Constraining the Crustal and Mantle Conductivity Structures Beneath Islands by a Joint Inversion of Multi‐Source Magnetic Transfer Functions

Chen, Chaojian; Kuvshinov, Alexey; Kruglyakov, Mikhail; Munch, Federico D.; Rigaud, Rafael

doi:10.1029/2022jb024106

Cited by 9 publications

(5 citation statements)

References 114 publications

(202 reference statements)

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“…We find that the contribution of proton for Earth‐relevant water contents is comparable to the sum of all other three conduction mechanisms in bridgmanite (i.e., the conductivity of dry bridgmanite) when hydrogen is incorporated as (Mg + 2H) Si or (Al + H) Si defects. The 1D conductivity‐depth profiles in the lower mantle, as determined from electromagnetic induction studies, are shown in Figure 8b (Chen et al, 2022; Civet et al., 2015; Civet & Tarits, 2013; Grayver et al., 2017; Kuvshinov & Olsen, 2006; Olsen, 1999a, 1999b; Puthe et al., 2015; Velimsky, 2010; Verhoeven et al., 2021; Yao, Ren, Pan, et al, 2023; Yao, Ren, Tang, et al, 2023). Most of these conductivity data fall within two orders of magnitude (0.1–10 S m −1 ) and generally remain nearly constant or slightly increase with increasing depth.…”

Section: Discussionmentioning

confidence: 99%

Hydrogen Diffusion in the Lower Mantle Revealed by Machine Learning Potentials

Peng,

Deng

2024

JGR Solid Earth

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Hydrogen may be incorporated into nominally anhydrous minerals including bridgmanite and post‐perovskite as defects, making the Earth's deep mantle a potentially significant water reservoir. The diffusion of hydrogen and its contribution to the electrical conductivity in the lower mantle are rarely explored and remain largely unconstrained. Here we calculate hydrogen diffusivity in hydrous bridgmanite and post‐perovskite, using molecular dynamics simulations driven by machine learning potentials of ab initio quality. Our findings reveal that hydrogen diffusivity significantly increases with increasing temperature and decreasing pressure, and is considerably sensitive to hydrogen incorporation mechanism. Among the four defect mechanisms examined, (Mg + 2H)Si and (Al + H)Si show similar patterns and yield the highest hydrogen diffusivity. Hydrogen diffusion is generally faster in post‐perovskite than in bridgmanite, and these two phases exhibit distinct diffusion anisotropies. Overall, hydrogen diffusion is slow on geological time scales and may result in heterogeneous water distribution in the lower mantle. Additionally, the proton conductivity of bridgmanite for (Mg + 2H)Si and (Al + H)Si defects aligns with the same order of magnitude of lower mantle conductivity, suggesting that the water distribution in the lower mantle may be inferred by examining the heterogeneity of electrical conductivity.

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Section: Discussionmentioning

confidence: 99%

Hydrogen Diffusion in the Lower Mantle Revealed by Machine Learning Potentials

Peng,

Deng

2024

JGR Solid Earth

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“…The C-responses at coastal observatories are significantly influenced by ocean induction effects (OIEs) due to the large contrast in conductivity between oceans and continents, especially for responses over short periods [ 27 , 28 , 29 , 30 ]. Some of our selected observatories are located near the coastline, so we examine the OIEs on C-responses.…”

Section: Methodsmentioning

confidence: 99%

A Mantle Plume Beneath South China Revealed by Electrical Conductivity Obtained from Three-Dimensional Inversion of Geomagnetic Data

Liu

2023

Sensors

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A three-dimensional electrical conductivity model of the mantle beneath South China is presented using the geomagnetic depth sounding method in this paper. The data misfit term in the inversion function is measured by the L1-norm to suppress the instability caused by large noises contained in the observed data. To properly correct the ocean effect in responses at coastal observatories, a high-resolution (1° × 1°) heterogeneous and fixed shell is included in inversion. The most striking feature of the obtained model is a continuous high-conductivity anomaly that is centered on ~(112° E, 27° N) in the mantle. The average conductivity of the anomaly appears to be two to four times higher than that of the global average models at the most sensitive depths (410–900 km) of geomagnetic depth sounding. Further analysis combining laboratory-measured conductivity models with the observed conductivity model shows that the anomaly implies excess temperature in the mantle. This suggests the existence of a mantle plume, corresponding to the Hainan plume, that originates in the lower mantle, passes through the mantle transition zone, and enters the upper mantle. Our electrical conductivity model provides convincing evidence for the mantle plume beneath South China.

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“… 2021 ; Kruglyakov and Kuvshinov 2022 ; Chen et al. 2023 ). However, tippers at inland observatories, abbreviated as CBT, JGU, and MLA in Fig.…”

Section: Introductionmentioning

confidence: 99%

Enormously large tippers observed in southwest China: can realistic 3-D EM modeling reproduce them?

Chen

Kruglyakov

et al. 2023

Earth Planets Space

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Vertical magnetic transfer functions (tippers) estimated at a global/continental net of geomagnetic observatories/sites can be used to image the electrical conductivity structure of the Earth’s crust and upper mantle (down to around 200 km). We estimated tippers at 54 geomagnetic observatories across China, aiming eventually to invert them in terms of subsurface three-dimensional (3-D) conductivity distribution. Strikingly, we obtained enormously large tippers at three inland observatories in southwest China. Large tippers are often observed at coastal/island observatories due to high conductivity contrasts between resistive bedrock and conductive seawater. However, tippers at those inland observatories appeared to be a few times larger than coastal/island tippers. As far as we know, such large tippers (reaching value 3) were never reported in any region worldwide. We perform electromagnetic simulations in 3-D conductivity models mimicking the geological setting and demonstrate that enormously large tippers are feasible and can be attributed to a current channeling effect. Graphical Abstract

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Constraining the Crustal and Mantle Conductivity Structures Beneath Islands by a Joint Inversion of Multi‐Source Magnetic Transfer Functions

Cited by 9 publications

References 114 publications

Hydrogen Diffusion in the Lower Mantle Revealed by Machine Learning Potentials

Hydrogen Diffusion in the Lower Mantle Revealed by Machine Learning Potentials

A Mantle Plume Beneath South China Revealed by Electrical Conductivity Obtained from Three-Dimensional Inversion of Geomagnetic Data

Enormously large tippers observed in southwest China: can realistic 3-D EM modeling reproduce them?

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