Results 181 to 190 of about 119,464 (301)

Research on fault diagnosis of substation grounding grid based on graph neural network and multi source information fusion. [PDF]

PLoS One
Pu X, Ding H, Zhong L, Chen X.
europepmc   +1 more source

Materials‐Driven Additive Manufacturing for Electrical Machines: Qualification‐Oriented Design Beyond Geometric Freedom

Advanced Engineering Materials, EarlyView.
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

Aidification of the self: a phenomenological approach to machine consciousness through human-robot 'between-ness'. [PDF]

Neurosci Conscious
Tanaka S.
europepmc   +1 more source

FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery

Advanced Engineering Materials, EarlyView.
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin, Émeline Cournède, Jens Krarup, Michael Lesa, Foyzul Hasan, Amandine Séné, Arnaud Lahouati, David Benhaiem, Jérémie‐Luc Sanchez, Simon Delacroix, Thierry Gacoin, Fabienne Testard, Damien Faivre, David Carriere, Corinne Chevallard, Olivier Taché, Mark A. Levenstein   +16 more
wiley   +1 more source

Enhanced prediction of electric field distribution in lightning protection systems with heterogeneous ground. [PDF]

Sci Rep
Khechekhouche A, Romdhane M, Gacem A, Mesbahi N, Alturki M, Almalaq Y, Naoui M, Albaker A, Alateeq A, Guesmi T.   +9 more
europepmc   +1 more source

Effect of Cu and CuP Additions on the Microstructure and Nanoindentation‐Based Fracture Behavior of CoNiAlSi Ferromagnetic Shape Memory Alloys

Advanced Engineering Materials, EarlyView.
Cu and combined Cu–P microalloying refine the microstructure and enhance the nanoindentation‐derived fracture resistance of CoNiAlSi ferromagnetic shape memory alloys without suppressing the martensitic transformation. Comparative SEM, DSC, and nanoindentation results reveal that the CuP‐containing alloy provides the most balanced response, achieving ...
Mehmet Demir
wiley   +1 more source

Editorial: Rethinking the embodiment of language: challenges and future horizons. [PDF]

Front Psychol
Cuccio V, Montalti M, Shtyrov Y, Gallese V.   +3 more
europepmc   +1 more source

Cryogenic Deformation Behavior of TiAl and Insights Into Embrittlement After High‐Temperature Exposure Combined With Secondary Ion Mass Spectroscopy of Near Surface Chemistry

Advanced Engineering Materials, EarlyView.
Near‐surface deuterium enrichment profiles for different microstructural types of TiAl after exposure at 700 °C in a heavy water‐containing environment. The deuterium levels are significantly higher than expected from natural occurrence, indicating that the heavy water dissociated during the exposure treatment and entered the specimens.
Jonathan D. H. Paul, Alexander Welle, Dirk Matthiessen, Michael Oehring, Fritz Appel, Florian Pyczak   +5 more
wiley   +1 more source

Perioperative management of spinal cord stimulators in patients undergoing non-SCS spine surgery: A retrospective cohort study. [PDF]

Interv Pain Med
Saleh AR, Standage E, Luansritisakul C, Jin E, Smith MR, Hao D.   +5 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
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, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source