Results 91 to 100 of about 18,891 (177)
This perspective reframes additive manufacturing for electrical machines as a qualification‐limited materials and architecture design problem. It links process–structure–property–performance relationships to magnetic, conducting, dielectric, and thermal property windows, highlighting where AM can enable segmented magnetic circuits, permanent magnet ...
Dénes Fodor, Loránd Szabó
wiley +1 more source
Flexible, super-resolution skin with in-sensor hyperdimensional computing for real-time pressure field perception. [PDF]
Zhang F +9 more
europepmc +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
Quantitative assessment of intrapulmonary vessel volume by CTPA in vasculitis patients with pulmonary vascular involvement. [PDF]
Ming Y +11 more
europepmc +1 more source
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe +6 more
wiley +1 more source
Mapping the Influence of Artificial Intelligence in Prosthodontics: A Scoping Review of the Current Trends and Challenges. [PDF]
Boca DA, Ille CE, Jivanescu A.
europepmc +1 more source
Despite benefits to storage stability and handleability of aluminum scrap, octadecyl phosphonic acid (ODPA) SAMs reduce the tensile strength of wires produced using friction‐induced recycling. Etching and methyl diphosphonic acid (MDPA) coatings, however, have little effect.
Timothy D. Goller +3 more
wiley +1 more source
Discovering algorithms with computational language processing. [PDF]
Bourdais T +3 more
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Hybrid Multi-Domain ECG Feature Learning with mRMR and CNN-Transformer for Cardiac Disease Classification. [PDF]
Alnusayri M +6 more
europepmc +1 more source

