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Record W4407352234 · doi:10.1038/s41561-024-01629-5

Geochemistry of lithospheric aqueous fluids modified by nanoconfinement

2025· article· en· W4407352234 on OpenAlexaff
Alireza Chogani, Helen E. King, Benjamin M. Tutolo, Aleksandar Živković, Oliver Plümper

Bibliographic record

VenueNature Geoscience · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsAlberta EnergyUniversity of Calgary
Fundersnot available
KeywordsLithosphereGeologyGeochemistryAqueous solutionPetrologyEarth scienceChemistrySeismologyTectonicsPhysical chemistry

Abstract

fetched live from OpenAlex

Water is a principal component of Earth's fluids, and its interaction with rocks governs lithospheric geochemical and geodynamic processes. Water-rock interactions are crucial in societally relevant resource management, including subsurface extraction and storage of energy, the deep carbon cycle and generating critical metal deposits. The prevailing view is that fluids navigate through the lithosphere without being influenced by the distinct properties that arise from matter confined at the nanoscale. Here we use electron microscopy and neutron scattering data to show that a diverse range of lithospheric rocks, including sandstones, peridotites and serpentinites, consistently show nanoporosity, predominantly with pore sizes < 100 nanometres. Using molecular dynamics simulations, we demonstrate that water's dielectric permittivity-a fundamental property that governs its geochemical behaviour-diverges in nanoconfinement from its bulk counterpart under conditions ranging from ambient to extremes of 700 °C and 5 GPa. Our geochemical simulations suggest that changes in water permittivity due to confinement will decrease mineral solubility, a process that is not currently considered in models of fluid-rock interactions. Given that permittivity is also intimately linked to ion speciation, pore-size-dependent properties should be expected to exert a primary influence on rock reactivity and the geochemical evolution of fluids during fluid-rock interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.214
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes1
Has abstractyes

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