in the most widely investigated memristive devices is mediated by filaments,…
Enhancing the switching speed of oxide-based memristive devices at a low voltage level is crucial for their use as non-volatile memory and their integration into emerging computing paradigms such as neuromorphic computing. Efforts to…
The great potential of memristive devices for real-world applications still relies on overcoming key technical challenges, including the need for a larger number of stable resistance states, faster switching speeds, lower SET/RESET…
The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS…
SrRuO3 (SRO), a conducting transition metal oxide, is commonly used for engineering domains in BiFeO3. New oxide devices can be envisioned by integrating SRO with an oxide semiconductor as Nb doped SrTiO3 (Nb:STO). Using a three-terminal…
The possibility to develop neuromorphic computing devices able to mimic the extraordinary data processing capabilities of biological systems spurs the research on memristive systems. Memristors with additional functionalities such as robust…
Memristors have attracted interest as neuromorphic computation elements because they show promise in enabling efficient hardware implementations of artificial neurons and synapses. We performed measurements on interface-type memristors to…
Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and…
We observed a strong modulation in the current-voltage characteristics of SrRuO$_3$/Nb:SrTiO$_3$ Schottky junctions by Mn substitution in SrRuO$_3$, which induces a metal-insulator transition in bulk. The temperature dependence of the…
The human brain, with its energy-efficient and massively parallel architecture seamlessly integrates memory and computation. Its topology and functionality serve as the inspiration for the field of neuromorphic computing. Realizing…
The computational efficiency of the human brain is believed to stem from the parallel information processing capability of neurons with integrated storage in synaptic interconnections programmed by local spike triggered learning rules such…
Memristive devices whose resistance can be hysteretically switched by electric field or current are intensely pursued both for fundamental interest as well as potential applications in neuromorphic computing and phase-change memory. When…
Valence change memory (VCM) cells based on SrTiO$_3$ (STO), a perovskite oxide, are a promising type of emerging memory device. While the operational principle of most VCM cells relies on the growth and dissolution of one or multiple…