Related papers: Characterizing Germanium Junction Transistors
The continuous development of superconducting electronics is encouraging several studies on hybrid Josephson junctions (JJs) based on superconductor/ferromagnet/superconductor (SFS) heterostructures, as either spintronic devices or…
We analyse the bipartite dynamic network of inventors and patents registered within the main area of electrical engineering in Germany to explore the driving forces behind innovation. The data at hand leads to a bipartite network, where an…
Graph neural networks (GNNs) are effective models for representation learning on relational data. However, standard GNNs are limited in their expressive power, as they cannot distinguish graphs beyond the capability of the Weisfeiler-Leman…
We present a novel unifying interpretation of excess event rates observed in several dark matter direct-detection experiments that utilize single-electron threshold semiconductor detectors. Despite their different locations, exposures,…
Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, and catalysis. In this study, we propose a novel approach…
This paper introduces a simplified and design-oriented version of the EPFL HEMT model [1], focusing on the normalized transconductance-to-current characteristic (Gm/ID ). Relying on these figures, insights into GaN HEMT modeling in relation…
Nernst effect, a transverse electric current induced by a temperature gradient, is a promising tool for revealing emergent phases of condensed matter. We find a Nernst coefficient plateau in low carrier density topological insulators, as a…
Large pretrained models, coupled with fine-tuning, are slowly becoming established as the dominant architecture in machine learning. Even though these models offer impressive performance, their practical application is often limited by the…
Our paper presents a non-destructive thermal transient measurement method that is able to reveal differences even in the micron size range of MEMS structures. Devices of the same design can have differences in their sacrificial layers as…
Gapped metals, a recently proposed class of materials, possess a band gap slightly above or below the Fermi level, behaving as intrinsic p- or n-type semiconductors without requiring external doping. Inspired by this concept, we propose a…
A Time Projection Chamber (TPC) is an ideal device for the detection of charged particle tracks in a large volume covering a solid angle of almost $4\pi$. The high density of hits on a given particle track facilitates the task of pattern…
Block-oriented nonlinear models are popular in nonlinear modeling because of their advantages to be quite simple to understand and easy to use. To increase the flexibility of single branch block-oriented models, such as Hammerstein, Wiener,…
The discrepancies in claims of experimental evidence in the search for weakly interacting massive particle (WIMP) dark matter necessitate a model for ionization efficiency (the quenching factor) at energies below 10 keV. We have carefully…
While Generative Adversarial Networks (GANs) have empirically produced impressive results on learning complex real-world distributions, recent works have shown that they suffer from lack of diversity or mode collapse. The theoretical work…
Power electronic converters for integrating renewable energy resources into power systems can be divided into grid-forming and grid-following inverters. They possess certain similarities, but several important differences, which means that…
Unconventional magnetism has emerged as a transformative frontier in condensed matter physics. Such phases are characterized by substantial non-relativistic spin splitting (NSS) in symmetry-compensated magnets. They have been classified by…
Deep Neural Networks (DNNs) have grown increasingly large in size to achieve state of the art performance across a wide range of tasks. However, their high computational requirements make them less suitable for resource-constrained…
Identification of nonlinear block-oriented models has been extensively studied. The presence of the process noise, more precisely its location in the block-oriented model influences essentially the development of a consistent identification…
The practical damage of silicon bipolar devices subjected to mixed ionization and displacement irradiations is usually evaluated by the sum of separated ionization and displacement damages. However, recent experiments show clear difference…
This paper presents and evaluates a novel method for generating power losses on transistors avoiding high currents. These could heat up the circuit tracks, affecting the accurate thermal modeling of the system. The proposed procedure is…