Related papers: Single-electron tunneling PbS/InP neuromorphic com…

We report measurements of charge configurations and charge transfer dynamics in a hybrid single-electron box composed of aluminum and copper. We used two single-electron transistors (SETs) to simultaneously read out different parts of the…

We measure electron tunneling via discrete energy levels in ferromagnetic cobalt particles less than 4 nm in diameter, using non-magnetic electrodes. Due to magnetic anisotropy, the energy of each tunneling resonance shifts as an applied…

We analyze the operation of the wireless single-electron logic family based on single-electron-parametron cells. Parameter margins, energy dissipation, and the error probability are calculated using the orthodox theory of single-electron…

Non-equilibrium Greens function techniques (NEGF) combined with Density Functional Theory (DFT) calculations have become a standard tool for the description of electron transport through single molecule nano-junctions in the coherent…

Recent experiments about the low temperature behaviour of a Single Wall Carbon Nanotube (SWCNT) showed typical Coulomb Blockade (CB) peaks in the zero bias conductance and allowed us to investigate the energy levels of interacting…

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…

A simple and highly reproducible single electron transistor (SET) has been fabricated using gated silicon nanowires. The structure is a metal-oxide-semiconductor field-effect transistor made on silicon-on-insulator thin films. The channel…

We introduce the percolation with plasticity (PWP) systems that exhibit neuromorphic functionalities including multi-valued memory, random number generation, matrix-vector multiplication, and associative learning. PWP systems have multiple…

We investigate spin and charge dynamics of a quantum dot of phosphorus atoms coupled to a radio-frequency single-electron transistor (rf-SET) using full counting statistics. We show how the magnetic field plays a role in determining the…

Recent experimental demonstrations of quantum coherence of the charge and flux states of Josephson junctions show that the quantum Josephson dynamics can be used to develop scalable quantum logic circuits. In this work, I review the basic…

We demonstrate the fabrication of a single electron transistor device based on a single ultra-small silicon quantum dot connected to a gold break junction with a nanometer scale separation. The gold break junction is created through a…

We present topological insulator (TI)-based single-electron transistors (SETs) as magnetic-field-compatible charge sensing devices that are easily integrable with TI-superconductor hybrid platforms. We observe well-resolved Coulomb diamonds…

We offer a general approach to calculation of single-electron tunneling spectra and conductance of a shuttle oscillating between two half-metallic leads with fully spin polarized carriers. In this case the spin-flip processes are completely…

One of the most challenging obstacles to realizing exascale computing is minimizing the energy consumption of L2 cache, main memory, and interconnects to that memory. For promising cryogenic computing schemes utilizing Josephson junction…

Various aspects of single-electron memory are discussed. In particular, we analyze the single-electron charging by Fowler-Nordheim tunneling, propose the idea of background charge compensation, and discuss the defect-tolerant architecture…

Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied…

The escalating energy demands of artificial intelligence pose a critical challenge to conventional computing. Leveraging the efficiency of event-driven, in-memory neuromorphic architectures into the superconducting circuits with ultra-high…

Standard Spiking Neural Network (SNN) models typically neglect metabolic constraints, treating neurons as energetically unconstrained components. We bridge this gap by implementing a conductance-based leaky integrate-and-fire (gLIF)…

We report on an artificial synapse, an organic synapse-transistor (synapstor) working at 1 volt and with a typical response time in the range 100-200 ms. This device (also called NOMFET, Nanoparticle Organic Memory Field Effect Transistor)…

Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of powerful, energy-efficient, and adaptive neuromorphic processing systems. A large number of…