Results 81 to 90 of about 73,829 (266)

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

Advanced 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, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced 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, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Design and Analysis of Compression–Torsion Coupling Metamaterials Using the Golden Section Method

Advanced Engineering Materials, EarlyView.
A novel compression–torsion metamaterial is engineered using inclined rods and symmetry breaking. To optimize its torsional performance, the golden section method is employed. The mechanical response of the metamaterial is validated through both numerical analysis and experimental validation.
Amirhossein Hassani, Sara Bagherifard
wiley   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Elastic Properties and Thermal Expansion Behavior of a Polycrystalline VMnFeCoNi High‐Entropy Alloy

Advanced Engineering Materials, EarlyView.
The high‐entropy alloy (HEA) V20Mn20Fe20Co20Ni20 (composition in at.%) can be made single‐phase face‐centered cubic (FCC) when annealed above 1338 K followed by water quenching. In this state, the alloy exhibits the greatest strength‐ductility combination of any quinary single‐phase FCC HEA.
Guillaume Laplanche, Marie Münchhalfen, Aditya Srinivasan Tirunilai, Jürgen Schreuer   +3 more
wiley   +1 more source

On the Effect of Creep on Local Lattice Orientation in Single‐Crystal Ni‐Based Superalloy Microstructures

Advanced Engineering Materials, EarlyView.
During creep of a single‐crystal Ni‐based superalloy, the overall crystal orientation is observed to remain constant while the microstructure evolves. Despite the lack of macroscopic rotation, small (<1°) rotations are observed on the submicron size scale and are accommodated by counteracting rotations over the scale of several micrometers.
E. J. Payton, E. B. Dursun, G. Eggeler, L. Agudo Jácome   +3 more
wiley   +1 more source

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

Advanced 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, Sarath Menon, Fritz Körmann, Thomas Hammerschmidt, Ralf Drautz   +4 more
wiley   +1 more source

The Influence of Field‐Assisted Sintering Technology (FAST) Temperature and Cooling Rate on the Microstructural Evolution in Gamma‐Titanium Aluminide Alloy GE4822

Advanced Engineering Materials, EarlyView.
Controlling the Field Assisted Sintering Technology (FAST) parameters, dwell temperature and cooling rate, significantly influences the microstructural evolution in titanium aluminide GE4822. Significant γ‐lamellar colonies develop only upon cooling through the α‐transus.
Jack Krohn, James Pepper, Martin Jackson
wiley   +1 more source

Ferroelectricity in Antiferromagnetic Wurtzite Nitrides

Advanced Functional Materials, EarlyView.
We establish MnSiN2${\rm MnSiN}_2$ and MnGeN2${\rm MnGeN}_2$ as aristotypes of a new multiferroic wurtzite family that simultaneously exhibits ferroelectricity and antiferromagnetism with altermagnetic spin splitting. By strategically substituting alkaline‐earth metals, we predict new materials with coexisting switchable polarization, spin texture, and
Steven M. Baksa, Lin‐Ding Yuan, Stephen D. Wilson, James M. Rondinelli   +3 more
wiley   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source