Results 71 to 80 of about 3,901,168 (239)

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

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Energies, 2016
An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve ...
Jin-Sun Yang, Jin-Young Choi, Geon-Ho An, Young-Jun Choi, Myoung-Hoe Kim, Dong-Jun Won   +5 more
doaj   +1 more source

Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam

Advanced Engineering Materials, EarlyView.
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva, Joseph Lavoie, Afsaneh Rabiei   +2 more
wiley   +1 more source

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

The Collaborative Semantic Grid

, 2006
Grid and Semantic Web technologies both enable heterogeneous resources to be joined up to achieve new functionality and capability, and their combined effectiveness has been demonstrated through a number of ‘Semantic Grid’ projects. These typically apply
De Roure, David, Michaelides, Danius, Page, Kevin, Frey, Jeremey, Page, KR, Roure, DD, Frey, JG, Michaelides, DT   +7 more
core   +2 more sources

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

Short‐term prediction of wind power based on temporal convolutional network and the informer model

IET Generation, Transmission & Distribution
In this study, a new short‐term wind power prediction model based on a temporal convolutional network (TCN) and the Informer model is proposed to solve the problem of low prediction accuracy caused by large wind speed fluctuations in short‐term ...
Shuohe Wang, Linhua Chang, Han Liu, Yujian Chang, Qiang Xue   +4 more
doaj   +1 more source

Comparative Analysis of Normal Force Characteristics and Dynamic Influence of Linear Flux-Switching Permanent Magnet Motor for Rail Transit

IEEE Access
The linear flux-switching permanent magnet motor (LFSPM) has significant potential for practical applications in the field of rail transit due to its advantages of high thrust density and high efficiency. However, LFSPM not only generates the thrust that
Yuxiao Zhu, Yongkuan Li, Yujian Chang, Jiaming Li, Jin Chen   +4 more
doaj   +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

Outlier Detection of Photovoltaic Power Generation System Data Based on GMM-IF Algorithm

IEEE Access
The Gaussian Mixture Model (GMM) is widely used in anomaly detection due to its flexibility in handling complex data distributions and its soft classification mechanism.
Xin Li, Guoxin Du, Yuman Li, Zengqiang Ma, Lihu Liu, Minglong Jiang, Feiyu Liu, Tianming Mu   +7 more
doaj   +1 more source