Results 191 to 200 of about 281,884 (245)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

open access: yesAdvanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang   +15 more
wiley   +1 more source

Low Power Optoelectronic Neuromorphic Memristor for In‐Sensor Computing and Multilevel Hardware Security Communications

open access: yesAdvanced Science, EarlyView.
ABSTRACT Conventional software‐based encryption faces mounting limitations in power efficiency and security, inspiring the development of emerging neuromorphic computing hardware encryption. This study presents a hardware‐level multi‐dimensional encryption paradigm utilizing optoelectronic neuromorphic devices with low energy consumption of 3.3 fJ ...
Bo Sun   +3 more
wiley   +1 more source

Active Metamaterials with Tunable Shear Nonreciprocity and Nonlinear Dynamics

open access: yesAdvanced Science, EarlyView.
Active gear‐based mechanical metamaterials enable simultaneous control of translational and torsional stiffnesses by 30–100×, break shear reciprocity under positive versus negative loads, broadly tune resonant frequencies, and offer programmable dynamic responses.
Xin Fang, Miao Yu, Dianlong Yu, Li Cheng
wiley   +1 more source

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