Results 101 to 110 of about 1,318,522 (307)

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source

Beyond knowledge: Confidence and the gender gap in financial literacy [PDF]

Women are less likely to correctly answer the “Big-3” financial literacy questions, and a substantial share of the gap reflects women’s lower confidence.
Cziriak, Marius, Alessie, Rob, Bucher-Koenen, Tabea   +2 more
core  

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Cathodic Cage Plasma Deposition of Nanostructured Cu–Fe–Se Coatings on Poly(methyl Methacrylate)

Advanced Engineering Materials, EarlyView.
Nanostructured Cu–Fe–Se coatings are deposited on PMMA by a modified cathodic cage plasma process, enabling low‐temperature deposition on polymer substrates. A transition from discontinuous to compact morphology is observed with temperature, with optimal properties at 200°C, where improved CuFeSe2‐type bonding, lowest sheet resistance, and favorable ...
V. S. S. Sobrinho, M. Naeem, T. H. C. Costa, M. S. Libório, J. C. A. Queiroz, C. B. B. Luna, R. R. M. Sousa, P. S. Vieira, E. M. Araújo   +8 more
wiley   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Financial Knowledge Matters Entrepreneurial Decisions: A Survey in the COVID-19 Pandemic. [PDF]

J Knowl Econ, 2023
Tran QN, Phung TMT, Nguyen NH, Nguyen TH.   +3 more
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Strengths and Weaknesses of Everyday Financial Knowledge and Judgment Skills of Adults with ADHD. [PDF]

Int J Environ Res Public Health, 2023
Koerts J, Bangma DF, Mette C, Tucha L, Tucha O.   +4 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Investigating the associations of consumer financial knowledge and financial behaviors of credit card use. [PDF]

Heliyon, 2023
Chen F, Yu D, Sun Z.
europepmc   +1 more source