Results 31 to 40 of about 8,515,992 (225)

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Theoretical Writing

Grounded Theory Review: An International Journal, 2009
Theoretical sorting has brought the analyst to the point of pent-up pressure to write: to see the months of work actualized in a “piece.” But this is only a personal pressure.
Barney G. Glaser, Ph.D., Hon. Ph.D.
doaj  

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

The Hook: Getting your grounded theory research published

Grounded Theory Review: An International Journal, 2009
I learned about the hook as a fledgling writer back in the late 70’s, and early 80s. I wrote about stepfamilies when almost nobody else did (Stern, 1978, 1982a, 1982b).
Phyllis Noerager Stern, DNS, LLD (hon.), FAAN
doaj  

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

Meta-coaching: a methodology grounded in psychological theory [PDF]

International Journal of Evidence Based Coaching and Mentoring, 2008
In this conceptual article we suggest that understanding clients’ self-reflexive processes enables coaches to become even more effective in helping clients make changes in how they think, feel and act.
Susie Linder-Pelz, Michael Hall
doaj  

How to do a grounded theory study: a worked example of a study of dental practices

BMC Medical Research Methodology, 2011
Background Qualitative methodologies are increasingly popular in medical research. Grounded theory is the methodology most-often cited by authors of qualitative studies in medicine, but it has been suggested that many 'grounded theory' studies are not ...
Evans R, Carter Stacy M, Sbaraini Alexandra, Blinkhorn Anthony   +3 more
doaj   +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

Qualitative and Quantitative Research

Grounded Theory Review: An International Journal, 2008
The main point in the next two chapters is that the methodological literature is filled with references to the quantitative-qualitative conflict or opposition.
Barney G. Glaser, Ph.D., Hon. Ph.D.
doaj  

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source