Results 191 to 200 of about 505,866 (269)

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

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

Soft Hardware, Flowing Software: Reconfigurable Microfluidics for Adaptable Chemical Computation

open access: yesAdvanced Materials, EarlyView.
A reconfigurable microfluidic platform based on soft, photo‐printable, and chemically erasable hydrogel structures printed and erased in situ is used to control flow routing, mixing, chemical patterning, and even chemical computing. Using hardware to control chemical computations decouples logic function from molecular composition, demonstrated via ...
Piet J. M. Swinkels   +4 more
wiley   +1 more source

Using a Zero‐Strain Reference Electrode to Distinguish Anode and Cathode Volume Changes in a Solid‐State Battery

open access: yesAdvanced Materials Interfaces, EarlyView.
Volume changes of a solid‐state battery cell are separated into the individual contributions of anode and cathode. Simultaneously determining the “reaction volumes” of both electrodes requires a reference electrode with a pressure‐independent potential.
Mervyn Soans   +5 more
wiley   +1 more source

Conductive Additives for Next‐Generation Batteries: Emphasizing the Potential of Bio‐Derived 3D Carbon Architectures at Electrode–Electrolyte Interfaces

open access: yesAdvanced Materials Interfaces, EarlyView.
3D conductive frameworks can maintain continuous electron transport, mechanical stability, and interfacial integrity, helping next‐generation batteries operate more efficiently. This Review examines their relevance to Si anodes, all‐solid‐state batteries, and dry‐processed electrodes, and highlights bio‐derived carbons as sustainable, structurally ...
SeoYoung Ha   +5 more
wiley   +1 more source

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