Results 221 to 230 of about 3,315 (302)

Cavity QED beyond the Jaynes-Cummings model. [PDF]

open access: yesOpt Quantum Electron
Al Ghamdi A, Jose G, Beige A.
europepmc   +1 more source

Ultrathin Li Metal Anodes: Quantitative Design Principles and Manufacturability Across Liquid and Solid‐State Batteries

open access: yesAdvanced Materials, EarlyView.
Ultrathin lithium metal anodes (≤15 µm) offer a promising route to high‐energy‐density batteries due to their high capacity and low potential. This review presents design principles for ultrathin Li, evaluates fabrication strategies, and discusses challenges in liquid and solid‐state cells.
Cheng Wang   +9 more
wiley   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

open access: yesAdvanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung   +9 more
wiley   +1 more source

Miniaturised wideband metasurface polarisation converter with high angular stability. [PDF]

open access: yesSci Rep
Nkimbeng CHS   +6 more
europepmc   +1 more source

Tailoring Phonon‐Driven Responses in α‐MoO3 through Isotopic Enrichment

open access: yesAdvanced Materials, EarlyView.
ABSTRACT The implementation of polaritonic materials into nanoscale devices requires selective tuning of parameters to realize desired spectral or thermal responses. One robust material, α‐MoO3, an orthorhombic crystal boasting three distinct phonon dispersions, provides three polaritonic dispersions of hyperbolic phonon polaritons (HPhPs) across the ...
Thiago S. Arnaud   +31 more
wiley   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

open access: yesAdvanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong   +11 more
wiley   +1 more source

Electric field switching of chiral phonons

open access: yes
Grimes M   +10 more
europepmc   +1 more source

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