Results 101 to 110 of about 121,065 (257)

Simulation‐Based Analysis of Insert Pull‐Out in Nickel‐Polyurethane Hybrid Foams Using CT‐Derived Geometries

Advanced Engineering Materials, EarlyView.
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz, Jonas Fell, Hendrik Jost, Stefan Diebels, Hans‐Georg Herrmann   +4 more
wiley   +1 more source

Fabrication Routes for Ionic Conducting Fiber Strain Sensors

Advanced Engineering Materials, EarlyView.
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw, Zhanhong Yang, Anne Ladegaard Skov, Magdalena Skowyra   +3 more
wiley   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Elastic–Plastic Modeling and Experimental Characterization of Granular Jamming Actuators

Advanced Engineering Materials, EarlyView.
Granular jamming enables rapid switching between soft and rigid mechanical states. Here, a reduced‐order elastic‐perfectly‐plastic beam framework captures pressure‐dependent loading, unloading, residual deformation, and hysteresis in jammed beams, while matching three‐point bending experiments across materials and geometries. The framework links design
Saheli Patel, Prashant K. Purohit, Jordan R. Raney   +2 more
wiley   +1 more source

Rotary 3D Printing With Integrated Electroplating

Advanced Engineering Materials, EarlyView.
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria, Nicola Larovere, Moslem Mohammadi, Gianluca Percoco, Ali Zolfagharian, Gianni Stano   +5 more
wiley   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Hiding Fuzzy Sequential Patterns by a Multi-Objective Scheme

International Journal of Information and Communication Technology Research, 2016
Improvements in technology have led to generating and mining huge amounts of data. Sequence mining is a research area of data mining that aims to extract useful knowledge from raw databases.
Olya Sadat Behbahani, Mir Mohsen Pedram, Kambiz Badie   +2 more
doaj  

Mitigating Creep Anisotropy and Enhancing Performance in Additively Manufactured Ni‐Based Superalloys: A Review

Advanced Engineering Materials, EarlyView.
Additive manufacturing introduces pronounced microstructural and crystallographic anisotropy in Ni‐based superalloys, resulting in orientation‐dependent creep deformation and damage. This review identifies the key microstructural origins of creep anisotropy, examines their influence on dominant deformation mechanisms, and highlights processing ...
Chandan Kumar, Shobhit Pratap Singh, Gaurav Mohanty, Praveen Kumar   +3 more
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