Results 191 to 200 of about 88,485 (243)

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

A Worm‐Inspired Origami Robot with Multimodal Locomotion for Adaptive Mobility in Complex Pipeline Environments

open access: yesAdvanced Science, EarlyView.
An origami worm‐inspired robot achieves multimodal locomotion in confined pipelines through mechatronic integration that embeds actuation, control, and communication within each origami module. Large, reversible configuration and dimensional changes enable 25 gaits synthesized by a unified framework across peristaltic, inchworm, and wheel‐rolling modes
Qiwei Zhang   +6 more
wiley   +1 more source

Psychometric Evaluation of Patients With Vitiligo. [PDF]

open access: yesIn Vivo
Kontoangelos K   +6 more
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

open access: yesAdvanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei   +7 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

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