Results 121 to 130 of about 7,472 (263)
Exceptional Antimodes in Multi‐Drive Cavity Magnonics
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith +4 more
wiley +1 more source
Trace water is acting as a constructive mediator in 2LiCl–GaF3, markedly increasing ionic conductivity while reorganizing local coordination. Hydration creates localized Li+ solvation environments and partially dissociates ion pairs, enhancing Li‐ion mobility.
Youngkyung Kim +10 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Bipolar Soft Limit Points in Bipolar Soft Generalized Topological Spaces
Hind Y. Saleh +2 more
openaire +1 more source
Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci +3 more
wiley +1 more source
Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
wiley +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
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 +5 more
wiley +1 more source
Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Incorporation of N‐based onium ions into the ionic framework of poly(heptazine imide) was obtained via protonation‐deprotonation of PHI frameworks arising from a parent Na‐containing analogue. Particularly, methylammonium moieties, through their small molecular size, hydrogen bonding capabilities and rotational mobility, appear to stabilize ...
Dingqiao Ji +6 more
wiley +2 more sources

