Results 141 to 150 of about 2,590,880 (251)
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 +7 more
wiley +1 more source
Theoretical Integration for Designing Healing ICU Environments: An Interdisciplinary Framework. [PDF]
Paquet E, Gagnon C, Gallani MC.
europepmc +1 more source
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 +5 more
wiley +1 more source
Do ESG Frameworks Capture Corporate Health Impacts? An Analysis of the Food and Beverage Industry. [PDF]
Burgess R +9 more
europepmc +1 more source
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 +6 more
wiley +1 more source
This white paper offers a comprehensive guide on Double Materiality (DM), an approach that integrates both financial and impact perspectives in corporate sustainability. It explains DM’s importance in aligning company strategies with evolving regulations,
Baeten, Xavier, Spijker, Stephanie Nuria
core
Performance: Conservation, Materiality, Knowledge
This deposited data set offers a representative cross-section of data generated by the research project Performance: Conservation, Materiality, Knowledge.
Magnin, Emilie +5 more
core +1 more source
A double-edged sword: materiality classifications of sustainability topics. [PDF]
Göttsche M +4 more
europepmc +1 more source
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 +4 more
wiley +1 more source
Engaging the stuff of words: language materiality and symbolic power. [PDF]
Thurlow C.
europepmc +1 more source

