Results 221 to 230 of about 4,798,915 (301)

Electric‐Field‐Controlled Interconversion of Antiferromagnetic States in a Two‐Dimensional Antiferroelectric Halide Perovskite

open access: yesAdvanced Science, EarlyView.
Electric‐field‐controlled antiferroelectric switching offers a ferroic pathway for reversible interconversion between symmetry‐distinct antiferromagnetic states in a two‐dimensional halide perovskite. A spin‐split altermagnet transforms into a spin‐degenerate type‐IV antiferromagnet through field‐driven structural symmetry reconstruction, enabling ...
Wan Zhao   +7 more
wiley   +1 more source

Enhancing Near‐Room‐Temperature Thermoelectric Performance of n‐Type Mg3(Sb, Bi)2‐Based Materials via ZrB2 Heterointerface Engineering

open access: yesAdvanced Science, EarlyView.
A conductive ZrB2 ceramic composite strategy was developed for Mg3(Sb, Bi)2 thermoelectrics to regulate carrier transport and phonon scattering through heterointerface engineering. The 1.0 wt.% ZrB2 composite achieved enhanced room‐temperature performance, with a power factor of 28.51 µW cm−1 K−2 and a peak ZT of 1.22 at 573 K.
Yangyang Xu   +7 more
wiley   +1 more source

Redeneren met figuren als Euclides [PDF]

open access: yes, 2017
Hogendijk, J.P.   +2 more
core  

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

open access: yesAdvanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang   +8 more
wiley   +1 more source

Logaritmen: Hoe en waarom [PDF]

open access: yes, 2017
Fundamental mathematics   +2 more
core  

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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