Results 241 to 250 of about 3,165,496 (285)
A physics‐guided generative surrogate framework is developed for programmable metasurface beamforming. Mode‐conditioned binary state generation, aperture‐physics prediction, routed residual correction, NSGA‐II optimization, and CST validation are combined to support fast candidate screening and full‐wave beam refinement across single‐beam, dual‐beam ...
Wenqian Liu +4 more
wiley +1 more source
Neural Radiance Field-Based 3D Reconstruction and View Synthesis for Mussel Farm Environments. [PDF]
Zhao J, Xue B, Vennell R, Zhang M.
europepmc +1 more source
Oxygen‐scavenging‐induced self‐formed interlayers regulate Schottky‐barrier modulation in IGZO memristors, producing a fundamental trade‐off between synaptic update linearity and retention. A preserved AlOx interlayer moderates voltage distribution and enables gradual, nearly linear conductance updates, whereas a soft‐broken SiO2 interlayer provides a ...
Jae Woo Lee +11 more
wiley +1 more source
Implanted dynamic electric field therapy for glioblastoma: preclinical safety and efficacy of intratumoral modulation therapy. [PDF]
Iredale E +11 more
europepmc +1 more source
From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku +5 more
wiley +1 more source
Osiris<sup>++</sup>: hierarchical representations for robotic-enabled precision agriculture. [PDF]
Mukuddem A +6 more
europepmc +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
Single-view neural illumination estimation and editing for dynamic light field display. [PDF]
Hong X +9 more
europepmc +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
Three-Dimensional Reconstruction and Real-Time Deformation of Flexible Bodies: A Scoping Review (2009-2025). [PDF]
Zisu S, Butnariu S.
europepmc +1 more source

