Results 91 to 100 of about 13,292,628 (203)
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
Data-Driven and Physics-Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence. [PDF]
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Hui W, Wang Y, Zhang T, Chen Y, Pan M.
europepmc +2 more sources
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
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
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu +5 more
wiley +1 more source
From Folding Mechanics to Robotic Function: A Unified Modeling Framework for Compliant Origami
A geometry‐consistent DDG framework captures compliant origami deformation from rigid‐like folding to soft panel bending. By tuning crease and panel stiffness, bistable snap‐through responses transform into smooth monostable deformation, enabling programmable stability and robot‐scale locomotion.
Bohan Zhang +7 more
wiley +1 more source
The Intent-Field: A Field-Theoretic Architecture of Attention, Tuning, and State Control
This chapter presents the Intent-Field as a structural component within a field-based architecture of experience generation. Intent is defined as directional bias emerging from desire, governing the switching, opening, and closing of experience-fields.
Zhao, Xiangbin
core +1 more source
Probing Electrocatalyst Design for Product Selectivity in CO2 Reduction
Selective CO2 electroreduction is controlled by catalyst structure, dynamic surface reconstruction, adsorbate interactions, and reaction microenvironment. This review summarizes Cu‐ and non‐Cu‐based catalysts, single‐atom and molecular systems, degradation pathways, and operando/computational strategies for steering CO2RR toward hydrocarbons ...
Suvodeep Sen +5 more
wiley +1 more source
HfO2‐based ferroelectrics exhibit wake‐up and fatigue behaviors during electrical cycling, significantly affecting device endurance and reliability. These phenomena are governed by defect dynamics, including oxygen vacancy redistribution and charge trapping.
Hongseok Kim +6 more
wiley +1 more source
Ferroelectric Catalysts in the Hydrogen Evolution Reaction: A Perspective
This perspective summarizes recent advances in ferroelectric (FE) catalysts for the hydrogen evolution reaction (HER). It first introduces HER fundamentals and FE mechanisms, then classifies FE catalysts into single‐phase, single‐atom‐modified, heterostructured, and other engineered types, with representative examples.
Rongxuan Lu +6 more
wiley +1 more source
EMPIRICAL LIKELIHOOD ESTIMATORS OF THE LINEAR SIMULTANEOUS EQUATIONS MODEL [PDF]
Information theoretic estimators are specified for a system of linear simultaneous equations, including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood.
Judge, George G. +2 more
core

