Results 91 to 100 of about 413,476 (255)

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer   +2 more
wiley   +1 more source

Elinvar Materials: Recent Progress and Challenges

open access: yesAdvanced Engineering Materials, EarlyView.
Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley   +1 more source

Low‐Angle Grain Boundaries and Re‐Segregation in Single‐Crystalline Ni‐Base Superalloys

open access: yesAdvanced Engineering Materials, EarlyView.
This work demonstrates that Re‐segregation at low‐angle grain boundaries (LAGBs) in Ni‐base superalloys is influenced by misorientation angle. Advanced microscopy and atom probe tomography reveal that higher misorientation angles increases Re‐segregation.
Alireza B. Parsa   +9 more
wiley   +1 more source

Rafting of Ni‐Based Superalloys Under Multiaxial Load as Understood by Phase‐Field Simulations and Critical Experiments

open access: yesAdvanced Engineering Materials, EarlyView.
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan   +5 more
wiley   +1 more source

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

open access: yesAdvanced 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

NanoMOF‐Based Multilevel Anti‐Counterfeiting by a Combination of Visible and Invisible Photoluminescence and Conductivity

open access: yesAdvanced Functional Materials, EarlyView.
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner   +9 more
wiley   +1 more source

Improved Feedback Quantizer with Discrete Space Vector

open access: yesSensors
The use of advanced modulation and control schemes for power converters, such as a Feedback Quantizer and Predictive Control, is widely studied in the literature. This work focuses on improving the closed-loop modulation scheme called Feedback Quantizer,
Matías Veillon   +6 more
doaj   +1 more source

Lipid Nanoparticles for the Delivery of CRISPR/Cas9 Machinery to Enable Site‐Specific Integration of CFTR and Mutation‐Agnostic Disease Rescue

open access: yesAdvanced Functional Materials, EarlyView.
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley   +12 more
wiley   +1 more source

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

open access: yesAdvanced 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   +11 more
wiley   +1 more source

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