Results 191 to 200 of about 74,163 (353)
A dual lattice‐surface strategy employing NaTi2(PO4)3 is adopted to enhance the performance of P3‐type Na0.67[Zn0.3Mn0.7]O2, whereby Ti stabilizes the bulk lattice and surface P species mitigate degradation, collectively improving high‐voltage cycling stability, Na+ diffusion, and oxygen redox reversibility through synergistic structural and ...
Natalia Voronina +13 more
wiley +1 more source
Chitosan's Ability to Remove the Smear Layer-A Systematic Review of Ex Vivo Studies. [PDF]
Ferreira-Reguera A +4 more
europepmc +1 more source
Gas evolution behaviors of sodium layered oxide cathodes with varying compositions, cutoff voltages, dopants, and particle sizes/morphologies have been systematically investigated by online electrochemical mass spectrometry. The fundamental outgassing mechanisms of sodium‐based cathodes compared to lithium‐based cathodes have been elucidated.
Chen Liu, Zehao Cui, Arumugam Manthiram
wiley +1 more source
The smear layer comparison in each group using hoc Dunn’s test corrected by Bonferroni.
Maryam Saber Mahdi (22403493) +1 more
openalex +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Assessment of smear layer removal utilizing a conservative root canal instrumentation technique involving magnetically agitated irrigation with iron paramagnetic nanoparticles. [PDF]
Al-Mustwfi ES, Al-Huwaizi HF.
europepmc +1 more source
Antibacterial and smear layer removal efficacy of moringa (Moringa oleifera): An in vitro study. [PDF]
Natsir N +6 more
europepmc +1 more source
From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal +2 more
wiley +1 more source

