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In this work, we investigate magneto-acoustic attenuation in thin film multiferroic Lamb wave delay lines. By leveraging magneto-acoustic interactions, multiferroics have potential to realize passive chip-scale alternatives to bulky ferrite devices. For the first time, magnetic field dependence of magneto-acoustic interactions in multiferroic Lamb wave devices is characterized. Multiferroic heterostructures of aluminum nitride and cobalt iron boron are fabricated into Lamb wave delay lines operating at 7.492 GHz to study the effect of strain nonuniformity on the multiferroic coupling. The attenuation of the Lamb waves is characterized as a function of the magnitude and angle of an applied in-plane bias magnetic field. It is found that the bias magnitude for peak attenuation is a strong function of angle, indicating that it is due to coupling between the Lamb waves and spin wave modes. This is in contrast with current models of attenuation in multiferroic SAW delay lines, where the uniform surface strains couple to ferromagnetic resonance, which has no angular dependence on the in-plane bias field magnitude. These results are the first steps towards passive chip-scale alternatives to ferrite devices utilizing Lamb wave devices, which have better coupling and scalability than their SAW counterparts. [2020-0114]

The magnetoelectric properties of exchange-coupled Ni/CoFeB-based composite multiferroic microstructures are investigated. The strength and sign of the magnetoelastic effect are found to be strongly correlated with the ratio between the thicknesses of two magnetostrictive materials. In cases where the thickness ratio deviates significantly from one, the magnetoelastic behavior of the multiferroic microstructures is dominated by the thicker layer, which contributes more strongly to the observed magnetoelastic effect. More symmetric structures with a thickness ratio equal to one show an emergent interfacial behavior which cannot be accounted for simply by summing up the magnetoelastic effects occurring in the two constituent layers. This aspect is clearly visible in the case of ultrathin bilayers, where the exchange coupling drastically affects the magnetic behavior of the Ni layer, making the Ni/CoFeB bilayer a promising next-generation synthetic magnetic system entirely. This study demonstrates the richness and high tunability of composite multiferroic systems based on coupled magnetic bilayers compared to their single magnetic layer counterparts. Furthermore, because of the compatibility of CoFeB with present magnetic tunnel junction-based spintronic technologies, the reported findings are expected to be of great interest for the development of ultralow-power magnetoelectric memory devices.

An unconditionally stable finite-difference time-domain (FDTD) algorithm is proposed to predict and understand the complex response in strain-mediated multiferroic radio frequency devices, such as antennas. A system of three coupled sets of governing equations is solved simultaneously: 1) Maxwell's equations for electromagnetic (EM) wave propagation; 2) Landau–Lifshitz–Gilbert equation for magnetic spin response; and 3) Newton's law for acoustic behavior. The formulation of this algorithm is elaborated on in detail followed by a demonstration of its capability through the simulation of a 1.3- μ m-thick bulk-acoustic-wave (BAW)-based strain-mediated multiferroic antenna. Analysis of the far-field radiation efficiency of this antenna as a function of magnetic dc bias demonstrates the importance of aligning the ferromagnetic resonance (FMR) and the mechanical BAW resonance to enhance EM radiation performance. Results also show that reducing the magnetic loss, or in other words, reducing the FMR linewidth, represents the dominating feature to achieve higher radiation efficiencies in these antennas.

This study applied and operationalized Bandura’s (1977, 1986) four-step observational learning process (i.e., attention, retention, production, and motivation) to investigate how tour-guides, peer ...

Both lifestyle and structural changes are needed to reduce carbon emissions and limit the impacts of climate change. In a series of three studies, we examine whether undertaking behaviors at the personal level affects (i.e., spills over onto) people's willingness to engage in behaviors at the collective level. In Study 1, we find that none of the personal behaviors measured are negatively associated with collective behavior intentions (willingness to join a campaign to convince elected officials to take action to reduce climate change), but some of the personal behaviors are positively associated with collective behavior intentions. In Study 2, we find that increasing the salience of past personal behaviors does not spill over to collective behavioral intentions. In Study 3, we find that increasing the salience of past personal behavior does not spillover to collective behavioral intentions but does increase support for a carbon tax on companies. We also find that increasing the salience of past behavior increases environmental identity and the perception that one is already taking enough action to reduce climate change. Overall, the results suggest that there are no spillover effects of personal mitigation behaviors on collective mitigation behavioral intentions. Messages that directly encourage collective mitigation behaviors may be more effective at promoting these behaviors than messages that emphasize past personal behaviors.

MAGIS-100 is a next-generation quantum sensor under construction at Fermilab that aims to explore fundamental physics with atom interferometry over a 100-meter baseline. This novel detector will search for ultralight dark matter, test quantum mechanics in new regimes, and serve as a technology pathfinder for future gravitational wave detectors in a previously unexplored frequency band. It combines techniques demonstrated in state-of-the-art 10-meter-scale atom interferometers with the latest technological advances of the world's best atomic clocks. MAGIS-100 will provide a development platform for a future kilometer-scale detector that would be sufficiently sensitive to detect gravitational waves from known sources. Here we present the science case for the MAGIS concept, review the operating principles of the detector, describe the instrument design, and study the detector systematics., Comment: 65 pages, 18 figures

Artificial intelligence frameworks utilizing unsupervised learning techniques can avoid the bottleneck of labeled training data required in supervised machine learning systems, but the programming time of these systems is inherently limited by their hardware implementations. Here, a finite-element model coupling micromagnetics and dynamic strain is used to investigate a multiferroic antiferromagnet as a high-speed artificial synapse in artificial intelligence applications. The stability of strain-induced intermediate antiferromagnetic magnetization states (non-uniform magnetization states between a uniform 0 or 1), along with the minimum time scale at which these states can be programmed is investigated. Results show that due to the antiferromagnetic material's magnetocrystalline anisotropy, two intermediate states (Néel vector 1/3z, 2/3x, and Néel vector 2/3z, 1/3x) between fully x and fully z Néel vector orientations can be successfully programmed using 375 με strain pulses, and that the time associated with this programming is limited to ∼0.3 ns by the material's antiferromagnetic resonance frequency.