Results 211 to 220 of about 518,702 (319)

Beyond Passive Substituents: Tosyl-Directed Self-Templation Enables Selective Pillar[4 + 1]arene Formation and Topology Switching. [PDF]

open access: yesJ Am Chem Soc
Ruengsuk A   +8 more
europepmc   +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

The Topology of Involutions [PDF]

open access: yesProceedings of the National Academy of Sciences, 1933
openaire   +2 more sources

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

open access: yesAdvanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano   +5 more
wiley   +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

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