Results 151 to 160 of about 11,986,581 (298)

Modeling Dislocation Cutting of γ′ Precipitates in Ni‐Base Superalloys: Linking Atomistic and Dislocation Dynamics Simulations

open access: yesAdvanced Engineering Materials, EarlyView.
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé   +9 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

open access: yesAdvanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink   +4 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

open access: yesAdvanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle   +5 more
wiley   +1 more source

Continuous Stiffness Graded Metal–Ceramic Femoral Stems: UMAT‐Based Design and Finite Element Assessment

open access: yesAdvanced Engineering Materials, EarlyView.
Functionally graded metal–ceramic femoral stems are engineered through continuous UMAT‐based stiffness tailoring, eliminating discrete material interfaces while enhancing biomechanical compatibility. Low‐index power‐law gradation optimizes load transfer, reduces stress shielding, and controls implant–bone micromotion, highlighting a materials‐design ...
Rihem Nouira, Sameh Elleuch, Hanen Jrad
wiley   +1 more source

Additive Manufacturing of Alumina‐Reinforced Elastomers

open access: yesAdvanced Engineering Materials, EarlyView.
Vat‐photopolymerized elastomers reinforced with platelet‐shaped alumina exhibited preferential orientation, reduced porosity, and significantly enhanced mechanical performance. A 3 wt% platelet loading increased tensile strength from 12.4 to 45.7 MPa, highlighting the critical role of filler morphology in elastomeric VPP composites.
Majid Barzegar Keyvani   +6 more
wiley   +1 more source

Enhancing Fatigue Crack Growth Resistance in Heterostructured Aluminum Bimetals by Tailored Interface Design

open access: yesAdvanced Engineering Materials, EarlyView.
Different Al/Al bimetals with a single engineered interface reveal how mechanical mismatch governs fatigue crack growth under cyclic loading. Additionally, loading–unloading–reloading tests link the microyielding behavior to the fatigue crack growth resistance, while crack‐path analysis reveals toughening mechanisms at the interface, highlighting ...
Sebastian Vollath   +2 more
wiley   +1 more source

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

open access: yesAdvanced Engineering Materials, EarlyView.
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma   +4 more
wiley   +1 more source

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