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Hund's metals, explained

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arxiv 1707.03282 v2 pith:QQYO277T submitted 2017-07-11 cond-mat.str-el cond-mat.supr-con

Hund's metals, explained

classification cond-mat.str-el cond-mat.supr-con
keywords hundfeaturesdopingenhancedinteractionmetalbandscrossover
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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A possible practical definition for a Hund's metal is given, as a metallic phase - arising consistently in realistic simulations and experiments in Fe-based superconductors and other materials - with three features: large electron masses, high-spin local configurations dominating the paramagnetic fluctuations and orbital-selective correlations. These features are triggered by, and increase with the proximity to, a Hund's coupling-favored Mott insulator that is realized for half-filled conduction bands. A clear crossover line is found where these three features get enhanced, departing from the Mott transition at half filling and extending in the interaction/doping plane, between a normal (at weak interaction and large doping) and a Hund's metal (at strong interaction and small doping). This phenomenology is found identically in models with featureless bands, highlighting the generality of this physics and its robustness by respect to the details of the material band structures. Some analytical arguments are also given to gain insight into these defining features. Finally the attention is brought on the recent theoretical finding of enhanced/diverging electronic compressibility near the Hund's metal crossover, pointing to enhanced quasiparticle interactions that can cause or boost superconductivity or other instabilities.

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Cited by 2 Pith papers

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  1. Revealing Hund superdispersion with tunneling spectroscopy

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    Tunneling spectroscopy reveals Hund-induced superdispersion in Sr2RuO4, matching DFT+DMFT predictions via non-monotonic real-part self-energy.

  2. Exact downfolding and its perturbative approximation

    cond-mat.str-el 2025-07 unverdicted novelty 6.0

    Derives an exact downfolded effective model by integrating out the rest space, states conditions for perturbative truncation, and formally recovers cRPA with corrections.