Results 91 to 100 of about 15,135,820 (245)

Microstructure Modification of Additively Manufactured Mo–9Si–8B by Annealing and Its Effects on High‐Temperature Mechanical Properties

Advanced Engineering Materials, EarlyView.
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt, Yong Chen, Georg Hasemann, Benjamin Wahlmann, Carolin Körner, Manja Krüger   +5 more
wiley   +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

Controlling Grain Growth in Powder Bed Fusion of Yttria‐Stabilized Zirconia Using Femtosecond Lasers: Challenges and Methodological Insights

Advanced Engineering Materials, EarlyView.
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn, Sarah Kaden, Andrea Barz, Daniel Störzner, Jens Bliedtner, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Cross-project defect prediction models: L'Union fait la force

, 2014
Existing defect prediction models use product or process metrics and machine learning methods to identify defect-prone source code entities. Different classifiers (e.g., linear regression, logistic regression, or classification trees) have been ...
DE LUCIA, Andrea, Andrea De Lucia, PANICHELLA, ANNIBALE, Annibale Panichella, Rocco Oliveto, Oliveto, Rocco   +5 more
core   +1 more source

Simulation‐Based Analysis of Insert Pull‐Out in Nickel‐Polyurethane Hybrid Foams Using CT‐Derived Geometries

Advanced Engineering Materials, EarlyView.
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz, Jonas Fell, Hendrik Jost, Stefan Diebels, Hans‐Georg Herrmann   +4 more
wiley   +1 more source

Cross-project software defect prediction

, 2022
The feasibility of building a software defect prediction (SDP) model in the absence of previous records has been increased by the introduction of the Cross-Project Defect Prediction (CPDP) method.
Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Bala, Yahaya Zakariyau, Manshor, Noridayu   +3 more
core   +1 more source

Influence of TiC and TiN Ceramic Reinforcements on the Microstructure, Thermal Expansion Behavior, and Tensile Properties of Invar 36 Manufactured by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji, Natasha Sacks, Johannes Pötschke, Björn Matthey   +3 more
wiley   +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

An Abstract Syntax Tree Encoding Method for Cross-Project Defect Prediction

IEEE Access, 2019
In the last few years, with the development of deep learning theory, researchers have tried to introduce the method of artificial intelligence into the field of software defect prediction (SDP) to improve its prediction effect.
Ziyi Cai, Lu Lu, Shaojian Qiu
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