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20022026
most citedFirst M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole

4.3k citations

Showing 2025 · cond-mat.mtrl-sciShow all

48 papers · 2 filters

cond-mat.mtrl-sci2025

First-principles study of magnetic and spin-dependent transport properties of Mn2VZ (Z = Al, Ga) with negative spin polarization using a disordered local moment approach at finite temperatures

Shogo Yamashita, Esita Pandey, Gerhard H. Fecher +2

First-principles studies were performed on two Mn-based ferrimagnetic Heusler compounds with L21 and B2 structures, that is, Mn2VZ (Z = Al or Ga). The aim was to investigate their…

cond-mat.mtrl-sci2025★ 1 cited

Anisotropic Band-Split Magnetism in Magnetostrictive CoFeO

Harry Lane, Guratinder Kaur, Masahiro Kawamata +9

Single crystal spinel CoFeO exhibits the largest room-temperature saturation magnetostriction among non-rare-earth compounds and a high Curie temperature ( K)…

cond-mat.mtrl-sci2025★ 3 cited

2D-RIXS: Resonant inelastic x-ray scattering microscopy with high energy and spatial resolutions

Kohei Yamamoto, Hakuto Suzuki, Jun Miyawaki

A two-dimensional resonant inelastic x-ray scattering (2D-RIXS) microscopy system has been developed at the beamline BL02U of NanoTerasu. The instrument combines a Wolter type-I mi…

cond-mat.mtrl-sci2025

Electric Current Control of Helimagnetic Chirality from a Multidomain State in the Helimagnet MnAu

Yuta Kimoto, Hidetoshi Masuda, Jun-ichiro Ohe +3

In this paper, we study the domain wall dynamics under electric current in the helimagnet MnAu. We have found that the threshold electric current of the transition from a multi…

cond-mat.mtrl-sci2025★ 19 cited

Physically Interpretable Descriptors Drive the Materials Design of Metal Hydrides for Hydrogen Storage

Seong-Hoon Jang, Di Zhang, Hung Ba Tran +5

Designing metal hydrides for hydrogen storage remains a longstanding challenge due to the vast compositional space and complex structure-property relationships. Herein, for the fir…

cond-mat.mtrl-sci2025

Deep Learning-Based Extraction of Promising Material Groups and Common Features from High-Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Akira Takahashi, Yu Kumagai, Arata Takamatsu +1

We report an interpretation method for deep learning models that allows us to handle high-dimensional spectral data in materials science. The proposed method uses feature extractio…