Results 281 to 290 of about 596,259 (322)

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

Decoding the therapeutic potential mechanism of <i>Cornus officinalis</i> in Parkinson's disease: a network pharmacology insight. [PDF]

Front Pharmacol
Wu Z, Zhao J, Wang W, Dong Y, Zhou T, Feng Y, Deng Y, Feng Y.   +7 more
europepmc   +1 more source

Interactions between Molten High‐Silicon Electrical Steels and Carbon‐Bonded MgO Refractories Based on Recyclates

Advanced Engineering Materials, EarlyView.
This study examines how several molten high‐silicon electrical steels interact with both conventional and recycled MgO–C refractories. For this, various immersion experiments are conducted. In addition to infiltration, a number of mechanisms are identified and explained that control the corrosion of the refractory material.
Lukas Neubert, Matheus Roberto Bellé, Anton Yehorov, Anhelina Mospan, Till M. J. Stadtmüller, Seetharaman Sridhar, Christos G. Aneziris, Olena Volkova   +7 more
wiley   +1 more source

Laser Metal Deposition of Aluminum Alloys 7075 and 5083 with the Addition of Volatile Alloying Elements through Powder Blending

Advanced Engineering Materials, EarlyView.
This study investigates laser metal deposition of aluminum alloys EN AW‐7075 and EN AW‐5083, using powder blending to compensate zinc and magnesium evaporation. In situ alloying and ex situ alloying with ZnAl12 and AZ91 preserve near‐standard compositions and improve mechanical properties.
Finn Bendixen, Anastasiya Toenjes, Annika Bohlen, Thomas Seefeld   +3 more
wiley   +1 more source

Urinary metabolome dynamics in ¹³C-labeled mice. [PDF]

Metabolomics
Damont A, Legrand A, Rousseau K, Bellanger L, Boiry S, Gibiat F, Leguay JJ, Junot C, Fenaille F, Ezan E.   +9 more
europepmc   +1 more source

Rheocasting versus Die Casting: An Insight into the Low‐Cycle Fatigue Behavior of AlSi7Mg0.6

Advanced Engineering Materials, EarlyView.
The study compares rheocast lightweight components with high‐pressure die cast materials regarding microstructure and fatigue behavior. Rheocast process offers higher efficiency due to lower casting temperatures. Despite some microstructural differences, both processes show similar strengths (yield strength 125 MPa, tensile strength 240 MPa).
Julia Richter, Thomas Wegener, Andreas Schilling, Martin Fehlbier, Thomas Niendorf   +4 more
wiley   +1 more source

Machine Learning-Based Integrative Analysis Identifies SUMOylation-Related Genes Underlying the Immune Heterogeneity of Sepsis. [PDF]

IET Syst Biol
Li Z, Yang J, Dong J, Ye Z, Li C, Hu Y, Ren H, Li S, Ji Z.   +8 more
europepmc   +1 more source

REVIVE: a computational platform for systematically identifying rejuvenating chemical and genetic perturbations. [PDF]

Aging (Albany NY)
Jung S, Hodar JA, Badam TVS, Del Sol A.
europepmc   +1 more source

A Polymeric Zwitterionic Hydrophilic Probe for Mapping the Human Serum Endogenous Glycopeptidome. [PDF]

J Sep Sci
Sajid MS, Saleem S, Ressom HW.
europepmc   +1 more source