Quantum spin liquids are exotic states of matter that form when strongly frustrated magnetic interactions induce a highly entangled quantum paramagnet far below the energy scale of the magnetic interactions. Three-dimensional cases are especially challenging due to the significant reduction of the influence of quantum fluctuations. Here, we report the magnetic characterization of K_{2}Ni_{2}(SO_{4})_{3} forming a three-dimensional network of Ni^{2+} spins. Using density functional theory calculations, we show that this network consists of two interconnected spin-1 trillium lattices. In the absence of a magnetic field, magnetization, specific heat, neutron scattering, and muon spin relaxation experiments demonstrate a highly correlated and dynamic state, coexisting with a peculiar, very small static component exhibiting a strongly renormalized moment. A magnetic field B≳4 T diminishes the ordered component and drives the system into a pure quantum spin liquid state. This shows that a system of interconnected S=1 trillium lattices exhibits a significantly elevated level of geometrical frustration.
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http://dx.doi.org/10.1103/PhysRevLett.127.157204 | DOI Listing |
ACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFNano Lett
January 2025
Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
Realizing field-free switching of perpendicular magnetization by spin-orbit torques is crucial for developing advanced magnetic memory and logic devices. However, existing methods often involve complex designs or hybrid approaches, which complicate fabrication and affect device stability and scalability. Here, we propose a novel approach using -polarized spin currents for deterministic switching of perpendicular magnetization through interfacial engineering.
View Article and Find Full Text PDFNano Lett
January 2025
Centre de Nanosciences et de Nanotechnologies, CNRS, Université Paris-Saclay, 91120 Palaiseau, France.
Multifunctional hardware technologies for neuromorphic computing are essential for replicating the complexity of biological neural systems, thereby improving the performance of artificial synapses and neurons. Integrating ionic and spintronic technologies offers new degrees of freedom to modulate synaptic potentiation and depression, introducing novel magnetic functionalities alongside the established ionic analogue behavior. We demonstrate that magneto-ionic devices can perform as synaptic elements with dynamically tunable depression linearity controlled by an external magnetic field, a functionality reminiscent of neuromodulation in biological systems.
View Article and Find Full Text PDFNano Lett
January 2025
Jiangxi Provincial Key Laboratory of Green Hydrogen and Advanced Catalysis, College of Physics, Communication and Electronics, Jiangxi Normal University, 99 Ziyang Avenue, Nanchang 330022, Jiangxi, China.
studies of the relationship between surface spin configurations and spin-related electrocatalytic reactions are crucial for understanding how magnetic catalysts enhance oxygen evolution reaction (OER) performance under magnetic fields. In this work, 2D FeSe nanosheets with rich surface spin configurations are synthesized via chemical vapor deposition. magnetic force microscopy and Raman spectroscopy reveal that a 200 mT magnetic field eliminates spin-disordered domain walls, forming a spin-ordered single-domain structure, which lowers the OER energy barrier, as confirmed by theoretical calculations.
View Article and Find Full Text PDFJ Mol Model
January 2025
School of Chemical and Environmental Engineering, China University of Mining and Technology-Beijing, Haidian District, Ding No.11 Xueyuan Road, Beijing, 100083, People's Republic of China.
Context: Understanding the structural characteristics of coal at the molecular level is fundamental for its effective utilization. To explore the molecular structure characteristic, the long-flame coal from Daliuta (DLT), coking coal from Yaoqiao (YQ), and anthracite from Taixi (TX) were investigated using various techniques such as elemental analysis, Fourier transform infrared spectroscopy, solid-state C nuclear magnetic resonance spectroscopy, and X-ray photoelectron spectroscopy. Based on the structural parameters, the coal molecular model was constructed and optimized.
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