Results 251 to 260 of about 89,376 (355)
Novel dual-targeting of biofilm formation and pyocyanin production in clinical Pseudomonas aeruginosa isolates using glutamine-modified thiosemicarbazone-conjugated ZnO nanoparticles. [PDF]
Rabani HM +3 more
europepmc +1 more source
ABSTRACT This work presents a fully thermomechanically coupled material model for shape memory alloys (SMAs), capable of predicting shape memory effect, superelasticity, stress and strain recovery, and martensite reorientation. Formulated within the Generalized Standard Material (GSM) framework, the model employs a rate potential, whose variations ...
Muhammad Babar Shamim +2 more
wiley +1 more source
2D-Cosine power sine coupled map with fractal-Fibonacci fusion for hyperchaotic image encryption. [PDF]
Kumar M, Ch D.
europepmc +1 more source
A UV‐crosslinkable soft anisotropic conductive film (ACF) provides high‐resolution, room‐temperature electrical interfacing. Upon UV exposure, azide crosslinkers within the ACF matrix form covalent bonds with a wide range of C–H‐containing materials, resulting in interfaces that are both mechanically durable and electrically reliable.
Jun Choi +7 more
wiley +1 more source
Applications of Entropy in Data Analysis and Machine Learning: A Review. [PDF]
Sepúlveda-Fontaine SA, Amigó JM.
europepmc +1 more source
High‐Concentration Antibody Formulation via Solvent‐Based Dehydration
Amorphous solid antibodies are encapsulated into hydrogel microparticles through a solvent‐based dehydration process. The solvent extracts water from antibody solution droplets, causing the antibody to concentrate, and precipitation of the antibody into amorphous solid is induced.
Talia Zheng +3 more
wiley +1 more source
Programmable space-frequency linear transformations in photonic interlacing architectures. [PDF]
Friedman J +3 more
europepmc +1 more source
Sinewave frequency estimation based on fractional Interpolated Discrete Fourier Transform
Fernando M. Janeiro, Pedro M. Ramos
openalex +1 more source
A parametrically‐Conditioned Deep Learning Surrogate for Coherent Spinodal Decomposition
Spinodal decomposition of strained alloys with cubic anisotropy is reproduced by a Convolutional Recurrent Neural Network, taking the misfit parameter as explicit input to return different morphologies. The predicted composition fields match phase‐field simulations over a broad range of parameters, allowing to reconstruct the full phase diagram.
Andrea Fantasia +5 more
wiley +1 more source

