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Register a new userParametric excitation of an optically silent Goldstone-like phonon mode
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Added by
Dominik Maximilian Juraschek
Publication date
2019
fields
Physics
and research's language is
English
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It has recently been indicated that the hexagonal manganites exhibit Higgs- and Goldstone-like phonon modes that modulate the amplitude and phase of their primary order parameter. Here, we describe a mechanism by which a silent Goldstone-like phonon mode can be coherently excited, which is based on nonlinear coupling to an infrared-active Higgs-like phonon mode. Using a combination of first-principles calculations and phenomenological modeling, we describe the coupled Higgs-Goldstone dynamics in response to the excitation with a terahertz pulse. Besides theoretically demonstrating coherent control of crystallographic Higgs and Goldstone excitations, we show that the previously inaccessible silent phonon modes can be excited coherently with this mechanism.
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Goldstone modes are massless particles resulting from spontaneous symmetry breaking. Although such modes are found in elementary particle physics as well as in condensed matter systems like superfluid helium, superconductors and magnons - structural Goldstone modes are rare. Epitaxial strain in thin films can induce structures and properties not accessible in bulk and has been intensively studied for (001)-oriented perovskite oxides. Here we predict Goldstone-like phonon modes in (111)-strained SrMnO3 by first-principles calculations. Under compressive strain the coupling between two in-plane rotational instabilities give rise to a Mexican hat shaped energy surface characteristic of a Goldstone mode. Conversely, large tensile strain induces in-plane polar instabilities with no directional preference, giving rise to a continuous polar ground state. Such phonon modes with U(1) symmetry could emulate structural condensed matter Higgs modes. The mass of this Higgs boson, given by the shape of the Mexican hat energy surface, can be tuned by strain through proper choice of substrate.
Ion diffusion is important in a variety of applications, yet fundamental understanding of the diffusive process in solids is still missing, especially considering the interaction of lattice vibrations (phonons) and the mobile species. In this work, we introduce two formalisms that determine the individual contributions of normal modes of vibration (phonons) to the diffusion of ions through a solid, based on (i) Nudged Elastic Band (NEB) calculations and (ii) molecular dynamics (MD) simulations. The results for a model ion conductor of $rm{Ge}$-substituted $rm{Li_3PO_4}$ ($rm{Li_{3.042}Ge_{0.042}P_{0.958}O_4}$) revealed that more than 87% of the $rm{Li^+}$ ion diffusion in the lattice originated from a subset of less than 10% of the vibrational modes with frequencies between 8 and 20 THz. By deliberately exciting a small targeted subset of these contributing modes (less than 1%) to a higher temperature and still keeping the lattice at low temperature, we observed an increase in diffusivity by several orders of magnitude, consistent with what would be observed if the entire material (i.e., all modes) were excited to the same high temperature. This observation suggests that an entire material need not be heated to elevated temperatures to increase diffusivity, but instead only the modes that contribute to diffusion, or more generally a reaction/transition pathway, need to be excited to elevated temperatures. This new understanding identifies new avenues for increasing diffusivity by engineering the vibrations in a material, and/or increasing diffusivity by external stimuli/excitation of phonons (e.g., via photons or other interactions) without necessarily changing the compound chemistry.
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Memristors have emerged as key candidates for beyond-von-Neumann neuromorphic or in-memory computing owing to the feasibility of their ultrahigh-density three-dimensional integration and their ultralow energy consumption. A memristor is generally a two-terminal electronic element with conductance that varies nonlinearly with external electric stimuli and can be remembered when the electric power is turned off. As an alternative, light can be used to tune the memconductance and endow a memristor with a combination of the advantages of both photonics and electronics. Both increases and decreases in optically induced memconductance have been realized in different memristors; however, the reversible tuning of memconductance with light in the same device remains a considerable challenge that severely restricts the development of optoelectronic memristors. Here we describe an all-optically controlled (AOC) analog memristor with memconductance that is reversibly tunable over a continuous range by varying only the wavelength of the controlling light. Our memristor is based on the relatively mature semiconductor material InGaZnO (IGZO) and a memconductance tuning mechanism of light-induced electron trapping and detrapping. We demonstrate that spike-timing-dependent plasticity (STDP) learning can be realized in our device, indicating its potential applications in AOC spiking neural networks (SNNs) for highly efficient optoelectronic neuromorphic computing.
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