Results 71 to 80 of about 4,122 (255)

Southern Binaries with the Zorro Speckle Camera @ Gemini South

The Astronomical Journal
We present measurements in the context of a survey of southern hemisphere binary and multiple stellar systems observed with the Zorro Speckle dual diffraction-limited optical imaging camera on the 8.1 m Gemini South telescope carried out between 2019 and
Rene A. Mendez, Andrei Tokovinin, Edgardo Costa, Maximiliano Dirk   +3 more
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

Advanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source

The Discovery of Three Galactic Wolf–Rayet Stars

The Astronomical Journal
Wolf–Rayet stars (WRs) are evolved massive stars in the brief stage before they undergo core collapse. Not only are they rare, but they also can be particularly difficult to find due to the high extinction in the Galactic plane.
Laurella C. Marin, Philip Massey, Brian A. Skiff, Kennedy A. Farrell   +3 more
doaj   +1 more source

Effects of Mg on Microstructure and Solidification of a Hypereutectic Zn–8 wt.%Al Alloy

Advanced Engineering Materials, EarlyView.
An appreciable set of results involving thermal data, microstructure, chemical composition, and microstructural growth laws is reported for ZnAlMg alloys. Such results demonstrate that ZnAlMg alloys have high potential for applications in automotive self‐lubricating components, batteries, and electrical systems.
Raí B. de Sousa, Jeverton L. Paixão, Daylla S. Silva, Bruno S. Sobral, Mucio D. de Medeiros, José E. Spinelli, Bismarck L. Silva   +6 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
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, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

A Chemically Peculiar Star Catalog from LAMOST DR12 Based on Deep Learning

The Astrophysical Journal Supplement Series
Chemically peculiar (CP) stars offer a unique observational sample for exploring key processes in stellar evolution. Leveraging the massive amounts of data obtained from large-scale sky surveys, deep learning technology has significantly advanced ...
Yixing Chen, Hui Deng, Lei Tan, Ying Mei, Feng Wang   +4 more
doaj   +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

22 Orbits of Binaries Based on SOAR Speckle Observations: Systems with Early Type Components

The Astronomical Journal
We have used new observational data obtained during the 2020, 2021, 2022, 2023, and 2024 speckle runs with the 4.1 m Southern Astrophysical Research (SOAR) telescope located at Cerro Pachón (Chile) to improve the orbits of the following 21 visual ...
José Ángel Docobo, Pedro Pablo Campo, Jorge Gómez, Luca Piccotti, Camila Caballero-Valdes, Rene A. Mendez, Edgardo Costa   +6 more
doaj   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source