Results 191 to 200 of about 5,612,993 (295)

Quantum-inspired Ising machine using sparsified spin connectivity. [PDF]

open access: yesSci Rep
Shimada M   +4 more
europepmc   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

open access: yesAdvanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su   +13 more
wiley   +1 more source

Unveiling a Hidden Conversion Pathway in CoSe2 Anodes via Rationally Designed CNT‐Interwoven Hollow Carbon Microclusters for High‐Performance Potassium‐Ion Batteries

open access: yesAdvanced Science, EarlyView.
A rational architectural design of hierarchical, CNT‐interwoven hollow carbon microclusters unlocks and stabilizes a unique monoclinic Co3Se4‐mediated conversion–insertion pathway for potassium storage. This structural confinement effectively guides the reaction kinetics and accommodates severe mechanical strain.
Ho Rim Kim   +8 more
wiley   +1 more source

From Nash Equilibrium to Social Optimum and Back: A Mean Field Perspective. [PDF]

open access: yesAppl Math Optim
Carmona R   +3 more
europepmc   +1 more source

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

open access: yesAdvanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning   +3 more
wiley   +1 more source

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