Results 81 to 90 of about 8,567 (212)
Adult stem cell therapy requires more than high in vitro potency. This review proposes a systems framework in which cell‐intrinsic programs, instructive microenvironmental cues, and pre‐/post‐delivery engineering are co‐designed under standardized translational rules.
Soo‐Rim Kim +2 more
wiley +1 more source
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
Boron‐oxide‐assisted particle engineering stabilizes O3‐type layered cathodes for sodium‐ion batteries by mitigating phase transitions and lattice strain. Acting as flux and structural modifier, boron forms submicron hexagonal platelets with (003) facets and expanded Na‐layer spacing, enabling rapid Na⁺ diffusion and mechanical resilience.
Tengfei Song +9 more
wiley +1 more source
P2‐type sodium layered oxides have potential for high‐voltage operation but suffer from structural instability and capacity fading. This work demonstrates that synergistic Li and Ti co‐doping enhances sodium inventory, suppresses detrimental phase transitions, and activates reversible lattice oxygen redox.
Rishika Jakhar +16 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
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho +4 more
wiley +1 more source
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim +2 more
wiley +1 more source
Distributions of intrinsic stacking fault energies (ISFE) among different slip planes in the face‐centered cubic Co2Ni2Ru alloy, predicted by three foundation potentials (DPA, Orb, and SevenNet) and density functional theory (DFT) calculations. This study evaluates the efficacy of three foundation potentials (FPs)—SevenNet, DPA, and Orb—in predicting ...
Subah Mubassira +8 more
wiley +1 more source
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source

