Results 31 to 40 of about 1,070 (109)

On the data-driven description of lattice materials mechanics

Results in Engineering
In the emerging field of mechanical metamaterials, using periodic lattice structures as a primary ingredient is relatively frequent. However, the choice of aperiodic lattices in these structures presents unique advantages regarding failure, e.g ...
Ismael Ben-Yelun, Luis Irastorza-Valera, Luis Saucedo-Mora, Francisco Javier Montáns, Francisco Chinesta   +4 more
doaj   +1 more source

Exploring Phonon Interference: Insights From a Nano‐Scale Silicon Double Slit Atomistic Simulation

Advanced Theory and Simulations, EarlyView.
Classical Waves at the Atomic Scale: Molecular Dynamics Reveal Phonon Interference in Silicon Nanostructures. Abstract In this study, the classic double‐slit experiment, originally developed for light waves is successfully adapted, to investigate the behavior of phonons in crystalline silicon.
Efstratios Nikidis, Paul Desmarchelier, Yoshiaki Nakamura, Anne Tanguy, Konstantinos Termentzidis, Joseph Kioseoglou   +5 more
wiley   +1 more source

Altered neural avalanche spreading in people with drug-resistant epilepsy✰

NeuroImage
Objective: To characterize a peculiar “EEG endophenotype” of drug-resistant epilepsy (DRE) through the graph theory characterization of avalanche spatiotemporal spreading properties.
B.M. Sancetta, M.A.G. Matarrese, L. Ricci, J. Lanzone, G. Lippa, M. Nesta, F. Zappasodi, M. Brunetti, V. Di Lazzaro, M. Tombini, G. Assenza   +10 more
doaj   +1 more source

Self‐Assembled Moiré Superlattices of Ti3C2Tx MXene for Future Twistronic Applications

Advanced Science, EarlyView.
Scanning tunneling microscopy imaging reveals self‐assembled Moiré superlattices in MXene with distinct periodicities. The observed Moiré modulates the local density of states due to interlayer electronic coupling. This work provides an atomic‐scale understanding of MXene Moiré physics and establishes a foundation for twistronics in future quantum ...
Kuanysh Zhussupbekov, Andrea Cabero del Hierro, Samuel Berman, Dahnan Spurling, Ainur Zhussupbekova, Stefano Ippolito, David D. O'Regan, Igor Shvets, Yury Gogotsi, Valeria Nicolosi   +9 more
wiley   +1 more source

Metal‐Less Top Electrode Semitransparent Organic Solar Modules with an Average Visible Transmission of 51% and a Light Utilization Efficiency of 4%

Advanced Science, EarlyView.
Semitransparent organic modules with device areas of 11.4 cm2 are developed for building‐integrated photovoltaics. Including a laser‐structured, metal‐free top electrode, the module achieves a PCE of 6.1% with an AVT of 47.5%. An extended back‐electrode design enhances optical and electrical performance, achieving PCE of 7.9%, AVT of 50.8%, and LUE of ...
Leonie Pap, Mathias List, René Haberstroh, Lasse Bienkowski, Martin Mattenheimer, Thomas Kroyer, Jared Faisst, Birger Zimmermann, Uli Würfel   +8 more
wiley   +1 more source

Metamaterial‐Enhanced Solar‐Driven Processes for Energy Conversion and Water Treatment

Advanced Science, EarlyView.
This review explores how metamaterials revolutionize solar‐driven process for energy conversion and water treatment through enhanced light absorption, LSPR, charge separation, and bandgap engineering. By leveraging unique nanostructures and AI‐guided design, these engineered materials drive CO₂ reduction, water splitting, pollutant degradation, and ...
Xuechen Jing, Zhehao Sun, Hang Yin, Kaili Liu, Yi‐Lun Chen, Shuwen Cheng, Zongyou Yin   +6 more
wiley   +1 more source

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +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

Adaptive event‐based asynchronous approach for containment control of Markov jump multi‐agent systems with hidden Markov models

Asian Journal of Control, EarlyView.
Abstract This paper focuses on the issue of adaptive event‐triggered containment control for Markov jump multi‐agent systems characterized by hidden Markov jump parameters. The central objective is to design an output‐feedback controller for the Markov jump multi‐agent system by using an adaptive event‐triggered technique that not only ensures the ...
Parivallal Arumugam, Oh‐Min Kwon, Sangwoon Yun, Yoon Mo Jung   +3 more
wiley   +1 more source

D2D-Assisted Adaptive Federated Learning in Energy-Constrained Edge Computing

Applied Sciences
The booming growth of the internet of things has brought about widespread deployment of devices and massive amounts of sensing data to be processed. Federated learning (FL)-empowered mobile edge computing, known for pushing artificial intelligence to the
Zhenhua Li, Ke Zhang, Yuhan Zhang, Yanyue Liu, Yi Chen   +4 more
doaj   +1 more source