Results 141 to 150 of about 110,849 (310)

Implementing the discontinuous-Galerkin finite element method using graph neural networks with application to diffusion equations

Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry.
Chen, Boyang, Heaney, Claire E, Li, Linfeng, Xiang, Jiansheng, Dargaville, Steven, Pain, Christopher C   +5 more
core   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Graph neural networks for network analysis

With an increasing number of applications where data can be represented as graphs, graph neural networks (GNNs) are a useful tool to apply deep learning to graph data.
He, Yixuan
core   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Mechanically Programmable DNA Hydrogel Microparticles for 3D Cellular Systems

Advanced Materials, EarlyView.
DNA hydrogel microparticles are designed to exhibit controllable viscoelasticity and stiffness across three orders of magnitude from 30Pa$30 \,\mathrm{Pa}$ to 6.5kPa$6.5 \,\mathrm{kPa}$. They are uptaken into fibroblast spheroids where they are actively remodeled by cellular forces depending on their mechanical properties.
Tobias Walther, Eleni Dalaka, Gotthold Fläschner, Manuel Gómez‐González, Ilia Platzman, Sadaf Pashapour, Michelle Emmert, Pere Roca‐Cusachs, Xavier Trepat, Kerstin Göpfrich   +9 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Harnessing collective structure knowledge in data augmentation for graph neural networks

Graph neural networks (GNNs) have achieved state-of-the-art performance in graph representation learning. Message passing neural networks, which learn representations through recursively aggregating information from each node and its neighbors, are among
Chen, L, MA, Rongrong, CHEN, Ling, Ma, R, PANG, Guansong, Pang, G   +5 more
core   +1 more source

Graph Neural Networks are Heuristics

CoRR
12 pages, 3 tables with 2 figures, code repo included in the ...
Yimeng Min, Carla P. Gomes
openaire   +2 more sources

Room‐Temperature Skyrmionic Synapse in 2D Ferromagnet Fe3GaTe2 Operating via Collective Spin Texture Transformation

Advanced Materials, EarlyView.
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang, Tongji Zhu, PeiYu Cai, Xiaoming Ma, Zhen Wang, Ruifu Zhang, Yi Hao, Jingdi Lu, Liubing He, Jun Xu, Yuejie Zhang, Wanjun Jiang, Jing Tao, Shiming Lei, Pavel Parchinskiy, Jing Teng, Lingfei Wang, Wei Niu, Elton J.G. Santos, Xiaoqian Zhang, Peng Li   +20 more
wiley   +1 more source