Results 181 to 190 of about 2,857,638 (285)

Micro-array based on parafilm towards the opto-analysis of Cu(ii), Cr(vi), and Ni(ii) ions in fish samples by specific indicators: a state-of-the-art approach. [PDF]

RSC Adv
Bahavarnia F, Kordasht HK, Hasanzadeh M, Shadjou N.   +3 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Source signal sparsity enhancement based on local maximum synchronous extraction transform algorithm for mixed matrix estimation in UBSS. [PDF]

Sci Rep
Li X, Li Z, Yao R, Guo Y, Zhang X, Zhou G.   +5 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

Gene-environment equivalence: The fundamental principle of Mendelian randomization. [PDF]

PLoS Med
Davey Smith G, Hemani G, Ebrahim S.
europepmc   +1 more source

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

An implantable dual-chamber capsule with three release modes for site-specific delivery and enhanced therapeutic efficacy. [PDF]

iScience
Ren L, Kou E, Zhang W, Li S, Tong X, Ren L, Tan Y.   +6 more
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

Gravity-sensing device for measuring bending angles in digestive endoscopes: Design and clinical evaluation. [PDF]

Endosc Int Open
Luo MY, Liu LQ, Lun ZX, Huang CY, Chen XC, Huang Y, Fu ZL, Zhou CK, Yang H, Zhang W.   +9 more
europepmc   +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