Results 61 to 70 of about 684 (200)
The symmetry‐driven coexistence of altermagnetism and (anti)ferroelectricity in perovskites shows a strong dimensional dependence. Upon reducing the system from bulk to the two‐dimensional limit, only C‐type antiferromagnetic order retains ferroelectrically switchable altermagnetism, whereas A‐ and G‐type orders become conventional antiferromagnets ...
Zhou Cui +6 more
wiley +1 more source
Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung +7 more
wiley +1 more source
Composition-induced antiferroelectric phase and giant strain in lead-free (Na y ,Bi z )Ti 1- x O 3(1- x ) -xBaTiO 3 ceramics [PDF]
(Nay,Biz)Ti1-xO3(1-x)- xBaTiO3 ceramics with an excess in Bi3+ and/or a deficiency in Na+ were prepared and investigated. It is found that an antiferroelectric phase can be induced through a modulation of the mole ratio of Na+ and Bi3+.
Luo, Haosu +4 more
core +1 more source
Antiferroelectric Shape Memory Ceramics
Antiferroelectrics (AFE) can exhibit a “shape memory function controllable by electric field”, with huge isotropic volumetric expansion (0.26%) associated with the AFE to Ferroelectric (FE) phase transformation.
Kenji Uchino
doaj +1 more source
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
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
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
Switching on Antiferroelectrics
Antiferroelectrics attract broad attention due to their unusual physical characteristics, chief among which is the double-hysteresis loop that separates their antipolar ground state from the voltage-induced polar phase, which is promising for applications in energy storage and electrocaloric cooling.
Catalan, G. +4 more
openaire +2 more sources
Defects and Lattice Instability in Doped Lead-Based Perovskite Antiferroelectrics: Revisited
This paper is a summary of earlier results that have been completed with recent investigations on the nature and sequence of phase transitions evolving in the antiferroelectric PbZrO3 single crystals doped with niobium and Pb(Zr0.70Ti0.30)O3 ceramics ...
Dariusz Kajewski
doaj +1 more source
An antiferroelectric tunnel junction serves as a reservoir computing node, where field‐induced phase transitions and spontaneous ZrO2 relaxation deliver nonlinear fading memory. An In‐Ga‐Zn oxide interlayer enlarges the memory margin and multibit state richness.
Taegyu Kwon +13 more
wiley +1 more source
The electric-field-modulation (E-modulation) of photoluminescence (PL) properties in bulk ceramics has attracted tremendous interest due to its potential application in optical data storage and communication devices.
Tengfei Lin (1706983) +11 more
core +1 more source

