Results 201 to 210 of about 7,150,473 (243)

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

Advanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar, Dhanadeep Dutta, G. Bharat Reddy   +2 more
wiley   +1 more source

Single-cell-informed senescence programs underpin a machine-learning prognostic model robustly validated across melanoma cohorts. [PDF]

Front Cell Dev Biol
Peng S, Xie J, He X.
europepmc   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

Thermodynamic Pathways of Nonequilibrium Solidification in Wire‐Arc Additive Manufacturing Fe‐Based Multicomponent Alloy Structures

Advanced Engineering Materials, EarlyView.
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios, Anthony Gonzalez, Aleksander Aleman, Tyler Dolmetsch, Tanaji Paul, Arvind Agarwal   +5 more
wiley   +1 more source

Explainable Machine Learning Predictive Models for Surgical Site Infections: Scoping Review. [PDF]

J Med Internet Res
Sun R, Liu Y, Lu S, Tartari E, Birgand G, Yang L, Zhou L.   +6 more
europepmc   +1 more source

Thermomechanical Fatigue and Creep–Fatigue Interaction of Inconel 718 Additively Manufactured by Laser Beam Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
Thermomechanical fatigue tests of laser beam powder bed fusion (PBF‐LB) Inconel 718 show that the additively manufactured material reaches almost the lifetimes of conventionally‐rolled material under no‐dwell conditions. Introducing dwell times at the maximum temperature markedly reduces the lifetimes due to pronounced grain boundary sliding associated
Stefan Guth, Tomáš Babinský, Jan Lars Riedel, Wen Hao Kan, Aijun Huang, Martin Heilmaier, Ivo Šulák   +6 more
wiley   +1 more source

Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants. [PDF]

Plant Genome
Xia H, Chen H, Wu Y, Zhang T, Zhang G, Zou J, Zhang Y.   +6 more
europepmc   +1 more source

Air‐Pressure–Actuated Vibroacoustic Metamaterial With Tunable Bandgap: Design, Modeling, and Characterization

Advanced Engineering Materials, EarlyView.
This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal, Michael M. Becker, Sarah C. L. Fischer   +2 more
wiley   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Multimodal MRI biomarkers and machine learning in neuromyelitis optica spectrum disorder: a review. [PDF]

Front Neurol
Zhang J, Xu H, Zhao M, Zheng Z, Zhao Y.
europepmc   +1 more source