This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin +12 more
wiley +1 more source
Selective H<sub>2</sub>O<sub>2</sub> photosynthesis in ferroelectric photocatalyst: rare-earth 4f-state-mediated charge-spin regulation. [PDF]
Xiong R +5 more
europepmc +1 more source
State of Charge Estimation of Li-Ion Battery Based on Adaptive Sliding Mode Observer. [PDF]
Wang Q, Jiang J, Gao T, Ren S.
europepmc +1 more source
Despite benefits to storage stability and handleability of aluminum scrap, octadecyl phosphonic acid (ODPA) SAMs reduce the tensile strength of wires produced using friction‐induced recycling. Etching and methyl diphosphonic acid (MDPA) coatings, however, have little effect.
Timothy D. Goller +3 more
wiley +1 more source
Operando tracking of ion kinetics and state-of-charge via multiresonant fiber-optic grating sensors in sodium-ion batteries. [PDF]
Han X +10 more
europepmc +1 more source
State-of-Charge Distribution of Single-Crystalline NMC532 Cathodes in Lithium-Ion Batteries: A Critical Look at the Mesoscale. [PDF]
Kröger TN +6 more
europepmc +1 more source
Rotary 3D Printing With Integrated Electroplating
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria +5 more
wiley +1 more source
Hybrid multi-scale CNN-Residual-LSTM approach for robust state-of-charge estimation in lithium-ion batteries. [PDF]
Oyucu S +5 more
europepmc +1 more source
H∞ Observer Based on Descriptor Systems Applied to Estimate the State of Charge. [PDF]
Meng S, Li S, Chi H, Meng F, Pang A.
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source

