Results 241 to 250 of about 280,801 (322)

AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices

open access: yesAdvanced Science, EarlyView.
Triboelectric nanogenerators (TENGs) enable sustainable energy harvesting and self‐powered sensing but face challenges in material optimization, fabrication, and stability. Integrating artificial intelligence (AI) enhances TENG performance through machine learning, improving energy output, adaptability, and predictive maintenance.
Aiswarya Baburaj   +4 more
wiley   +1 more source

Programmable Metamaterials with Perforated Shell Group Supporting Versatile Information Processing

open access: yesAdvanced Science, EarlyView.
This study proposes a novel mechanical metamaterial with high‐density memory based on multi‐stable perforated shells to realize multi‐layer information encoding, storage, decoding, and reading. The metamaterial can perform more application‐oriented tasks to process information, such as encryption and dynamic behavior regulation, which hopefully enables
Xiaoyuan Ma   +3 more
wiley   +1 more source

Giant Modulation of Interlayer Coupling in Twisted Bilayer ReS2

open access: yesAdvanced Science, EarlyView.
Twist angle in stacked bilayer ReS2 can modulate 30% of interlayer coupling and the whole range of exciton energy between 1L and 2L ReS2. Abstract Stacking monolayers of two‐dimensional (2D) transition metal dichalcogenides with different twist angles can provide a way to tune their quantum optical and electronic characteristics.
Krishna P. Dhakal   +14 more
wiley   +1 more source

Atomic‐Level Strain Sensing and Piezoresistance Effect in a 1D Single‐Atom Chain

open access: yesAdvanced Science, EarlyView.
The atomic‐scale piezoresistance effect of the Ag single‐atom chain is explored using strain characterization and electrical measurement. Single‐atom chain has the potential to serve as a strain sensor with atomic‐level precision, overcoming the challenge of low temporal resolution in a transmission electron microscope.
Zhi Qu   +6 more
wiley   +1 more source

Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites

open access: yesAdvanced Science, EarlyView.
Selective carbonylation sites (SCANS) are conceptualized, designed, evaluated, and released. SCANS captures segment‐level, protein‐level, and residue embeddings features. It utilizes elaborate loss function to penalize cross‐predictions at the residue level.
Jian Zhang   +6 more
wiley   +1 more source

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