Results 101 to 110 of about 1,376,697 (345)

Trans‐Conductive Melt Pool Scaling and its Implications for Parameter Transfer in Laser Powder Bed Fusion for Metals with High Thermal Diffusivity

Advanced Engineering Materials, EarlyView.
Developing process parameters for the laser‐based Powder Bed Fusion of metals can be a tedious task. Based on melt pool depth, the process parameters are transferable to different laser scan speeds. For this, understanding the melt pool scaling behavior is essential, particularly for materials with high thermal diffusivity, as a change in scaling ...
Markus Döring, Matthias Gehring, Michael Schmidt   +2 more
wiley   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source

Rashba field in GaN

, 2010
We discuss problem of Rashba field in bulk GaN and in GaN/AlGaN two-dimensional electron gas, basing on results of X-band microwave resonance experiments. We point at large difference in spin-orbit coupling between bulk material and heterostructures.
Drabinska, A., Grzegory, I., Lucznik, B., Porowski, S., Skierbiszewski, C., Wilamowski, Z., Wolos, A.   +6 more
core   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Heat and Fluid Flow in Solvothermal Autoclave for Single-Crystal Growth Process

Journal of Thermal Science and Technology, 2012
We report and discuss an experiment and numerical simulation of heat transfer by natural convection inside an autoclave for the solvothermal growth of bulk crystalline GaN.
Yoshio MASUDA, Akira SUZUKI, Tohru ISHIGURO, Chiaki YOKOYAMA   +3 more
doaj   +1 more source

GAN-EM: GAN Based EM Learning Framework [PDF]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Expectation maximization (EM) algorithm is to find maximum likelihood solution for models having latent variables. A typical example is Gaussian Mixture Model (GMM) which requires Gaussian assumption, however, natural images are highly non-Gaussian so that GMM cannot be applied to perform image clustering task on pixel space.
Chenliang Xu, Wentian Zhao, Jing Shi, Zhihuai Xie, Shaojie Wang   +4 more
openaire   +3 more sources

Key Trends and Insights in Smart Polymeric Skin Wearable Patches

Advanced Engineering Materials, EarlyView.
Intelligent polymers, which respond to various physical and biological stimuli, are explored for the development of skin wearable patches in biomedical applications. Smart polymers, also known as intelligent or stimuli‐responsive polymers, play a crucial role in the development of advanced wearable patches due to their versatility and softness.
Sergio J. Peñas‐Núñez, Rajat Rai, Miryam Criado‐Gonzalez   +2 more
wiley   +1 more source

Magnetic studies of GaN nanoceramics

, 2006
The synthesis, morphology and magnetization measurements of GaN nanoceramics obtained under high pressure are reported. In particular the effect of grain size on magnetic properties of GaN nanopowders and nanoceramics was investigated.
Nyk, M., Strek, W., Zaleski, A. J.
core   +1 more source

High‐Performance Low‐Emissivity Paints Enabled by N‐Doped Poly(benzodifurandione) (n‐PBDF) for Energy‐Efficient Buildings

Advanced Functional Materials, EarlyView.
This study introduces a scalable and colored low‐emissivity (low‐e) paint achieved by spraying an ultrathin n‐doped poly(benzodifurandione) (n‐PBDF) coating onto various colored substrates. The low‐e paint enhances thermal regulation by reducing mid‐infrared thermal emissivity to 0.19, thereby stabilizing indoor temperatures across diverse climates ...
Xiaojie Liu, Won‐June Lee, Daniel William Carne, Yanpei Tian, Andrea Felicelli, Yue Lei, Joseph A. Romo, Liyan You, Zixin Xiong, Orlando Gabriel Rivera Gonzalez, Abdulrahman Aljwirah, Qiaoqiang Gan, Jianguo Mei, Xiulin Ruan   +13 more
wiley   +1 more source

Carbon Nanotube 3D Integrated Circuits: From Design to Applications

Advanced Functional Materials, EarlyView.
As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu, Yun Sun, Dong‐Ming Sun, Hui‐Ming Cheng   +3 more
wiley   +1 more source