Related papers: Characterizing Germanium Junction Transistors
Estimates of the exchange interaction parameter (J) between electronic magnetic momenta residing in the d-shells of several divalent first row transition metal ions, and those residing on the [TCNE]$^-$. anion-radicals (TCNE =…
Equivariant Graph Neural Networks (eGNNs) trained on density-functional theory (DFT) data can potentially perform electronic structure prediction at unprecedented scales, enabling investigation of the electronic properties of materials with…
This paper introduces a robust Pareto design approach for transistor sizing of Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs), particularly for power amplifier (PA) and low-noise amplifier (LNA) designs in 5G applications.…
The creation of point defects in the crystal lattices of various semiconductors by subthreshold events has been reported on by a number of groups. These observations have been made in great detail using sensitive electrical techniques but…
The break-down of the Born-Oppenheimer approximation is an important topic in chemical dynamics on metal surfaces. In this context, the most frequently used "work-horse" is electronic friction theory, commonly relying on friction…
In machine-learning-assisted high-throughput defect studies, a defect-aware latent representation of the supercell structure is crucial to the accurate prediction of defect properties. The performance of current graph neural network (GNN)…
The Gas Electron Multiplier (GEM) detector is one of promising particle and radiation detectors that has been improved greatly from previous gas detectors. The improvement includes better spatial resolutions, higher detection rate…
The development of semiconductor electronics is shortly reviewed, beginning with the development of germanium devices (band gap $E_g=0.66$ eV) after world war II. Quickly a tendency to alternative materials with wider band gap became…
Elastic form factors provide information about the low energy structure of composite particles.Recent double polarization coincidence experiments significantly improved our knowledge of proton and neutron form factors. Recoil polarization…
Reconfigurable magnetic tunnel diodes and transistors are a new concept in spintronics. The realization of such a device requires the use of materials with unique spin-dependent electronic properties such as half-metallic magnets (HMMs) and…
Embedding layers in transformer-based NLP models typically account for the largest share of model parameters, scaling with vocabulary size but not yielding performance gains proportional to scale. We propose an alternative approach in which…
The convergence of GD and SGD when training mildly parameterized neural networks starting from random initialization is studied. For a broad range of models and loss functions, including the most commonly used square loss and cross entropy…
We study parameter estimation for interacting particle systems (IPSs) consisting of $N$ weakly interacting multivariate hypoelliptic SDEs. We propose a locally Gaussian approximation of the transition dynamics, carefully designed to address…
Dark matter plays a crucial role in our comprehension of the universe, but its mysterious nature poses challenges for direct detection. A primary obstacle in detecting dark matter is distinguishing genuine signals from the prevailing…
Down-scaling device dimensions to the nanometer range raises significant challenges to traditional device design, due to potential current leakage across nanoscale dimensions and the need to maintain reproducibility while dealing with…
Using the partition-free time-dependent Landauer-B{\"u}ttiker formalism for transient current correlations, we study the traversal times taken for electrons to cross graphene nanoribbon (GNR) molecular junctions. We demonstrate electron…
Half-Heusler compounds (space group Fm3m) has garnered increasing attention in recent years in the thermoelectric community. Three decades ago, refractory RNiSn half-Heusler compounds (R represents refractory metals such as Hf, Zr, Ti) were…
Capacitance-voltage characteristics of individual germanium nanowire field effect transistors were directly measured and used to assess carrier mobility in nanowires for the first time; thereby removing uncertainties in calculated mobility…
This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian Process Regression (GPR) and Support Vector Regression (SVR). Although GPR is a competent model for…
Realizing a controllable network with multiple degrees of interaction is a challenge to physics and engineering. Here, we experimentally report an on-chip reconfigurable network based on nanoelectromechanical resonators with…