Results 101 to 110 of about 279,833 (216)
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
A combined finite element and phase‐field approach predicts the evolution of microstructure during the directional solidification of Ni‐based superalloys. The model reveals how withdrawal rate, temperature gradient, and wall thickness control the dendrite spacing, highlighting the strong effect of surface regions in thin sections where dendrite growth ...
Sean Böhm +3 more
wiley +1 more source
Creating Ti–Fe α/β Alloys by Diffusion‐Driven Solid‐State Processing
This study proposes making alloys containing fast diffusing elements that are difficult to produce by ingot metallurgy, by diffusion‐driven solid‐state HIP processing of elemental powders and low‐temperature homogenisation. Here, novel Fe‐Ti α–β alloys are formed having fine α–β lamellae, a small β prior grain size without significant intermetallics ...
Jiaqi Xu +10 more
wiley +1 more source
Identified through the use of statistical design of experiments and metallographic investigation, this study exposes the stochastic origins of intergranular cracks in blown powder laser beam directed energy deposition additive manufacturing of pure molybdenum. It further demonstrates a successful crack mitigation approach with direct correlation to the
Nathaniel J. Lies +2 more
wiley +1 more source
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
Improved quantum clustering analysis based on the weighted distance and its application. [PDF]
Decheng F, Jon S, Pang C, Dong W, Won C.
europepmc +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

