Results 161 to 170 of about 244,425 (248)

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

Prime editing of the common Familial Dysautonomia-causing c.2204 + 6T > C splicing mutation. [PDF]

Orphanet J Rare Dis
Peretto L, Pinotti M, Balestra D.
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

RaPID2: a parallel scalable framework for identity-by-descent segment detection via parallel PBWT. [PDF]

Bioinform Adv
Tang K, Naseri A, Zhi D, Zhang S.
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

Sufficient is better than optimal for training neural networks. [PDF]

Nat Commun
Babayan I, Aliahmadi H, van Anders G.
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

Quantum kernel methods for marketing analytics with convergence theory and separation bounds. [PDF]

Sci Rep
Sáez Ortuño L, Forgas Coll S, Ferrara M.   +2 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

Accelerated Stochastic Conjugate Gradient for a class of convex optimization. [PDF]

PLoS One
He L, Du Y.
europepmc   +1 more source