Results 291 to 300 of about 543,862 (358)

Notes on Piezo-remanent Magnetization of Igneous Rocks II

, 1969
Takashi Nagata, B. J. CARLETON
openalex   +2 more sources

A Promising MM–Fe–Al–Ga–B Permanent Material with Substantially Boosted Magnetic Performance

Advanced Science, EarlyView.
A facile two‐step strategy, Al‐doping toward high‐(BH)max followed by Nd/Pr‐based grain boundary diffusion processing toward high‐Hcj, endows the microcrystalline MM–Fe–Al–Ga–B magnet with substantially boosted magnetic performance [(BH)max = 28.02 MGOe, Hcj = 10.14 kOe].
Wang Chen, Shaoqing Ren, Jiaying Jin, Liang Zhou, Bo Xin, Mingjing Zhao, Mengfan Bu, Xu Li, Chen Wu, Mi Yan   +9 more
wiley   +1 more source

Observation of Topological Spin Textures in Ferrimagnetic Mn_{2 - x}Zn_xSb. [PDF]

Small
Li Y, Nabi MRU, Park H, Liu Y, Rosenkranz S, Petford-Long AK, Hu J, Velthuis SGET, Phatak C.   +8 more
europepmc   +1 more source

Sublattice Magnetization in Several Rare-Earth and Yttrium Iron Garnets by Means of 57Fe NMR

, 1966
Roland Gonano, E. Raymond Hunt, H. Meyer, A. B. Harris   +3 more
openalex   +2 more sources

Orbital Coupling and Spin Textures of Fe/Pd Thin Films Grown on Si Substrate with High Magnetic Fields

Advanced Science, EarlyView.
High magnetic fields (HMFs) regulate orbital coupling and spin polarization in Fe/Pd thin films, promoting crystallization and ordered spin textures. HMF‐assisted growth transitions Fe from amorphous to dense 2D structures, enhancing saturation magnetization and domain uniformity. This strategy advances the design of high‐performance spintronic devices
Xuefeng Wu, Bin Gong, Wenyu Kang, Li Chen, Xu Li, Yaping Wu, Junyong Kang   +6 more
wiley   +1 more source

Efficient spin accumulation carried by slow relaxons in chiral tellurium. [PDF]

Nat Commun
Barts E, Tenzin K, Sławińska J.
europepmc   +1 more source

Study on Magnetization of the Japanese Rocks

, 1962
Naoto Kawai, Shōichi Kume, Haruaki Ito
openalex   +2 more sources

Machine Learning Approach to Characterize Ferromagnetic La0.7Sr0.3MnO3 Thin Films via Featurization of Surface Morphology

Advanced Science, EarlyView.
A machine‐learning approach is presented to characterize ferromagnetic LSMO thin films by featurizing their surface morphology. Through an ensemble model, the non‐linear correlations between surface morphology and the electric/magnetic properties of LSMO thin films are successfully captured.
Sanghyeok Ryou, Jihyun Lim, Minwoo Jang, Kitae Eom, Sunwoo Lee, Hyungwoo Lee   +5 more
wiley   +1 more source

Magnetic localization and manipulation of locking synchronous motors. [PDF]

Commun Eng
Richter M, Masjosthusmann L, Makushko P, Venkiteswaran VK, Makarov D, Misra S.   +5 more
europepmc   +1 more source