Results 191 to 200 of about 11,002 (264)

Synergistic Spin‐Polarization and Single‐Atom Engineering in Magnetic Heterojunctions for Efficient Solar Water Splitting

open access: yesAdvanced Science, EarlyView.
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren   +8 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

open access: yesAdvanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale   +6 more
wiley   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

open access: yesAdvanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang   +14 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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