Results 111 to 120 of about 35,088 (292)

Nanoindentation Criteria for Combinatorial Thin Film Libraries

Advanced Engineering Materials, EarlyView.
Thin‐film material libraries are compositional spreads used for screening composition‐structure‐property relationships. Nanoindentation is often used to characterize mechanical behavior across these systems, however variations in methodology are widespread.
Andre Bohn, Adie Alwen, Andrea M. Hodge
wiley   +1 more source

Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading

Advanced Engineering Materials, EarlyView.
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley   +1 more source

Artificial intelligence and the dawn of an algorithmic divide

Frontiers in Communication
Emerging technologies like artificial intelligence (AI) and algorithms reshape news curation and consumption. Against this background, previous research has been focused on divides between groups regarding access to such digital technologies. Disparities
Maximilian Eder, Helle Sjøvaag
doaj   +1 more source

A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials

Advanced Engineering Materials, EarlyView.
This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline, Matthew Santer, Robert Hewson   +2 more
wiley   +1 more source

Synthetic Social Alienation: The Role of Algorithm-Driven Content in Shaping Digital Discourse and User Perspectives

Journalism and Media
This study investigates how algorithm-driven content curation impacts mediated discourse, amplifies ideological echo chambers and alters linguistic structures in online communication.
Aybike Serttaş, Hasan Gürkan, Gülçicek Dere   +2 more
doaj   +1 more source

Evaluation of Plasticity and Creep Parameters From Tensile Stress–Strain Data for a Range of Strain Rates

Advanced Engineering Materials, EarlyView.
This plot compares experimental tensile stress–strain curves (with 4 different strain rates) and corresponding modelled curves (obtained using the optimised sets of Voce and Miller–Norton parameter values shown). The inferred M‐N values, characterizing the creep, are very similar to those obtained via conventional creep testing.
S. Ooi, R. P. Thompson, T. W. Clyne
wiley   +1 more source

A complete, multi-layered quranic treebank dataset with hybrid syntactic annotations for classical arabic processingMendeley Data

Data in Brief
This article describes the Extended Quranic Treebank (EQTB), a comprehensive, multi-layered, and computationally accessible linguistic resource for Classical Arabic (CA), meticulously developed to overcome the documented limitations of the original ...
Wadee A. Nashir, Abdulqader M. Mohsen, Asma A. Al-Shargabi, Mohamed K. Nour, Badriyya B. Al-onazi   +4 more
doaj   +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

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Ground-truth is law: The invisible conceptual work behind AI

Big Data & Society
This article challenges the idea that the turn from rule-based algorithm to machine learning systems leads to a decline in formal conceptualization. Through ethnographic research at two artificial intelligence (AI) production sites within the French ...
Camille Girard-Chanudet
doaj   +1 more source