Results 191 to 200 of about 283,093 (346)

Investigating the Structural Factors Influencing the Magnetic Interaction between Individual Copper Spins in the CuCu4 Metallacrown Complex, from Its Bulk Form to Its Adsorption on Au(111)

open access: yesAdvanced Materials Interfaces, EarlyView.
The Cu(II)[12‐MCCu(II)N(Shi)‐4] metallacrown complex (CuCu4) is studied to examine how geometric transformations affect magnetic coupling between copper spins by using ultraviolet photoemission spectroscopy and DFT calculations for the bulk phase and CuCu4 adsorbed on Au(111). While adsorption minimally affects tDOS, exchange coupling constants between
Ariyan Tavakoli   +11 more
wiley   +1 more source

Behavior of Damping Ratio with Cutting Condition

open access: yesJournal of the Japan Society for Precision Engineering, 1996
Takahiro SHIRAKASHI   +2 more
openaire   +2 more sources

Tunable Sensitivity in PAN/CNF/PEDOT:PSS Nanofiber‐Based Piezocapacitive Sensors

open access: yesAdvanced Materials Interfaces, EarlyView.
This study demonstrates highly tunable, flexible pressure sensors made from a nanofibrous composite of polyacrylonitrile (PAN) and carbon nanofibers (CNF) or poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). By adjusting filler type, concentration, and mat thickness, the sensors achieve large sensitivity improvements, stable ...
Alireza Gholamhoseini   +4 more
wiley   +1 more source

Roadmap to Precision 3D Printing of Cellulose: Rheology‐Guided Formulation, Fidelity Assessment, and Application Horizons

open access: yesAdvanced Materials Technologies, EarlyView.
This critical review presents a comprehensive roadmap for the precision 3D printing of cellulose. Quantitative correlations link ink formulation and rheological properties to print fidelity and final material performance. This framework guides the development of advanced functional materials, from biomedical scaffolds to electromagnetic shielding ...
Majed Amini   +3 more
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

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