Results 231 to 240 of about 18,721 (312)

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
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

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

open access: yesAdvanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell   +3 more
wiley   +1 more source

Near‐Field Electrospinning Micro‐Printhead Achieves Precise Control of Nanofiber Deposition

open access: yesAdvanced Engineering Materials, EarlyView.
A micro‐printhead for near‐field electrospinning enables reproducible deposition of polymer nanofibers with diameters below 50 nm. Systematic parameter studies uncover the mechanisms linking operating conditions to fiber morphology, paving the way for precise and low‐cost nanoscale 3D manufacturing.As a high‐resolution, cost‐effective, and rapid ...
Han Xu, Dario Mager, Jan G. Korvink
wiley   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

open access: yesAdvanced Engineering Materials, EarlyView.
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

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced Engineering Materials, EarlyView.
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

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