Results 261 to 270 of about 1,735,729 (314)
Extracellular vesicles (EVs) play a dual role in diagnostics and therapeutics, offering innovative solutions for treating cancer, cardiovascular, neurodegenerative, and orthopedic diseases. This review highlights EVs’ potential to revolutionize personalized medicine through specific applications in disease detection and treatment.
Farbod Ebrahimi+4 more
wiley +1 more source
FAIR and Structured Data: A Domain Ontology Aligned with Standard‐Compliant Tensile Testing
The digitalization in materials science and engineering is discussed, emphasizing the importance of digital workflows and ontologies in managing diverse experimental data. Challenges such as quality assurance and data interoperability are tackled with semantic web technologies, focusing and introducing the tensile test ontology (TTO).
Markus Schilling+6 more
wiley +1 more source
AISI 304L stainless steel powder is mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. The numerical approach effectively predicts the Si3N4 powder homogeneity and N content distribution on the powder bed. Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by
Yuanbin Deng+7 more
wiley +1 more source
In this study, exciting new bi‐/multi‐linear elastic behavior of soft elastic composites that accompany the activation of wrinkling in the embedded interfacial layers is analyzed. The new features and performance of these composite materials, including dramatic enhancements in energy storage, can be tailored by the concentration of interfacial layers ...
Narges Kaynia+2 more
wiley +1 more source
Research Methodologies and Role of GIS in Social Science Research
openaire +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani+2 more
wiley +1 more source
An Automatized Simulation Workflow for Powder Pressing Simulations Using SimStack
The implementation of Workflow active Nodes (WaNos) for the convenient execution and automated evaluation of discrete element method calculations of powder pressing is showcased. Purposeful combination of WaNos creates timesaving and resource‐effective computational workflows.
Bjoern Mieller+2 more
wiley +1 more source
Digital Methods for the Fatigue Assessment of Engineering Steels
The use of engineering steels is often limited by their fatigue strength. In the sake of a faster product development, the fatigue behavior can be predicted by machine learning (ML). In this work, ML is applied on a heterogeneous database, covering a wide range of steel types.
Sascha Fliegener+7 more
wiley +1 more source
This manuscript presents advances in digital transformation within materials science and engineering, emphasizing the role of the MaterialDigital Initiative. By testing and applying concepts such as ontologies, knowledge graphs, and integrated workflows, it promotes semantic interoperability and data‐driven innovation. The article reviews collaborative
Bernd Bayerlein+44 more
wiley +1 more source
Smart Rubber Extrusion Line Combining Multiple Sensor Techniques for AI‐Based Process Control
This publication presents a digitalization approach for a laboratory rubber extrusion line, employing innovative measurement methods and artificial intelligence (AI)‐based process control. The results demonstrate that the measurement systems are capable of detecting changes in the process and extrudate quality.
Alexander Aschemann+18 more
wiley +1 more source