Results 131 to 140 of about 6,187,400 (306)

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Global models for temporal relation classification [PDF]

, 2008
textTemporal relation classification is one of the most challenging areas of natural language processing. Advances in this area have direct relevance to improving practical applications, such as question-answering and summarization systems, as well as ...
Ponvert, Elias Franchot
core  

Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs

Advanced Engineering Materials, EarlyView.
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen, Osamu Waseda, Bernd Bayerlein, Simon Stier, Steffen Brinckmann, Abril Azócar Guzmán, Sarath Menon, Matthias A. Popp, Jesper R. Pedersen, Ivano E. Castelli, Jörg Waitelonis, Wolfgang Wenzel, Jörg Neugebauer, Jörg Schaarschmidt, Tilmann Hickel   +14 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

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

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

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes. [PDF]

Gigascience, 2017
Soranno PA, Bacon LC, Beauchene M, Bednar KE, Bissell EG, Boudreau CK, Boyer MG, Bremigan MT, Carpenter SR, Carr JW, Cheruvelil KS, Christel ST, Claucherty M, Collins SM, Conroy JD, Downing JA, Dukett J, Fergus CE, Filstrup CT, Funk C, Gonzalez MJ, Green LT, Gries C, Halfman JD, Hamilton SK, Hanson PC, Henry EN, Herron EM, Hockings C, Jackson JR, Jacobson-Hedin K, Janus LL, Jones WW, Jones JR, Keson CM, King KBS, Kishbaugh SA, Lapierre JF, Lathrop B, Latimore JA, Lee Y, Lottig NR, Lynch JA, Matthews LJ, McDowell WH, Moore KEB, Neff BP, Nelson SJ, Oliver SK, Pace ML, Pierson DC, Poisson AC, Pollard AI, Post DM, Reyes PO, Rosenberry DO, Roy KM, Rudstam LG, Sarnelle O, Schuldt NJ, Scott CE, Skaff NK, Smith NJ, Spinelli NR, Stachelek JJ, Stanley EH, Stoddard JL, Stopyak SB, Stow CA, Tallant JM, Tan PN, Thorpe AP, Vanni MJ, Wagner T, Watkins G, Weathers KC, Webster KE, White JD, Wilmes MK, Yuan S.   +79 more
europepmc   +1 more source

Implantable Ionic Memristors Based on Natural Polymer Heterojunctions

Advanced Functional Materials, EarlyView.
We report an implantable natural polymer‐based ionic memristor composed of hyaluronic acid, chitosan, and PDMS. The device achieved 98.94% accuracy in MNIST classification while reducing training time by 36.8% compared with a conventional artificial neural network (ANN).
Dong‐yup Lee, Byung Ik Park, Gihyeon Yim, Hyunjae Yoo, Sangjun Ma, Jundong Park, Jeong‐Yun Sun   +6 more
wiley   +1 more source