Results 211 to 220 of about 191,173 (288)
Rheology of Dental Photopolymers for SLA/DLP/MSLA 3D Printing. [PDF]
Šimunović L +4 more
europepmc +1 more source
Anti‐Slip Material‐Based Strategies and Approaches
This review highlights the principle mechanisms of slipping at the microscale, linking contact mechanics with a friction behavior model for surface interfaces. Main strategies to develop anti‐slip properties to the surfaces are discussed alongside standardized testing approaches.
Sogand Abbaspoor‐Zanjani +3 more
wiley +1 more source
Optimal nano-silica filler concentration to optimize kinetics, rheology and bonding of self-adhesive composites. [PDF]
Alves M +3 more
europepmc +1 more source
4D Printing of Multimaterial Flexible Magneto‐Active Polymers
Magneto‐active polymers are 3D‐printed with tunable mechanical and magnetic properties using both superparamagnetic and hard ferromagnetic fillers. Nano‐CT imaging reveals the spatial distribution of particles within the matrix. Programmable magnetization patterns and soft, flexible architectures enable responsive actuation, offering exciting ...
Naji Tarabay +6 more
wiley +1 more source
Rigidity Percolation Dictates Rheological Hysteresis Regime in Polypropylene during Crystallization and Melting. [PDF]
Roberts P, Snyder CR, Kotula AP.
europepmc +1 more source
Elastomers Combining Damping Efficiency With Rapid Recovery
Double network granular elastomers (DNGEs) combine high energy dissipation under both cyclic loading and high impact with rapid shape recovery. 3D printing enables the production of complex, customizable structures with tailored performance. Recyclable DNGEs retain their properties over multiple recycling cycles.
Eva Baur, Alain Molleyres, Esther Amstad
wiley +1 more source
Linear Viscoelastic Wood Creep Models. [PDF]
Socha T, Kula K, Denisiewicz A.
europepmc +1 more source
This work establishes a framework for high‐resolution printed interconnects by coupling e‐jet printing control, multilayer deposition, and sintering optimization. Ink properties and printing speed influence particle stacking, while different sintering atmospheres drive distinct microstructural evolution.
Kaifan Yue +6 more
wiley +1 more source
Mesoscale avalanche size underpins the rheology of granular yielding. [PDF]
Lee KL, Yeh TY.
europepmc +1 more source
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source

