Results 181 to 190 of about 3,751,804 (256)

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

open access: yesAdvanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne   +12 more
wiley   +1 more source

Subicular spatial codes arise from predictive mapping. [PDF]

open access: yesNat Commun
Bennett L   +10 more
europepmc   +1 more source

Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency

open access: yesAdvanced Science, EarlyView.
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun   +9 more
wiley   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

open access: yesAdvanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu   +9 more
wiley   +1 more source

scTIDE: Deciphering Critical Transitions Through Cell‐Perturbed Manifold Graphs and Optimal Transport Conditional Flow Matching

open access: yesAdvanced Science, EarlyView.
scTIDE identifies single‐cell tipping points by combining manifold‐based graph representations with optimal‐transport conditional flow matching, which preserves intrinsic topology and models distributional dynamics. It supports critical‐transition detection at individual‐cell resolution, prediction of unseen cells, and dimensionality reduction and ...
Jiayuan Zhong   +6 more
wiley   +1 more source

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