Results 181 to 190 of about 771,265 (286)

Multistage Evolution and Inheritance in a Magma‐Poor Conjugate Margin: Insights From Serpentinized Peridotites of the Newfoundland Margin (ODP Hole 1277A)

Geochemistry, Geophysics, Geosystems, Volume 27, Issue 10, October 2026.
Abstract The nature of mantle sections exhumed at magma‐poor rifted margins remains poorly constrained, largely because direct sampling of mantle in modern passive margins is exceptionally rare. The Iberia–Newfoundland system is unique in providing drilled mantle rocks on both conjugate margins, offering an unprecedented glimpse into mantle ...
A. Secchiari, M. Godard, A. Montanini
wiley   +1 more source

Tectonic Evolution of the Mariana Trough

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 10, October 2026.
Abstract The Mariana Trough is an active back‐arc basin formed by subduction of the Pacific Plate beneath the Philippine Sea Plate and provides an ideal setting for investigating the evolution of back‐arc basins. In this study, we compile bathymetric, magnetic, and gravity data to reconstruct the formation history of the entire basin.
Seitaro Ono, Kyoko Okino, Nobukazu Seama, Toshitsugu Yamazaki, Hisanori Iwamoto   +4 more
wiley   +1 more source

Sluggish post-garnet transformation controls slab stagnation at the uppermost lower mantle. [PDF]

Nat Commun
Shen Y, Yang J, Zhao L.
europepmc   +1 more source

Episodic Change, Quiescence, and Recovery of Earth's Inner Core Surface

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 10, October 2026.
Abstract While a consensus has emerged that the hypothesis of inner core differential rotation cannot provide a consistent explanation for the seismic data, it remains debated whether the seismic data indicate a concurrence of a temporal change of inner core surface with an inner core differential rotation or the temporal change of inner core surface ...
Xin Zhang, Lianxing Wen
wiley   +1 more source

Melt burst events in a dominantly amagmatic lithosphere at Gakkel Ridge in the Arctic Ocean. [PDF]

Nat Commun
Zhou F, Grevemeyer I, Dyment J.
europepmc   +1 more source

A Machine‐Learning Surrogate for Differentiable Phase Equilibrium Modeling of Mantle Rocks on a Planetary Scale

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Modeling processes within Earth's and other planetary bodies' mantle requires constraints from phase equilibrium to infer how changes in phase abundance and composition affect physical properties and geochemical processes. When applying such thermodynamic models on a planetary scale, performance becomes especially crucial.
Philip Hartmeier, Pierre Lanari
wiley   +1 more source

Sulfur isotope heterogeneity in Martian shergottites reveals early atmosphere - mantle exchange. [PDF]

Commun Earth Environ
Patil K, Dottin JW, Fu H, Monteleone B, Chatterjee N, Hooper N, Izon G, Adams JC, Irving A, Shearer CK, Franz HB, Ono S.   +11 more
europepmc   +1 more source

IGyTheM: Integrating Geodynamics With Thermodynamics Using Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Achieving a comprehensive understanding of mantle convection requires integrated models that couple mantle dynamics with thermodynamic properties. Although advances in computational geodynamics have substantially improved our ability to simulate the underlying physical processes, incorporating thermodynamics into self‐consistent geodynamic ...
Qian Yuan, Paul D. Asimow, Michael Gurnis, Paula Antoshechkina, Junjie Dong   +4 more
wiley   +1 more source

Clinical Impact of a Germline CD19 Variant on Treatment Outcome After CAR-T Cell Therapy in Relapsed/Refractory Mantle Cell Lymphoma. [PDF]

Cancers (Basel)
Ruckstuhl SA, Seipel K, Shaforostova I, Bertschinger M, Bacher U, Pabst T.   +5 more
europepmc   +1 more source

How Much Physics Should a Neural Network Know? Thermodynamics‐Informed Neural Networks for Rock Constitutive Modeling With Epistemic Uncertainty

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Machine learning offers a flexible route to constitutive modeling, with two emergent questions for geoscience applications: what level of thermodynamic constraint should be embedded in the network architecture, and how should predictive uncertainty be quantified when extrapolating from laboratory to field conditions? We address both challenges
Kangan Li, Tushar Mittal, Benjamin K. Holtzman, Seth Saltiel   +3 more
wiley   +1 more source