Results 51 to 60 of about 5,371,789 (237)

Effect of Dioctyl Sebacate on Corrosion Behavior of Fine-grain High-strength Reinforcement in Simulated Concrete Pore Solutions

International Journal of Electrochemical Science, 2017
Dioctyl sebacate (DS) was used as a corrosion inhibitor for fine-grain high-strength reinforcement (HRBF500 reinforcement) in simulated concrete pore solutions (SCP solutions) with 3.5% NaCl.
Bilan Lin, Zan Luo, Chaonong Liu, Xuefeng Liu, Yuye Xu   +4 more
doaj   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

Influence of pH on passivation of mild steel in simulated concrete pore solution: Electrochemical, ToF-SIMS and ReaxFF study

Developments in the Built Environment
The passivation evolution of mild steels in simulated concrete pore solutions with varying pH were systematically investigated in present study. Based on electrochemical, time-of-flight secondary ion mass spectrometry, and ReaxFF molecular dynamics ...
Guojian Liu, Panpan Zhang, Cheng Liu, Yunsheng Zhang   +3 more
doaj   +1 more source

The corrosion inhibition efficiency of aluminum tripolyphosphate on carbon steel in carbonated concrete pore solution

, 2017
The efficiency of aluminum tripolyphosphate (ATP) as inhibiting agents for carbon steel was studied in a carbonated concrete pore solution and mortars, respectively.
Ruilong Shi, Da Chen, Lu, Xiangyu, Xiufeng Huang, Shi, Ruilong, Xingguo Feng, Yiwen Xu, Huang, Xiufeng, Xiangyu Lu, Feng, Xingguo, Xu, Yiwen, Chen, Da   +11 more
core   +1 more source

Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials

Advanced Engineering Materials, EarlyView.
Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley   +1 more source

Influence of Chloride Ions on Corrosion Behavior of Steel Bars in a Simulated Concrete Pore Solution

International Journal of Electrochemical Science, 2019
The performance of steel bars deteriorates under chloride corrosion. It is thus essential to study the corrosion mechanism of different steel bars to better understand the corrosion of steel bars in concrete structures.
Hongwei Wu, Keyu Pan, Yi Dai, Hesong Jin, Fuhai Li   +4 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

Thermo-mechanical performance of concrete with alternative binder material. [PDF]

, 2013
Purpose – This paper investigates the effect of changes to fundamental components of concrete; cement type, water/cement ratio, aggregate size & age, on thermo-mechanical properties of hardened concrete.
Richardson, Alan, Agnew, Brian, Kirton, Paula   +2 more
core   +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 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