Results 111 to 120 of about 23,821 (231)

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

open access: yesAdvanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao   +3 more
wiley   +1 more source

Spanish phishing and legitimate email dataset with technical and psychological annotations. [PDF]

open access: yesData Brief
Bustio-Martínez L   +9 more
europepmc   +1 more source

Binary Code Similarity Detection: Retrospective Review and Future Directions

open access: yesComputers, Materials & Continua
Shengjia Chang   +2 more
openaire   +1 more source

Dynamic Regulation of Endogenous Transcription Factor Hubs at Single‐Molecule Resolution

open access: yesAdvanced Science, EarlyView.
This study combines single‐molecule microscopy and genome editing to characterize the dynamic behaviors of endogenous oncofusion transcription factor EWS::FLI1 in Ewing sarcoma cells. EWS::FLI1 forms neomorphic hubs that dynamically assemble and dissolve. The hubs are regulated during mitosis, by RNA, and by specific chemicals.
Shawn Yoshida   +4 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

open access: yesAdvanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang   +2 more
wiley   +1 more source

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