Results 161 to 170 of about 4,453,047 (296)

Low‐Cost, Large‐Scale Nanoporous Metals by Mechanical Alloying, Oxide Reduction, and Dealloying of Powders

Advanced Engineering Materials, EarlyView.
Powder metal processing provides scalable advantages in nanoporous (np) metal development. Mechanical alloying is used to produce unique precursors for hybrid nanopore formation by oxide reduction and dealloying. As demonstrated in np Ag, this approach improves process efficiency while promoting smaller ligaments and larger pores, both of which are ...
Mark A. Atwater, Oliver A. Fowler
wiley   +1 more source

Technological architecture for a multi-region solution within the regulation of Brazil's Unified Health System. [PDF]

Front Digit Health
Cardoso PH, Barreto TO, Valentim JLRDS, Coutinho KD, Dos Santos JPQ, de Morais AHF, Veras NVR, Portela AEA, Melo JS, Barros CDC, Pinheiro AS, Dantas MB, Paiva JCL, Filho JAP, de Almeida RS, Júnior WDS, da Silva AM, de Melo EAS, da Silva DLI, Crisostomo JVM, Dos Santos SRFC, Veloso CMFM, Machado GM, Valentim RAM.   +23 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced 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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Correcting model error bias in estimations of neuronal dynamics from time series observations. [PDF]

Sci Rep
Williams I, Taylor JD, Nogaret A.
europepmc   +1 more source

Insect architecture.

[J. Rennie]
openaire   +4 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Distillation-free Scaling of Large State-Space Models for Images and Videos. [PDF]

Int J Comput Vis
Suleman H, Wasim ST, Naseer M, Gall J.
europepmc   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

AutoGERN: single-cell RNA-seq gene regulatory network inference via explicit link modeling and adaptive architectures. [PDF]

Bioinformatics
Wang J, Chen Y, Zou Q, Luo X.
europepmc   +1 more source