相关论文: Process Optimization and Downscaling of a Single E…
In Phys. Rev. Lett. 91 167206 (2003), Sun et al. study memory effects in an interacting nanoparticle system with specific temperature and field protocols. The authors claim that the observed memory effects originate from spin-glass dynamics…
Neuromorphic or neurally-inspired optimizers rely on local but parallel parameter updates to solve problems that range from quadratic programming to Ising machines. An ideal realization of such an optimizer not only uses a compute-in-memory…
We propose a new type of magnetoelectric memory device that stores magnetic easy-axis information or pseudo-magnetization, rather than a definite magnetization direction, in piezoelectric/ferromagnetic (PE/FM) heterostructures.…
The application of nanocrystals as heterogeneous catalysts and plasmonic nanoparticles requires fine control of their shape and chemical composition. A promising idea to achieve synergistic effects is to combine two distinct chemical and/or…
Memory devices operating due to the fast proton transfer (PT) process are proposed by means of the first-principles calculations. Writing an information is performed using the electrostatic potential of the scanning tunneling microscopy…
The progress in the semiconductor industry has resulted in great demand for high-frequency magnetic materials applicable in microfabricated inductor cores. Nanocomposite materials, containing magnetic nanoparticles in a non-conducting…
Stimulus-responsive shape memory materials have attracted tremendous research interests recently, with much effort focused on improving their mechanical actuation. Driven by the needs of nanoelectromechnical devices, materials with large…
We present a detailed electron diffraction study of individual single-walled carbon nanotubes. A novel sample preparation procedure provides well-separated, long and straight individual single-shell nanotubes. Diffraction experiments are…
Analog crossbar arrays consisting of emerging memory devices can greatly alleviate the computational strain required by vector matrix multiplications for neural network applications. The ability to produce spin orbit torque-magnetic…
Modern opto-electronic devices are based on semiconductor heterostructures employing the process of electron-hole pair annihilation. In particular polar materials enable a variety of classic and even quantum light sources, whose on-going…
The synapse is a key element of neuromorphic computing in terms of efficiency and accuracy. In this paper, an optimized current-controlled memristive synapse circuit is proposed. Our proposed synapse demonstrates reliability in the face of…
Silicon quantum computing has the potential to revolutionize technology with capabilities to solve real-life problems that are computationally complex or even intractable for modern computers [1] by offering sufficient high quality qubits…
Recent advances in nanofluidics have enabled the confinement of water down to a single molecular layer. Such monolayer electrolytes show promise in achieving bio-inspired functionalities through molecular control of ion transport. However,…
Neuromorphic hardware platforms can significantly lower the energy overhead of a machine learning inference task. We present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-…
Single particle cryo-electron microscopy has become a critical tool in structural biology over the last decade, able to achieve atomic scale resolution in three dimensional models from hundreds of thousands of (noisy) two-dimensional…
Computational experiments are exploited in finding a well-designed processing path to optimize material structures for desired properties. This requires understanding the interplay between the processing-(micro)structure-property linkages…
In many cases, the behavior of physical memristive devices can be relatively well captured by using a single internal state variable. This study investigates the low-power control of first-order memristive devices to derive the most…
Memory effects are ubiquitous in nature and are particularly relevant at the nanoscale where the dynamical properties of electrons and ions strongly depend on the history of the system, at least within certain time scales. We review here…
NAND flash memory is ubiquitous in everyday life today because its capacity has continuously increased and cost has continuously decreased over decades. This positive growth is a result of two key trends: (1) effective process technology…
The magnetic properties of single-domain nanoparticles with different geometric shapes, crystalline anisotropies and lattice structures are investigated. A recently proposed scaling approach is shown to be universal and in agreement with…