Results 121 to 130 of about 448,585 (316)
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
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 +17 more
wiley +1 more source
The State Space Models Toolbox for MATLAB
State Space Models (SSM) is a MATLAB toolbox for time series analysis by state space methods. The software features fully interactive construction and combination of models, with support for univariate and multivariate models, complex time-varying (dy ...
Jyh-Ying Peng, John A. D. Aston
doaj
Multimodal Data‐Driven Microstructure Characterization
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 +4 more
wiley +1 more source
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 +2 more
wiley +1 more source
In predictive maintenance, the complexity of the data often requires the use of Deep Learning models. These models, called “black boxes”, have proved their worth in predicting the Remaining Useful Life (RUL) of industrial machines.
Mouhamadou Lamine NDAO +3 more
doaj +1 more source
Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai +6 more
wiley +1 more source
To study the effects of parameters in smoothed particle hydrodynamics (SPH) simulations of hypervelocity impacts on basalt, numerical analysis and validation were performed using the Riemann-SPH method based on ground-based impact tests.
Yandong LIU, Qi ZHOU, Mingtao LI
doaj +1 more source
Tailoring Functional Properties of Ti–Ni–Cu Shape Memory Alloy Thin Films for MEMS Actuators
A comprehensive study of critical parameters required to develop well‐performing Ti–Ni–Cu thin film shape memory alloy microactuators is provided. Materials science and device integration aspects are integrated by addressing structural and physical relationships using complementary characterization techniques as well as a practical fabrication solution
Elaheh Akbarnejad +6 more
wiley +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
Comparing parameter choice methods for regularization of ill-posed problems
In the literature on regularization, many different parameter choice methods have been proposed in both deterministic and stochastic settings. However, based on the available information, it is not always easy to know how well a particular method will ...
Bauer, F., Lukas, M.A.
core

