Results 171 to 180 of about 98,478 (267)

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

open access: yesAdvanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu   +5 more
wiley   +1 more source

Strain‐Adaptive Dielectric Metamaterials via Bioinspired “Ligament‐Bone” Architecture for Ultrahigh‐Energy Capacitive Storage

open access: yesAdvanced Science, EarlyView.
A bioinspired strain‐adaptive ligament‐bone architecture achieves record‐high energy density of 26.1 J cm−3 and 90% efficiency at 600 MV m−1, coupled with a Young's modulus of 2.13 GPa. ABSTRACT Polymer dielectrics for capacitive energy storage face fundamental trade‐offs between breakdown strength, energy density, efficiency, and mechanical robustness.
Jian Wang   +6 more
wiley   +1 more source

Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]

open access: yesFront Comput Neurosci
Çetin C   +5 more
europepmc   +1 more source

Programmable Multi‐Axially Aligned Aerogels via Sequential Freeze‐Casting for Tailored Anisotropy and Tunable Mechanics

open access: yesAdvanced Science, EarlyView.
Conventional single‐gradient freeze‐casting typically produces unidirectional porous architectures with limited transverse connectivity. The Sequential Hybridization by Infiltration and Freeze‐casting Technique (SHIFT) addresses this constraint by integrating secondary aligned structures within a preformed primary scaffold.
Kiho Sung, Sungchul Shin
wiley   +1 more source

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

open access: yesAdvanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

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