Results 171 to 180 of about 2,058,197 (242)

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

A unified analytical framework for Mössbauer synchrotron sources. [PDF]

J Synchrotron Radiat
Szymański KR.
europepmc   +1 more source

Enhancement of the Through‐Thickness Electrical Conductivity of Carbon‐Fiber‐Reinforced Plastics Using Large Graphite Particles

Advanced Engineering Materials, EarlyView.
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, Yu Zhou, Shintaro Kamiyama, Takao Okada, Tomohiro Yokozeki, Ryoma Tokonami, Tatsuhiro Takahashi   +6 more
wiley   +1 more source

Large Temperature-invariant Anomalous Nernst Effect in Non-collinear Antiferromagnet Mn₃Pt. [PDF]

Adv Sci (Weinh)
Gong P, Zhang X, Zhu W, Wang M, Pan C, Xu A, Guo Y, Li Y, Chen J, Zhou Y, Shi Z, Shao D, Liu L, Zhou S, Guan Y, Cheng R, Qiu X.   +16 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

On Low-Rank Multiplicity-Free Complex Fusion Categories. [PDF]

Commun Math Phys
Vercleyen G, Slingerland J.
europepmc   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

Symmetry-based derivation of neuronal membrane dynamics: a Lie group approach to action potential generation. [PDF]

Front Neurosci
Melendy RF, Blue DH.
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

A Physics-Informed neural network (PINN) for parameter identification in analytical ultracentrifugation (AUC) analysis. [PDF]

J Comput Appl Math
Cao W, Martin R, Demeler B.
europepmc   +1 more source