Experiment and Modelling of Ultrasonic Vibration-Assisted Creep-Aging Tensile for 7055-T6 Alloy. [PDF]
Zuo D, Fu H, Xu T, Ye T, Han Y, Gao C.
europepmc +1 more source
Harnessing Phase Separation for the Development of High‐Performance Hydrogels
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao +3 more
wiley +1 more source
Rheological characteristics and modification mechanism of rock asphalt compound modified binder based on grey relational analysis. [PDF]
Hou J, Guo X.
europepmc +1 more source
Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing +10 more
wiley +1 more source
Reduced-Feature Hybrid Machine Learning for Coal Ash Sintering-Temperature Prediction Using Chemistry and Physicochemical Descriptors. [PDF]
Al-Otoom A.
europepmc +1 more source
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
An inverse analysis method for estimating tension softening constitutive of quasi-brittle materials under monotonic loading. [PDF]
Liu D, Guo Y, Chen H.
europepmc +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
A Unified Temperature-Dependent Elastoplastic Damage Framework for Concrete from Sub-Zero to Elevated Temperatures. [PDF]
Gao P +6 more
europepmc +1 more source
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

