Results 121 to 130 of about 3,559,721 (288)

High‐Temperature Phase Transformation in a V‐9Si‐6.5B Alloy: The Kinetic and Crystallographic Pathway From V5SiB2 to V8SiB4

open access: yesAdvanced Engineering Materials, EarlyView.
In situ synchrotron high‐energy X‐ray diffraction reveals the real‐time high‐temperature phase evolution of a ternary V‐9Si‐6.5B alloy. The study uncovers a kinetically delayed V5SiB2 → V8SiB4 transformation governed by massive structural and chemical barriers.
Zahra Sabeti   +4 more
wiley   +1 more source

The technological impact of diffusion in nanopores [PDF]

open access: yes, 2005
The impact of nanopore diffusion on the performance of adsorption separation processes is reviewed. Zeolite membrane processes and kinetically selective cyclic adsorption processes depend for their selectivity on differences in intracrystalline diffusion
Ruthven, Douglas M.
core   +1 more source

A Gas Source Localization Algorithm Based on Particle Filter in Wireless Sensor Network

open access: yesInternational Journal of Distributed Sensor Networks, 2015
Gas source localization (GSL) is a critical component in wireless sensor network (WSN) which can be used to estimate the position of gas leaks through the gas concentration measured by the monitoring nodes.
Qiuming Li, Zhigang Liu, Xianda Xiao
doaj   +1 more source

Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials

open access: yesAdvanced 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

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

Modeling brain extracellular space from diffusion data [PDF]

open access: yes, 2007
The extracellular space (ECS) of the brain is a thin region surrounding each cell that is filled with a medium resembling cerebrospinal fluid and an unknown amount of extracellular matrix. The ECS is difficult to study but diffusion measurements based on
Nicholson, Charles
core   +1 more source

Reaction-Diffusion in Co2Si/Zn Diffusion Couple

open access: yes
Periodic layered structures were examined in the Co₂Si/Zn diffusion couple annealed at 390 °C. SEM, TEM, EPMA, and XRD analyses revealed alternating Co–Si–rich and Zn–rich layers composed of CoSi, γ₁, and γ₂ phases with cell-to-cell variations in ...
Cserháti, Csaba   +4 more
core   +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 Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced 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   +14 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose   +7 more
wiley   +1 more source

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