Results 221 to 230 of about 40,691 (307)

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

Thouless quantum walks in topological flat bands. [PDF]

Light Sci Appl
Danieli C, Conti C, Pilozzi L, Brosco V.
europepmc   +1 more source

Grain Refinement During Severe Plastic Deformation and Similitude of Subgrain Formation: A Molecular Dynamics Study

Advanced Engineering Materials, EarlyView.
Molecular dynamics is used to investigate structure refinement during severe plastic deformation. The results show similitude with experimental data. Molecular dynamics simulations of severe plastic deformation of monocrystalline and polycrystalline samples by multiaxial compression of aluminum are carried out.
Roberto B. Figueiredo
wiley   +1 more source

A Classification of Intrinsic Ergodicity for Recognisable Random Substitution Systems. [PDF]

Commun Math Phys
Gohlke P, Mitchell A.
europepmc   +1 more source

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

Advanced 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, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +1 more source

Nereid as a regular satellite of Neptune. [PDF]

Sci Adv
Belyakov M, Davis MR, Wong I, Batygin K, Brown ME.   +4 more
europepmc   +1 more source

Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids

Advanced Functional Materials, EarlyView.
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow, Samya Sen, Joaquin Yus, Eliza E. Lovrich, Amanda G. Hoika, Kelly M. Chang, Arielle A. Pfeil, Nellie Haug, Amy J. Wagoner Johnson, Randy H. Ewoldt   +9 more
wiley   +1 more source

Towards a mathematical framework for modelling cell fate dynamics. [PDF]

J Math Biol
Vittadello ST, Diaz L, Liu Y, Zanca A, Stumpf MPH.   +4 more
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Multiscale Ordinal-Pattern Dynamics and Temporal Symmetries in a Photonic Neuron with Single and Dual Delayed Feedback. [PDF]

Entropy (Basel)
Feiveson J, Yearian M, Jones M, Aragoneses A.   +3 more
europepmc   +1 more source