Results 221 to 230 of about 32,160,307 (285)

MetaboSense: An Integrated Quantum Dot‐Mediated Aptamer Assay and Modular Microfluidic Platform for Continuous In‐Line Monitoring of Lung Metabolism During Ex Vivo Perfusion

open access: yesAdvanced Science, EarlyView.
MetaboSense is a first‐of‐its‐kind microfluidic platform enabling continuous, in‐line monitoring of glucose and lactate during ex vivo lung perfusion. Combining a quantum dot–mediated aptamer assay with mixing, depletion, and optofluidic detection modules, it achieves 60–s temporal resolution and shows strong agreement with standard blood gas analyzers,
Sanjana Srikant   +14 more
wiley   +1 more source

Computationally Evidence‐Grounded Sequence‐First Design of Peptide Binders

open access: yesAdvanced Science, EarlyView.
BOND‐PEP enables controllable, sequence‐first peptide binder design by grounding generation in binding evidence retrieved for each target. It uses topology‐conditioned message passing to integrate relevant peptide examples with the target protein sequence, forming a residue‐level representation that guides the generation of diverse, target‐specific ...
Wenze Ding
wiley   +1 more source

3D Printed Meter‐Scale Soft Origami Robots Capable of Load‐Bearing Actuation Via Crease Stiffness Modulation

open access: yesAdvanced Science, EarlyView.
Origami has inspired numerous soft deployable mechanisms for safe human‐robot interaction, while its intrinsic kinematic instability at arbitrary configurations limited their practical robotic application. This work presents a 3D printed meter‐scale origami robotic actuator capable of load‐bearing deformation through creaseline stiffness modulation.
Sung Yol Yu   +5 more
wiley   +1 more source

Inverse Design of Pre‐Strain via a Predictive Electromechanical Model for Enhanced Strain Sensing

open access: yesAdvanced Science, EarlyView.
An analytical electromechanical model rooted in microcrack evolution mechanics is globally calibrated from only eight pre‐strain datasets, enabling prediction of the complete sensing response at untested pre‐strain values within the calibrated design space (R2 > 0.99).
Jia‐Chen Shang   +10 more
wiley   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes

open access: yesAdvanced Science, EarlyView.
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley   +1 more source

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