Results 161 to 170 of about 4,361,784 (275)

Discrepancies Between Micro Versus Macroscale Viscoelastic Properties in a Microplastic‐Tissue Composite Model

open access: yesAdvanced Engineering Materials, EarlyView.
This study explores the discrepancies between bulk mechanics and spatial mapping in a tissue‐mimetic hydrogel model. Microplastic particles create localized stiff mechanical microenvironments that are detectable by cellular‐scale nanoindentation but leave bulk properties unchanged as measured by rheology.
Ahron T. Verschleisser   +3 more
wiley   +1 more source

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

open access: yesAdvanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang   +6 more
wiley   +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

open access: yesAdvanced 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   +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

open access: yesAdvanced 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   +7 more
wiley   +1 more source

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

open access: yesAdvanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source

Investigating the Low‐Temperature Phase Stability of the Binary Ta–W System

open access: yesAdvanced Engineering Materials, EarlyView.
Atomistic simulations show that the binary Ta–W system forms ordered intermetallic phases, B2‐TaW and D03‐TaW3, as 0 K ground states. Configurational entropy, however, lowers the free energy of the disordered bcc solid solution, which becomes the stable phase above about 400 K.
Klemens Lechner   +7 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

open access: yesAdvanced 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   +67 more
wiley   +1 more source

A note on Atiyah's $\Gamma$-index theorem in Heisenberg calculus

open access: yes, 2016
In this note, we prove an index theorem on Galois covering for Heisenberg elliptic differential operators, which is not elliptic, analogous to Atiyah's $\Gamma$-index theorem. This note also contains an example of Heisenberg differential operators with non-trivial $\Gamma$-index.
openaire   +1 more source

Effect of Cu and CuP Additions on the Microstructure and Nanoindentation‐Based Fracture Behavior of CoNiAlSi Ferromagnetic Shape Memory Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
Cu and combined Cu–P microalloying refine the microstructure and enhance the nanoindentation‐derived fracture resistance of CoNiAlSi ferromagnetic shape memory alloys without suppressing the martensitic transformation. Comparative SEM, DSC, and nanoindentation results reveal that the CuP‐containing alloy provides the most balanced response, achieving ...
Mehmet Demir
wiley   +1 more source

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