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Dynamic functional connectivity is an effective measure for the brain's responses to continuous stimuli. We propose an inferential method to detect the dynamic changes of brain networks based on time-varying graphical models. Whereas most…
Fluid ferroelectrics, a recently discovered class of liquid crystals that exhibit switchable, long-range polar order, offer opportunities in ultrafast electro-optic technologies, responsive soft matter, and next-generation energy materials.…
We examine spin dependent transport in a quantum interferometer composed of magnetic atomic sites based on transfer matrix formalism. The interferometer, threaded by a magnetic flux $\phi$, is symmetrically attached to two semi-infinite…
Neuromorphic computing (NC) architecture has shown its suitability for energy-efficient computation. Amongst several systems, spin-orbit torque (SOT) based domain wall (DW) devices are one of the most energy-efficient contenders for NC. To…
A large number of simulation models have been proposed over the years to mimic the electrical behaviour of memristive devices. The models are based either on sophisticated mathematical formulations that do not account for physical and…
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…
Ferroelectric memristors are intensively studied due to their potential implementation in data storage and processing devices. In this work we show that the memristive behavior of metal/ferroelectric oxide/metal devices relies on the…
Stochastic diffusion processes are pervasive in nature, from the seemingly erratic Brownian motion to the complex interactions of synaptically-coupled spiking neurons. Recently, drawing inspiration from Langevin dynamics, neuromorphic…
Ferroelectric field-effect transistors (FE-FETs) consisting of tunable dielectric layers are utilized to investigate interfacial transport processes. Large changes in the dielectric constant as a function of temperature are observed in…
We theoretically analyzed inelastic effects in the electron transport through molecular junctions originating from electron-vibron interactions. The molecular bridge was simulated by a periodic chain of identical interacting hydrogen-like…
A spin field effect transistor (FET) is proposed by utilizing a graphene nanoribbon as the channel. Similar to the conventional spin FETs, the device involves ferromagnetic metals as a source and drain; they, in turn, are connected to the…
Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic…
All-electric-controlled nonvolatile spin field-effect transistors (SFETs) based on two-dimensional (2D) multiferroic van der Waals (vdW) heterostructures hold great promise for advanced spintronics applications. However, their performance…
Brain-inspired neuromorphic computing which consist neurons and synapses, with an ability to perform complex information processing has unfolded a new paradigm of computing to overcome the von Neumann bottleneck. Electronic synaptic…
Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of…
This paper discusses how classical transport theories such as the thermionic emission, can be used as a powerful tool for the study and the understanding of the most complex mechanisms of transport in Fin Field Effect Transistors (FinFETs).…
This study investigates how dynamical systems may be learned and modelled with a neuromorphic network which is itself a dynamical system. The neuromorphic network used in this study is based on a complex electrical circuit comprised of…
Biological neuronal networks are characterized by nonlinear interactions and complex connectivity. Given the growing impetus to build neuromorphic computers, understanding physical devices that exhibit structures and functionalities similar…
We present an in-house modelling framework for Ferroelectric Tunnelling Junctions (FTJ), and an insightful study of the design of FTJs as synaptic devices. Results show that a moderately low-k tunnelling dielectric (e.g. SiO2) can increase…
A novel nanoelectronic device is constructed by graphyne that is robustly connected between graphene electrodes, where graphyne is composed of hexagonal carbon rings and carbon chains. Owing to similarities between the bond lengths and unit…