Results 171 to 180 of about 21,020,521 (317)

The Influence of the Different Repair Methods on the Electrical Properties of the Normally off p-GaN HEMT. [PDF]

Micromachines (Basel), 2021
Niu D, Wang Q, Li W, Chen C, Xu J, Jiang L, Feng C, Xiao H, Wang Q, Xu X, Wang X.   +10 more
europepmc   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

The ESD Robustness and Protection Technology of P-GaN HEMT. [PDF]

Micromachines (Basel)
Shi Y, Chen Y, He L, Chen X, Chen Y, Lu G.   +5 more
europepmc   +1 more source

A Novel Atomic-Level Post-Etch-Surface-Reinforcement Process for High-Performance p-GaN Gate HEMTs Fabrication. [PDF]

Nanomaterials (Basel), 2023
Wang L, Zhang P, Zhu K, Wang Q, Pan M, Sun X, Huang Z, Chen K, Yang Y, Xie X, Huang H, Hu X, Xu S, Wu C, Wang C, Xu M, Zhang DW.   +16 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

The Impact of Load-Dump Stress on p-GaN HEMTs Under Floating Gate Condition. [PDF]

Micromachines (Basel)
Shen Z, Shi Y, Wu L, He L, Chen X, Chen Y, Zhao D, He J, Zhu G, Zeng H, Lu G.   +10 more
europepmc   +1 more source

Improved I_on/I_off Current Ratio and Dynamic Resistance of a p-GaN High-Electron-Mobility Transistor Using an Al_0.5GaN Etch-Stop Layer. [PDF]

Materials (Basel), 2022
Wang HC, Liu CH, Huang CR, Shih MH, Chiu HC, Kao HL, Liu X.   +6 more
europepmc   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

On-Wafer Gate Screening Test for Improved Pre-Reliability in p-GaN HEMTs. [PDF]

Micromachines (Basel)
Giorgino G, Miccoli C, Cioni M, Reina S, Wakrim T, Guillon V, Sama NY, Gaillard P, Zeghouane M, Chauveau HJ, Castagna ME, Constant A, Iucolano F, Chini A.   +13 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source