Results 211 to 220 of about 2,296,565 (295)

pH-controlled reversible assembly of magnetic and plasmonic nanoparticles on gold nanorods. [PDF]

Nanoscale Adv
Rizvi MH, Wang R, Schubert J, Josefsberg AL, Fery A, Tracy JB.   +5 more
europepmc   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source

Atomistic insight into Al-Mg friction stir welding process via molecular dynamics simulation. [PDF]

PLoS One
Nguyen VT, Hoang VH, Nguyen TT, Thien TN, Vo XT, Nguyen VTT.   +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

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Data-driven prediction of thin-film metallic glass forming ability <i>via</i> Bayesian classification and experimental verification in the Cu-Zr-Al system. [PDF]

RSC Adv
Luo X, Mäkinen T, Huo W, Bonfanti S, Chen Z, Mizohata K, Sarakinos K, Alava M.   +7 more
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Discrete distributions are learnable from metastable samples. [PDF]

Nat Commun
Jayakumar A, Lokhov AY, Misra S, Vuffray M.   +3 more
europepmc   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Defining Operational Limits of Low-Cost MSLA 3D Printing for Microfluidic Systems: Resin Performance, Cell Compatibility, and Fluid Dynamics. [PDF]

ACS Omega
Radziunas-Salinas Y, Blanco-Fernández B, Valdiglesias V, Flores-Arias MT, Bao-Varela C, Gómez-Varela AI.   +5 more
europepmc   +1 more source