Results 221 to 230 of about 39,608 (292)

Metarhizium anisopliaeMitigates the Phytotoxicity of Lead and Nanoplastics on Rice by Modifying Physiological, Transcriptomic, Metabolomic Activities, and Soil Microbiome

open access: yesAdvanced Science, EarlyView.
Metarhizium anisopliae alleviates the phytotoxic effects of polyethylene nanoplastics (NP) and lead (Pb) in rice by decreasing Pb uptake, restoring antioxidant and hormonal equilibrium, and promoting growth. Additionally, the fungus modifies the rhizosphere microbiota, enhancing both contaminant tolerance and plant growth, thereby effectively ...
Jing Peng   +7 more
wiley   +1 more source

Neural Network‐Based Permittivity Engineering of Magnetic Absorbers for Customizable Microwave Absorption

open access: yesAdvanced Science, EarlyView.
A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu   +9 more
wiley   +1 more source

Enhancing Interfacial Dioxygen Bridging Dynamics of Waste‐Derived Cathode Catalysts for Augmented High‐Rate Performance in Li‐O2 Batteries

open access: yesAdvanced Science, EarlyView.
This study fabricates Fine Slag/Ti4O7@TiC hybrids with interfacial dioxygen bridge coupling to optimize oxygen redox dynamics in lithium‐oxygen batteries (LOBs). Lattice distortion from oxygen vacancies and inherent charge repulsion of Ti‐O‐C interfacial coupling reconstruct and refine the surface coordination environment.
Jixiong Zhang   +6 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

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