997 citations · 4.4k across the 57 of their papers we have counts for
58 papers
Study of the electronic properties of topological kagome metals YVSn and GdVSn
Ganesh Pokharel, Samuel M. L. Teicher, Brenden R. Ortiz +6
The synthesis and characterization of vanadium-based kagome metals YVSn and GdVSn are presented. X-ray diffraction, magnetization, magnetotransport, and heat capaci…
History of Ferroelectrics -- A Crystallography Perspective
Nicola A. Spaldin, Ram Seshadri
"Underlying the whole treatment is the assumption that the physical properties of a solid are closely related to its structure, and that the first step to understanding the physica…
Magnetoentropic mapping and computational modeling of cycloids and skyrmions in the lacunar spinels GaVS and GaVSe
Julia L. Zuo, Daniil Kitchaev, Emily C. Schueller +4
We report the feasibility of using magnetoentropic mapping for the rapid identification of magnetic cycloid and skyrmion phases in uniaxial systems, based on the GaV4S8 and GaV4Se8…
Understanding Magnetic Phase Coexistence in RuMnFeSn Heusler Alloys: A Neutron Scattering, Thermodynamic, and Phenomenological Analysis
Eric McCalla, Emily E. Levin, Jason E. Douglas +6
The random substitutional solid solution between the antiferromagnetic (AFM) full-Heusler alloy RuMnSn and the ferromagnetic (FM) full-Heusler alloy RuFeSn provides a rare…
Fermi surface mapping and the nature of charge density wave order in the kagome superconductor CsVSb
Brenden R. Ortiz, Samuel M. L. Teicher, Linus Kautzsch +6
The recently discovered family of AVSb (A: K, Rb Cs) kagome metals possess a unique combination of nontrivial band topology, superconducting ground states, and signatures o…
Learning the Crystal Structure Genome for Property Classification
Yiqun Wang, Xiao-Jie Zhang, Fei Xia +3
Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structu…