Results 191 to 200 of about 2,288,990 (250)

High‐Entropy Engineering and External Magnetic Field Modulation Synergistically Enhance the H2S Sensing Performance of Rare‐Earth Perovskite Ferrites

open access: yesAdvanced Science, EarlyView.
A novel high‐entropy perovskite oxide, (Gd0.2Tb0.2Dy0.2Ho0.2Er0.2)FeO3, was successfully synthesized for advanced hydrogen sulfide gas detection. By synergistically coupling high‐entropy‐induced local lattice distortion with weak magnetic field modulation, the tailored material generates abundant active sites. This innovative dual strategy dramatically
Yunfei Wang   +7 more
wiley   +1 more source

Geometry‐Encoded Actuation as a Structural Interaction Layer in Origami Robots

open access: yesAdvanced Science, EarlyView.
We present geometry‐encoded actuation (GEA), a design framework that integrates multistable origami with liquid crystal elastomer actuators to encode environmental interactions into autonomous structural responses. GEA enables programmable shape transformation without continuous sensing or complex control, achieving robust adaptive manipulation and ...
Jianshu Zhou   +8 more
wiley   +1 more source

Spatially Encoded Protocell Network for Non‐Cascaded Parallel Biocomputation

open access: yesAdvanced Science, EarlyView.
A non‐cascaded, hydrogel‐based proteinosome computational platform is developed, in which redox‐responsive proteinosomes serve as local computing units within a shared reaction–diffusion field. Reductant inputs, countered by an auxiliary glucose gradient, regulate spatially patterned proteinosome disruption, and generate population‐level boundaries ...
Shuqi Wu, Liangfei Tian
wiley   +1 more source

Trustworthy Multimodal Attention Framework for Creep Rupture Life Prediction Under Data‐Scarce Conditions: A Case Study on IN718

open access: yesAdvanced Science, EarlyView.
An attention‐based multimodal deep learning framework is developed to predict the creep life of Ni‐based superalloys by fusing processing parameters with microstructural micrographs. The model achieves high accuracy (R2 = 0.92), aligns with metallurgical principles by capturing δ‐phase influence, and incorporates uncertainty quantification, offering a ...
Haopeng Lv   +10 more
wiley   +1 more source

Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors

open access: yesAdvanced Science, EarlyView.
An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley   +1 more source

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