Application of solid modeling techniques for geometric simulation of surface topography in boring operations. [PDF]
Mehrabinasab M +2 more
europepmc +1 more source
Thermochemical Micro‐Explosion for Prompt Thrombolysis via Proximal Injection of Liquid Alkali Metal
We report a micro‐explosive thermochemical thrombolysis (METCT) therapy via injectable liquid alkali metal encapsulated in dimethyl silicone (LAM@oil). METCT enables prompt and safe vascular recanalization within 90 s. Critically, the LAM@oil system demonstrates significantly higher thrombolytic efficacy compared to clinically available thrombolytic ...
Xin Liao +7 more
wiley +1 more source
Tree-ring δ¹³C and growth responses of <i>Larix principis-rupprechtii</i> to climate change in the Central-Northern Taihang Mountains. [PDF]
Dong J +5 more
europepmc +1 more source
A reservoir‐guided silver‐nanoparticle soldering strategy is developed for bending‐resistant 3D graphene–metal heterojunctions. Controlled hot‐plate evaporation confines conductive ink within the metal reservoir, suppressing spreading and protecting the LIG interface from deformation‐induced fracture.
Saeyoung Park +5 more
wiley +1 more source
Beech latewood density as a proxy for temperature reconstruction. [PDF]
Verschuren L +15 more
europepmc +1 more source
Intra-seasonal development of radial increment of Picea abies in Latvia
Jēkabs Dzenis +3 more
openaire +1 more source
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Study on Damage Evolution and Mechanical Performance of PCCP Before and After Internal Steel-Cylinder Repair Under Multiple Broken-Wire Conditions. [PDF]
Si J, Wang G, Zheng Y, He J, Wang R.
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
Computational heat transfer analysis of solar based energy systems via employment of numerical calculations and finite volume scheme. [PDF]
Melaibari AA +2 more
europepmc +1 more source

