Selective effect of atmospheric non-thermal plasma on resin cement shear bond strength to glass ceramics. [PDF]
Mustafaoğlu E +3 more
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
A Comparative Evaluation of Surface Roughness and Shear Bond Strength of Two Ceramic Repair Systems After Different Chemical and Mechanical Surface Treatments: An In Vitro Study. [PDF]
Patil PA, Joshi S, Sanyal P.
europepmc +1 more source
Local stress concentration disrupts metabolic homeostasis and induces inflammation in the nucleus pulposus (NP), thereby accelerating intervertebral disc degeneration (IDD). A biomimetic HA/ChS hydrogel millimeter sphere (ChS@HM) is developed to enable synergistic stress dispersion and sustained hydration lubrication.
Ang Li +4 more
wiley +1 more source
Evaluation of Micro-Shear Bond Strength of Self-Adhesive Flowable Giomer To Bovine Tooth. [PDF]
Kim E +5 more
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
Comparative evaluation of shear bond strength of composite restorations and glass-incorporated restorations with calcium silicate-based cement liner: A systematic review and meta-analysis. [PDF]
Rohida SG +4 more
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

