Results 121 to 130 of about 55,674 (265)

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Sensitivity in phononic crystal sensors via super asymmetric coupled-cavity engineering. [PDF]

Sci Rep
Aly AH.
europepmc   +1 more source

Compatibility of Methacrylate Based Resins Controls Interfacial Failure and Toughness in 3D‐Printed Multimaterial Composites

Advanced Engineering Materials, EarlyView.
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim, Li Meng, Ahmad R. Najafi, Nicolas J. Alvarez   +3 more
wiley   +1 more source

Strong Lateral Mode Confinement by Embedding SiO₂ Nanospheres in the DBRs of GaN-Based VCSELs. [PDF]

Micromachines (Basel)
Chen H, Lei M, Meng L, Chu Z, Chen W, Hu X.   +5 more
europepmc   +1 more source

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

Detecting directed motion and confinement in single-particle trajectories using hidden variables. [PDF]

Elife
Simon F, Ramadier G, Fonquernie I, Zsok J, Patskovsky S, Meunier M, Boudoux C, Dultz E, Weiss LE.   +8 more
europepmc   +1 more source

Reconfigurable Logic‐in‐Memory Operations Enabled by Triple‐Gated Feedback Field‐Effect Transistors for Area‐Efficient Computing

Advanced Engineering Materials, EarlyView.
A reconfigurable logic‐in‐memory cell composed of triple‐gated feedback field‐effect transistors implements multiple combinational logic functions within a single configuration. By utilizing program gates as dynamic input terminals, the proposed cell performs full adder, full subtractor, 2‐to‐1 multiplexer, and 4‐to‐2 encoder operations without ...
Minhyeok Seol, Yunwoo Shin, Donghyung Lee, Dongki Kim, Kyoungah Cho, Sangsig Kim   +5 more
wiley   +1 more source

Coil-Globule versus Field-Driven Coil-Blob Transitions of PEG under Nanopore Confinement. [PDF]

ACS Meas Sci Au
Asandei A, Dejoux C, Pastoriza-Gallego M, Lubin-Germain N, Piguet F, Oukhaled A.   +5 more
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

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