One of wide bandgap semiconductors, SiC has been widely applied to the power devices, and then, the super-junction MOS transistor of SiC is being investigated to obtain higher performance for Ron and BV [1]. The super-junction structure is fabricated by trench filling with the epitaxial growth [2, 3].
Previously published fast empirical models for diffusion coefficients in silicon-germanium (Si1-x Gex) [1][2] were not applicable to high germanium content x≥0.5 and hence did not properly extend towards germanium. For some dopants, diffusion coefficients become very small and hence this model cannot be applied to devices containing silicon-germanium with high germanium content or devices containing silicon, silicon-germanium and germanium
Gallium nitride (GaN)-based devices for power electronics show superior performance in comparison to silicon carbide and silicon-based devices [1]–[3]. The development of vertical devices, like pn-diodes and power HEMTs results in higher power density and voltage handling. One of the key parameters of this technology is the dislocation density. This is lower in free-standing GaN-on-GaN epitaxy than in heteroepitaxial GaN growth on different substrates like SiC or Si, but still has a density of 104-106 cm-2 [4]. The diode reverse leakage seems to be related to the dislocation density, and it can be modelled with a Poole-Frenkel or a hopping conduction mechanism [5]. The Poole-Frenkel model is already implemented in the trap-assisted tunnelling model in Silvaco Atlas [6]. For the leakage in threading dislocations a variable-range hopping (VRH) model has been implemented in the simulator, based on Ref. [7].
This document describes how to setup a virtual environment suitable for the deckbuild remote mode.
The host system to consider shall be Windows (7 or 10). The goal is to use the windows version of the TCAD GUI tools TonyPlot and DeckBuild and to run any simulation (Victory, Athena, Clever) on a Linux Virtual Machine (VM).
本ウェビナーでは、著名なゲスト講演者、アリゾナ州立大学、電気電子情報工学の教授、Hugh Barnaby博士をお招きします。シルバコTCADの概要について学ぶことができ、また半導体デバイス物理の学習の一環として、効率的かつ効果的にTCADを利用する方法、および物理ベース・モデリングを用いて新技術を調査、設計するツールとしてTCADを導入する方法について、Barnaby博士の考えを聴くことができます。
本ウェビナーでは、寄生抽出結果のレビュー、寄生ネットリスト上で多数の解析を行う手法、およびツールの概要についてご紹介します。
本ウェビナーでは、現在の半導体企業が直面する問題と、半導体企業がデザイン・データだけでなく技術とは関係ない大量のメタデータ、そして社内および社外IPをエンタープライズ・レベルで体系化するのに役立つシルバコのテクノロジについて考察します。
本ウェビナーでは、ストレス・シミュレーションに使用される数値的手法を説明し、シンプルな構造の解析モデルと比較、そして変形のため誘起される応力に対するシルバコの非線形有限要素法によるアプローチを紹介します。
本ウェビナーでは、シルバコのドライバ、HAL(Hardware Abstraction Layer)、ローレベル・ソフトウェアを使用するAMBA Subsystemsへのサポートについて紹介します。
Cryogenic electronics plays a fundamental role in several applications, such as spacecraft, high-energy physics experiments, metrology, superconductive astronomical detectors and, with the increased interest in quantum computing, the manipulation of quantum bits (qubits) [1]. Outstanding characteristics have been reported for advanced CMOS technologies operating at cryogenic temperature in terms of on-state current, leakage current, subthreshold swing, and transconductance [2]. This represents an excellent opportunity to use such advanced technologies to design and implement a quantum computing control system (including multiplexers, LNAs, and RF oscillators) and introduce it inside the refrigerator together with the qubits [3]. Another recently growing field of application is the cryogenic silicon photonics [4].