Search arXivSearch

arXiv · 1506.03056

Traveling surface spin-wave resonance spectroscopy using surface acoustic waves

Abstract

Coherent gigahertz-frequency surface acoustic waves (SAWs) traveling on the surface of a piezoelectric crystal can, via the magnetoelastic interaction, resonantly excite traveling spin waves in an adjacent thin-film ferromagnet. These excited spin waves, traveling with a definite in-plane wave-vector q enforced by the SAW, can be detected by measuring changes in the electro-acoustical transmission of a SAW delay line. Here, we provide a first demonstration that such measurements constitute a precise and quantitative technique for spin-wave spectroscopy, providing a means to determine both isotropic and anisotropic contributions to the spin-wave dispersion and damping. We demonstrate the effectiveness of this spectroscopic technique by measuring the spin-wave properties of a Ni thin film for a large range of wave vectors,q = 2.5 x 10^4 - 8 x 10^4 cm^(-1), over which anisotropic dipolar interactions vary from being negligible to quite significant.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Praveen G. Gowtham, Takahiro Moriyama, Daniel C. Ralph, Robert A. Buhrman. 2016-03-09. Traveling surface spin-wave resonance spectroscopy using surface acoustic waves. https://doi.org/10.1063/1.4938390

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling

Recent advances in physics-augmented neural networks have enabled thermodynamically consistent data-driven constitutive modeling of complex inelastic materials. Most existing approaches, however, implicitly adopt a specific thermodynamic framework and embed structural assumptions such as normality, dual dissipation potentials, or other structure from manually constructed models directly into the learning architecture. Consequently, differences in predictive performance may arise not only from data or network design, but also from the underlying theoretical assumptions. In this work, we present a unified comparison of several thermodynamically consistent inelastic modeling frameworks from a machine learning perspective. We consider internal-variable formulations with dissipation potential, generalized standard materials, and metriplectic structures, and we analyze their structural assumptions, admissible dependencies, convexity requirements, and implications for dissipation and evolution. Each framework is implemented within a common neural potential architecture based on invariant representations and neural ordinary differential equations. This unified setting ensures that performance differences can be attributed to thermodynamic structure rather than architectural variation. The models are trained and evaluated on three representative inelastic datasets generated from high-fidelity representative volume element simulations: an elastoplastic alloy, a viscoelastic composite, and a rate-dependent crystal plasticity polycrystal. By isolating the role of thermodynamic structure, we assess how restrictions such as duality, normality, operator-based evolution, and convexity influence learnability, expressiveness, stability, and generalization.

cond-mat.mtrl-sci

Berry Curvature Driven Transport in Silicon-Compatible Altermagnetic $α$-MnTe Thin Films

Integrating spin-dependent functionality with mainstream semiconductor technology is a central goal of modern spintronics, yet most candidate materials remain incompatible with silicon-based platforms. Here, we report the direct epitaxial integration of $α$-MnTe thin films on Si(111) via molecular beam epitaxy and demonstrate a robust anomalous Hall effect (AHE) in this silicon-compatible altermagnetic system. Despite the absence of net bulk magnetization, the films exhibit a pronounced hysteretic Hall response, providing transport evidence consistent with finite Berry curvature generated by symmetry breaking in the thin-film geometry. High-resolution structural and spectroscopic characterization confirms phase-pure, epitaxial growth with hexagonal NiAs-type symmetry, while magnetotransport measurements reveal correlated hysteresis in both transverse and longitudinal channels with systematic temperature evolution. First-principles calculations reveal substantial uncompensated Berry curvature arising from the spin-split band structure, consistent with altermagnetic symmetry and the origin of the observed Hall response. These results establish MnTe/Si(111) as a silicon-compatible altermagnetic platform and chart a concrete pathway for embedding Berry-phase-driven functionalities into scalable semiconductor device architectures.

cond-mat.mtrl-sci

All-Optical Control of Interfacial Polarization in MoS$_2$/WSe$_2$ Heterobilayers

All-optical tuning of van der Waals heterostructures with coherent radiation offers a promising path toward ultrafast memory and optoelectronic devices. In the first-principles framework of real-time time-dependent density functional theory, we predict the induction of a persistent, long-lived out-of-plane polarization in MoS$_2$/WSe$_2$ heterobilayers, resonantly driven by intense ultrafast pulses. While weak fields preserve the intrinsic type-II band alignment, intermediate intensities trigger a four-fold enhancement of interlayer charge transfer. By analyzing the high-harmonic generation spectrum, we identify a transition from the perturbative to the strong-field regime inducing photoinduced interfacial polarity. We additionally show that lattice strain, ubiquitously present in heterobilayers, can be used as additional knob to adjust the resonant condition without compromising the permanent dipole induction. Our findings provide a theoretical blueprint for the all-optical manipulation of polar phases in low-dimensional heterostructures at the femtosecond scale.

cond-mat.mtrl-sci