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Record W3166675557 · doi:10.5194/egusphere-egu21-1410

Molecular dynamics approach to assess aqueous alteration of potassium-rich feldspar surfaces

2021· article· en· W3166675557 on OpenAlexaff
Anand Kumar, Allan K. Bertram, G. N. Patey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNucleationChemistryPotassiumIce nucleusMolecular dynamicsCrystallographyComputational chemistry

Abstract

fetched live from OpenAlex

Ice clouds play an important role in the Earth’s radiative budget and hence climate. Heterogeneous ice nucleation, a major pathway for ice formation in cirrus and mixed-phase clouds, is induced by active sites present on atmospheric aerosol particles termed as ice-nucleating particles. Feldspars have been shown to be highly ice nucleation active. Despite the importance of mineral dusts for ice nucleation, the role of atmospheric aging (e.g. surface alteration due to interactions with chemical species) on their ice nucleation efficiency is largely unknown. This is primarily due to the lack of microscopic level insight into nucleation from laboratory/field-based experiments, due to the inability to experimentally access the small spatial and temporal scales at which nucleation process occurs – a problem that can be potentially tackled with computer simulations. We utilize direct Molecular Dynamics simulations (GROMACS 5.1.4) to investigate the interactions of solutes with different surfaces of potassium feldspar mineral (microcline) and the corresponding interfacial water structure at a microscopic scale. We investigated the interactions of monovalent cations (H3O+, (NH4)+, Li+, K+, Cs+) with various surfaces of microcline, and subsequent effects on the near-surface water structure at 300 K. The investigated surfaces include the perfect cleavage planes, (001) and (010), as well as the high energy plane (100) of microcline. Feldspar is modeled as semi-rigid (lattice atoms fixed expect K+ and H of surface OH) and as fully flexible (all lattice atoms free to move) with the CLAYFF force field, and the TIP4P/Ice model is employed for water. Results show that on simulation timescales, lattice vibration is necessary for ion exchange between added cation and lattice K+, albeit at different exchange rates for the 3 planes. None of the 3 flexible surfaces show any preference for over K+ in terms of ion exchange within the simulation timescale. Both the semi-rigid and flexible surfaces show higher adsorption of molecular cations ((NH4)+ and H3O+) compared with the simple spherical cations. In addition, we do not observe ice nucleation on modified microcline surfaces (both semi-rigid and flexible) at a supercooled temperature of 230 K within the simulation timescale. To conclude, the presented work provides an improved understanding of the processes modifying the feldspar surfaces in water and aqueous solutions and its possible relevance for ice formation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.220
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2021
Admission routes1
Has abstractyes

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