Results 121 to 130 of about 604,226 (267)
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley +1 more source
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé +9 more
wiley +1 more source
Leveraging the redox activities of cerium and dibenzotetrathiafulvalene to discover a photo-responsive magnetic material. [PDF]
Gupta H +11 more
europepmc +1 more source
Sol–gel‐derived ZnO–rGO hybrid nanoparticles enable Al7075 powder‐metallurgy composites to achieve concurrent gains in hardness and thermal conductivity while markedly lowering friction and wear. The hybrid architecture couples ZnO‐based load support with rGO‐assisted lamellar sliding and heat spreading, revealing a promising route toward lightweight ...
Bunyamin Aksakal +3 more
wiley +1 more source
Topological Phase Transition in Two-Dimensional Magnetic Material CrI<sub>3</sub> Bilayer Intercalated with Mo. [PDF]
Yin CE, Huang A, Jeng HT.
europepmc +1 more source
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari +4 more
wiley +1 more source
Co-assembly of Block Copolymers and Cobalt Ferrite Nanoparticles for Magnetic Material Design. [PDF]
Bertucci S +11 more
europepmc +1 more source
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma +4 more
wiley +1 more source
Correction: Chen et al. Deep Learning Applied to Defect Detection in Powder Spreading Process of Magnetic Material Additive Manufacturing. <i>Materials</i> 2022, <i>15</i>, 5662. [PDF]
Chen HY +8 more
europepmc +1 more source
Controlling the Field Assisted Sintering Technology (FAST) parameters, dwell temperature and cooling rate, significantly influences the microstructural evolution in titanium aluminide GE4822. Significant γ‐lamellar colonies develop only upon cooling through the α‐transus.
Jack Krohn, James Pepper, Martin Jackson
wiley +1 more source

