Results 191 to 200 of about 718,685 (289)

Field‐Driven Active Colloids as Distributed Micromachines: Bridging Physics, Control, and Function Across Length Scales

open access: yesAdvanced Science, EarlyView.
Field‐driven active colloids are framed as distributed micromachines in which externally supplied power, sensing, and control regulate task‐relevant states. By closing the loop between particle behavior, imaging, computation, and electric or magnetic actuation, these systems can progress from programmable motion toward adaptive functional outcomes ...
Ruchi Patel, Bhuvnesh Bharti
wiley   +1 more source

Opposite Trap‐State Evolution Pathways Govern Endurance and Retention Failure in Amorphous Chalcogenide Memory

open access: yesAdvanced Science, EarlyView.
GeSbSe selector‐only memory devices are investigated through physical and electrical analyses to reveal opposite trap‐state evolution pathways governing reliability degradation. Endurance cycling drives Se migration, transitioning traps from deep to shallow states.
Byung Jun Lee   +3 more
wiley   +1 more source

Mechanically Regulated Secretion: How Physical Forces Instruct the Secretory Pathway and Remodel the Secretome

open access: yesAdvanced Science, EarlyView.
Mechanical cues, including ECM stiffness, stretch, compression, shear stress, and traction forces, remodel trafficking across the secretory pathway, from the ER and Golgi to endolysosomal compartments and the plasma membrane. The resulting secretome reshapes ECM composition and tissue mechanics, establishing feedback loops that support homeostasis or ...
Domenico Russo   +5 more
wiley   +1 more source

Electrically Tunable Heliconical Smectic Superstructure in Polar Fluids. [PDF]

open access: yesAdv Mater
Nishikawa H   +5 more
europepmc   +1 more source

Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi   +3 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
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

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