EasyGaN is a GaN-on-Silicon epivendor. We develop advanced epiwafers for the GaN-on-Si semiconductor market using Molecular Beam Epitaxy (MBE).

GaN-on-Si stack with highly resistive AlN buffer for mmWave RF devices. Ultra-thin buffer for enhanced thermal dissipation and low bow RF losses < 0.5 dB/mm Remarkable homogeneity over the whole wafer No degradation of performance after stress tests Available in 100-, 150- and 200-mm diameters

Custom epitaxy solutions and services in the fields of optoelectronics, electronics and beyond. Why EasyGaN? We rely on original molecular beam epitaxy techniques and offer a broad range of innovating solutions with striking benefits. MBE Advantages : ☑ Low-temperature processes (nucleation, regrown contact, …)

EasyGaN is a startup providing epitaxy solutions to unleash the full potential of GaN-on-Silicon technology. Located in Sophia Antipolis, EasyGaN is a CRHEA-CNRS spin-off, an internationally...

The company offers turnkey substrates that meet the GaN barriers on silicon and market requirements in terms of quality and cost, it provides epitaxy solutions to unleash the potential of GaN-on-Silicon technology, and it develops advanced substrates for the GaN on Silicon semiconductor market using the Molecular Beam Epitaxy technique, its AIN ...

EasyGaN is a startup providing epitaxy solutions for an easy access to the GaN-on-silicon technology. Located in Sophia Antipolis, EasyGaN is a spin-off of CRHEA-CNRS, an internationally recognised research center with 20+ years of experience in …

EasyGaN is a startup focused on advancing GaN-on-Silicon technology within the semiconductor industry. The company specializes in providing epitaxy solutions, including high-quality Aluminum Nitride (AlN) templates and Gallium Nitride (GaN) on Silicon epiwafers, primarily for optoelectronics and electronics applications.

Very simple implementation of GANs, DCGANs, CGANs, WGANs, and etc. with PyTorch for various dataset (MNIST, CARS, CelebA). You can run the code at Jupyter Notebook. And …

With this step, EasyGaN will be able to provide high-quality AlN templates to the electronic market enabling the fabrication of GaN-on-Si devices with improved breakdown voltages, significantly lower RF losses, and allowing for a higher manufacturing throughput with the required diameters.

GAN stands for Generative adversarial network. Generative adversarial networks (GANs) are a class of artificial intelligence algorithms used in unsupervised machine learning, implemented by a system of two neural networks contesting with each other in a zero-sum game framework. They were introduced by Ian Goodfellow et al. in 2014. [1] .