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The shape of a nanomechanical resonator profoundly affects its mechanical properties and determines its suitability for various applications, such as ultra-sensitive mass and force detection. Despite the promise of two-dimensional…
The rising energy demands of conventional AI systems underscore the need for efficient computing technologies like brain-inspired computing. Physical reservoir computing (PRC), leveraging the nonlinear dynamics of physical systems for…
The prospects of application of graphene and related structures as the membrane mimetic materials, capable of reproducing several biomembrane functions up to the certain limit, are analyzed in the series of our papers. This paper considers…
Advanced neural interfaces mediate a bio-electronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading…
The influence of spatial confinement on the thermally excited stochastic cation dynamics of the room-temperature ionic liquid 1-N-butylpyridinium bis-((trifluoromethyl)sulfonyl)imide ([BuPy][Tf_2N]) inside porous carbide-derived carbons…
Ionic liquids constrained at interfaces or restricted in subnanometric pores are increasingly employed in modern technologies, including energy applications. Understanding the details of their behavior in these conditions is therefore…
Graphene is a promising platform for spin-based non-volatile memory, logic, and neuromorphic computing by combining long-distance spin transport with electrical tunability at room temperature. However, advancing beyond passive spin channels…
Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tuneable conductivity properties enable the imitation of synaptic behaviour. Multipore nanofluidic memristors have shown their…
The long spin-diffusion length, spin-lifetimes and excellent optical absorption coefficient of graphene provide an excellent platform for building opto-electronic devices as well as spin-based logic in a nanometer regime. In this study, by…
Neuromorphic computing devices attempt to emulate features of biological nervous systems through mimicking the properties of synapses, towards implementing the emergent properties of their counterparts, such as learning. Inspired by recent…
Nanopore membranes are a versatile platform for a wide range of applications ranging from medical sensing to filtration and clean energy generation. To attain high-flux rectifying ionic flow, it is required to produce short channels…
Ionic Coulomb blockade in nanopores is a phenomenon that shares some similarities but also differences with its electronic counterpart. Here, we investigate extensively this phenomenon using all-atom molecular dynamics of ionic transport…
Fundamental understanding of ionic transport at the nanoscale is essential for developing biosensors based on nanopore technology and new generation high-performance nanofiltration membranes for separation and purification applications. We…
Synaptic plasticity, the dynamic tuning of signal transmission strength between neurons, serves as a fundamental basis for memory and learning in biological organisms. This adaptive nature of synapses is considered one of the key features…
Graphene nanopore based sensor devices are exhibiting the great potential for the detection of DNA. To understand the fundamental aspects of DNA translocating through a graphene nanopore, in this work, molecular dynamics (MD) simulations…
Porous media is widely distributed in nature, found in environments such as soil, rock formations, and plant tissues, and is crucial in applications like subsurface oil and gas extraction, medical drug delivery, and filtration systems.…
Ordered graphene nanodisk arrays have been successfully fabricated by combining nanosphere lithography (NSL) and reactive ion etching (RIE) processes. The dimension of graphene nanodisks can be effectively tuned by varying the size of…
Nanofluidics, the field interested in flows at the smallest scales, has grown at a fast pace, reaching an ever finer control offluidic and ionic transport at the molecular level. Still, artificial pores are far from reaching the wealth of…
Quantum interference in nano-electronic devices could lead to reduced-energy computing and efficient thermoelectric energy harvesting. When devices are shrunk down to the molecular level it is still unclear to what extent electron…
We have calculated the key characteristics of associative (content-addressable) spatial-temporal memories based on neuromorphic networks with restricted connectivity - "CrossNets". Such networks may be naturally implemented in…