Elasticity‐Driven Periodic Polarization Patterns in a Chiral Ferroelectric Nematic Fluid
Chiral polar ferroelectric nematic fluids exhibit spontaneous formation of stripe, square, and hexagonal polarization textures under confinement. Controlled by thickness and anchoring, these patterns produce spatially modulated nonlinear optical responses.
Anej Sterle +11 more
wiley +1 more source
Predicting unconfined compressive strength of geopolymer-stabilized clays using a sector fruit fly-based extreme learning machine. [PDF]
Abdellatief M, Mortagi M.
europepmc +1 more source
Molecular doping redistributes the internal electric field in organic photodetectors, providing a new degree of freedom to spatially control carrier transport and collection. Simulations and experiments reveal distinct transport pathways for injected and photogenerated carriers, enabling low dark current under reverse bias and wavelength‐selective ...
Jingwei Yi +15 more
wiley +1 more source
Hybrid Machine learning-based modeling to predict and optimize the compressive strength of electric arc furnace slag-modified concrete. [PDF]
Uddin MA +6 more
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Ionic Gating of Liquid‐Crystal‐Like Pteridine Assemblies Enables Tunable Light Scattering
Tunable optical properties emerge through developmentally regulated ionic gating, which transforms disordered, ultraviolet (UV)‐absorbing organelles into concentrically ordered, liquid‐crystal‐like light scatterers. By integrating analyses of pteridine composition, potassium‐dependent assembly, hierarchical ultrastructure, and optical behavior, the ...
Sourabh Bera +22 more
wiley +1 more source
Effects of Dust Addition on the Reactivity and High-Temperature Compressive Strength of Ferro-Coke. [PDF]
Wang R +7 more
europepmc +1 more source
Antibacterial efficacy and compressive strength of modified glass ionomer cements. [PDF]
Ponangi K +5 more
europepmc +1 more source
Predicting compressive strength of mortars containing recycled CRT glass using GMDH and GEP methods. [PDF]
Ghorbani V, Seyedkazemi A, Kutanaei SS.
europepmc +1 more source
Evaluate the compressive strength of fiber-reinforced geopolymer concrete incorporating ground granulated blast furnace slag with machine learning approach. [PDF]
Rahman Sobuz MH +7 more
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Prediction of Compressive Strength of Concrete Using Explainable Machine Learning Models. [PDF]
Fu H, Zhou X, Xu P, Sun D.
europepmc +1 more source

