Results 121 to 130 of about 437,099 (249)

Intelligent recommendation system for College English courses based on graph convolutional networks

Heliyon
With the rapid development of international communication, the number of English courses has shown an explosive growth trend, which has caused a serious problem of information overload, resulting in poor teaching performance of recommended English ...
Chen Lilan, Jianqi Zhong
doaj   +1 more source

Engineered Protein‐Based Ionic Conductors for Sustainable Energy Storage Applications

Advanced Materials, EarlyView.
Rational incorporation of charged residues into an engineered, self‐assembling protein scaffold yields solid‐state protein films with outstanding ionic conductivity. Salt‐doping further enhances conductivity, an effect amplified in the engineered variants. These properties enable the material integration into an efficient supercapacitor.
Juan David Cortés‐Ossa, Paolo Blesio, Marcial Fernandez‐Castro, Lisa Almonte, Maxence Fernandez, Mantas Liutkus, Perumal Pandurangan, Carlos Sabater, Aitor Villaverde, Manuel Melle‐Franco, Nurit Ashkenasy, Felipe Jiménez‐Ángeles, M. Carmen Morant‐Miñana, M. Reyes Calvo, Aitziber L. Cortajarena   +14 more
wiley   +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

Graph in Graph Neural Network

Existing Graph Neural Networks (GNNs) are limited to process graphs each of whose vertices is represented by a vector or a single value, limited their representing capability to describe complex objects. In this paper, we propose the first GNN (called Graph in Graph Neural (GIG) Network) which can process graph-style data (called GIG sample) whose ...
Wang, Jiongshu, Yang, Jing, Deng, Jiankang, Gunes, Hatice, Song, Siyang   +4 more
openaire   +2 more sources

Light‐Induced Entropy for Secure Vision

Advanced Materials, EarlyView.
This work realized a ternary true random number generator by exploiting stochastic traps emerging within multiple junction interfaces, and quantitatively validated the generation of high‐quality random numbers. Furthermore, it successfully demonstrated diverse applications, including AI‐resilient image security, thereby providing a valuable guide for ...
Juhyung Seo, Seungme Kang, Chaehyun Kim, Taehyun Park, Youngwoo Yoo, Yeong Kwon Kim, Wonjun Shin, Byung Chul Jang, Young‐Joon Kim, Hocheon Yoo   +9 more
wiley   +1 more source

MGATs: Motif-Based Graph Attention Networks

Mathematics
In recent years, graph convolutional neural networks (GCNs) have become a popular research topic due to their outstanding performance in various complex network data mining tasks.
Jinfang Sheng, Yufeng Zhang, Bin Wang, Yaoxing Chang   +3 more
doaj   +1 more source

Non-convolutional graph neural networks.

Advances in Neural Information Processing Systems 37
Rethink convolution-based graph neural networks (GNN) -- they characteristically suffer from limited expressiveness, over-smoothing, and over-squashing, and require specialized sparse kernels for efficient computation. Here, we design a simple graph learning module entirely free of convolution operators, coined random walk with unifying memory (RUM ...
Wang, Yuanqing, Cho, Kyunghyun
openaire   +2 more sources

Science‐Towards‐Technology Breakthrough in CO2 Electroreduction: Multiphysics, Multiscale, and Artificial Intelligence Insights

Advanced Materials, EarlyView.
Electrochemical CO2RR is a key technology for converting CO2 into chemicals, but there remains a gap between “laboratory science” and “engineering practice” in current research. This review establishes a multi‐scale research framework, encompassing atomic‐level characterization, microenvironment regulation, external field‐assisted optimization, and AI ...
Ping Hong, Changfan Xu, Huaping Zhao, Yong Lei   +3 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

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source