Nature Physics, Published online: 15 July 2024; doi:10.1038/s41567-024-02537-6
Plasmonic excitations can enhance the interaction between a metal and molecules adsorbed onto its surface. This Review summarizes the different effects involved in this process and places them into a framework based on electron scattering.
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- Nature Physics, Published online: 15 July 2024; doi:10.1038/s41567-024-02552-7 The observation of phase modes of charge density wave has been a long-standing challenge. Such low-energy phase excitations have now been seen in a transition metal dichalcogenide.
- Nature Physics, Published online: 11 July 2024; doi:10.1038/s41567-024-02579-w High harmonic generation has long been successfully described using the semi-classical three-step model. However, recent progress has introduced a quantum optical formulation, exposing the limitations of the semi-classical picture.
- Nature Physics, Published online: 10 July 2024; doi:10.1038/s41567-024-02575-0 Inducing superconductivity in quantum anomalous Hall insulators is crucial to realize topological superconductors. Now a study shows superconducting correlations in the quantum anomalous Hall state, which can convert electrons on its one-way path into holes.
- Nature Physics, Published online: 10 July 2024; doi:10.1038/s41567-024-02574-1 The superconducting proximity effect has not been experimentally demonstrated in a quantum anomalous Hall insulator. Now this effect is observed in the chiral edge state of a ferromagnetic topological insulator.
- Nature Physics, Published online: 09 July 2024; doi:10.1038/s41567-024-02572-3 The growth of a biofilm—a bacterial colony attached to a surface—is governed by a trade-off between horizontal and vertical expansion. Now, it is shown that this process significantly depends on the contact angle at the biofilm’s edge.
- Nature Physics, Published online: 09 July 2024; doi:10.1038/s41567-024-02534-9 As the energy consumption of neural networks continues to grow, different approaches to deep learning are needed. A neuromorphic method offering nonlinear computation based on linear wave scattering can be implemented using integrated photonics.
- Nature Physics, Published online: 09 July 2024; doi:10.1038/s41567-024-02531-y Nonlinearity is crucial for sophisticated tasks in machine learning but is often difficult to engineer outside of electronics. By encoding the inputs in parameters of the system, linear systems can realize efficiently trainable nonlinear computations.