Results 201 to 210 of about 275,998 (257)

Time‐Dependent Oxidation and Scale Evolution of a Wrought Co/Ni‐Based Superalloy

Advanced Engineering Materials, EarlyView.
This study shows how a new wrought Co/Ni‐based superalloy resists oxidation at 800 ∘$^\circ$C. The oxide scale changes from rough, fast‐growing spinel to a dense, protective chromia–alumina layer. Atom probe analysis reveals tiny refractory‐rich bubbles at the interface that mark the transition to long‐term, diffusion‐controlled protection ...
Cameron Crabb, Zachary T. Kloenne, Samuel R. Rogers, Chi Hang Dominik Kwok, Mark C. Hardy, Michele S. Conroy, David Dye   +6 more
wiley   +1 more source

Karl Popper and the Mechanisms of Hydrogen Embrittlement

Advanced Engineering Materials, EarlyView.
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +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

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

THE STRUCTURAL EQUATION MODEL

, 1989
openaire   +2 more sources

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Toward equation structural modeling: an integration of interpretive structural modeling and structural equation modeling

Journal of Management Analytics, 2021
Interpretive structural modeling (ISM) is an interactive process in which a malformed (bad structured) problem is structured into a comprehensive systematic model.
Alireza Amini, Moslem Alimohammadlou
openaire   +1 more source

Structural Equation Modeling With Ωnyx

Structural Equation Modeling: A Multidisciplinary Journal, 2014
Ωnyx is a free software environment for creating and estimating structural equation models (SEM). It provides a graphical user interface that facilitates an intuitive creation of models, and a powerful back end for performing maximum likelihood estimation of parameters. Path diagrams in Ωnyx can be exported to OpenMx, lavaan, and Mplus to allow an easy
von Oertzen, T., Brandmaier, A. ; https://orcid.org/0000-0001-8765-6982, Tsang, S.   +2 more
openaire   +2 more sources

Structural Equation Modeling

2011
Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path ...
Catherine M, Stein, Nathan J, Morris, Nora L, Nock   +2 more
openaire   +2 more sources