Results 231 to 240 of about 51,997 (309)

FGL2‐HDAC11 Drives Immunothrombosis via NETs‐Mediated Endothelial Capillarization in MASLD Fibrosis

open access: yesAdvanced Science, EarlyView.
ABSTRACT Metabolic dysfunction–associated steatotic liver disease (MASLD) is frequently accompanied by hepatic fibrosis and systemic cardiovascular complications; however, the mechanistic interplay between coagulation abnormalities and disease progression remains poorly defined.
Xitang Li   +16 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications

open access: yesAdvanced Science, EarlyView.
Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin   +3 more
wiley   +1 more source

Type‐II Dirac Fermions in Monolayer In2O: Interplay of Magnetotransport, Spin Hall Effect, and Superconductivity

open access: yesAdvanced Science, EarlyView.
First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu   +6 more
wiley   +1 more source

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

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