Results 171 to 180 of about 11,592 (210)

A Perspective on the Applications of Triphasic Gas Storage in Electrochemical Systems

Advanced Science, EarlyView.
Gas storage in microporous materials positioned locally at an electrode or electrocatalyst surface enhances electrochemical processes. Abstract Microporous materials store gases under dry conditions (e.g., hydrogen or oxygen via physisorption), but in some cases microporous materials also show triphasic (e.g., in a solid|gas|liquid system) gas storage ...
Zhongkai Li, Corin T. Scott, Taku Suzuki‐Osborne, John P. Lowe, Dominic Taylor, Mariolino Carta, Neil B. McKeown, Andrew D. Burrows, Lucia H. Mascaro, Frank Marken   +9 more
wiley   +1 more source

Cross Kingdom Metabolic Engineering Paradigm Elevating Sustainable Protein Production

Advanced Science, EarlyView.
ABSTRACT Confronting the dual crisis of escalating global protein demand and unsustainable agriculture necessitates transformative solutions. Here, we pioneer evolutionary insights from maize nitrogen optimization via asparagine synthetase (ASNS) to rewire metabolism in Pichia pastoris.
Yuanyuan Du, Changyu Pi, Kai Hong, Le Gao, Xin Wu   +4 more
wiley   +1 more source

Wavy‐Interlocked Stretchable Triboelectric Nanogenerators Enhanced by Liquid Metal Microflowers for Self‐Powered Wearable Motion Monitoring

Advanced Science, EarlyView.
Schematic showing a stretchable triboelectric nanogenerator based on interlocked wavy architectures that uses EGaIn microflower‐embedded PVDF‐TrFE and Nylon‐6 nanofiber membranes. The multi‐petaled, electron‐rich EGaIn microflowers enhance interfacial polarization and capacitance, while the interlocked wavy architecture enlarges the effective contact ...
Qianqian Xu, Huimin Li, Hanmin Zeng, Yahui Meng, Yimeng He, Xinke Hu, Senfeng Zhao, Jianxun Zhang, Peiqiong Zhou, Kechao Zhou, Dou Zhang, Chris Bowen, Yan Zhang   +12 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

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NETWORK TOPOLOGY DESIGN

IFAC Proceedings Volumes, 2008
Abstract The application of the Industrial Ethernet brings up issues of both the reliability and behaviour of the networks under a demanded load, while preserving the permitted time delay in the whole network. We propose an algorithm that designs the network topology, which meets the required fault tolerance and allows reliable communication between ...
Tomas Fencl, Pavel Burget, Jan Bilek
openaire   +1 more source

The topology of dark networks

Communications of the ACM, 2008
Knowing the structure of criminal and terrorist networks could provide the technical insight needed to disrupt their activities.
Jennifer Jie Xu 0001, Hsinchun Chen
openaire   +2 more sources

Estimating Topology of Networks

Physical Review Letters, 2006
We suggest a method for estimating the topology of a network based on the dynamical evolution supported on the network. Our method is robust and can be also applied when disturbances and/or modeling errors are presented. Several examples with networks of phase oscillators, pulse-coupled Hindmarch-Rose neurons, and Lorenz oscillators are provided to ...
DONGCHUAN YU, RIGHERO, MARCO, LJUPCO KOCAREV   +2 more
openaire   +3 more sources

Network Topology

2019
Networks are a convenient and powerful tool for modeling many real world processes, crossing different industrial, sociological and scientific areas, that exhibit some sort of interaction, called edge or link, between different target entities, called nodes.
Giuseppe Manco, Ettore Ritacco, Massimo Guarascio   +2 more
openaire   +2 more sources