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Record W4387696329 · doi:10.3897/aca.6.e108262

Organomineralization of dolomite in hypersaline microbial mats from Qatar sabkhas visualized by TEM & STXM

2023· article· en· W4387696329 on OpenAlexaffabout
Ivan A. Strakhov, Zach Diloreto, Jassim A. Al‐Khayat, Maria Dittrich

Bibliographic record

VenueARPHA Conference Abstracts · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersQatar Foundation
KeywordsDolomiteCarbonateXANESTransmission electron microscopyMineralization (soil science)Selected area diffractionMineralogyDissolutionCalciteChemistrySpectroscopyChemical engineeringAnalytical Chemistry (journal)GeologyEnvironmental chemistryMaterials scienceNanotechnologyMetallurgyPhysicsNitrogen

Abstract

fetched live from OpenAlex

Deep insight into the low-temperature mineralization mechanism of dolomite in sediments has remained elusive. This issue is popularly termed “The Dolomite Problem” due to its multifactorial nature. Dolomite has been observed to mineralize in the exopolymeric substances produced by microbial mat communities (Bontognali et al. 2013), where productivity is high. One working hypothesis suggests that degrading organic matter in hypersaline environments releases the necessary component ions, increasing saturation with respect to dolomite (DiLoreto et al. 2019, Dupraz et al. 2009, Petrash et al. 2017). Other models suggest a dissolution-reprecipitation reaction of calcite to dolomite (Rivers 2023). High-resolution micro-spectroscopy techniques (such as transmission electron microscopy, TEM; and scanning transmission X-ray microscopy, STXM) can be used to determine chemical changes in crystals nucleating in a matrix, however to date very little studies have focused on observing dolomite mineralization at the nano-scale. The present study investigates microbial mats collected from hypersaline salt flats in the Persian gulf at micro- to nano-meter scales using high-spatial and -energy resolution TEM (Thermo Scientific Talos 200X at the Canadian Centre for Electron Microscopy) and STXM (PolLux Beamline at the Swiss Light Source at Paul Scherrer Institut), specifically to see changes in carbonate mineralization due to interactions with organic matter. C, Ca and O elemental maps of carbonate crystals were obtained with EDXS (energy-dispersive X-ray spectroscopy) in TEM. These crystals were also indexed by SAED (selected area electron diffraction in TEM). Fine spectral signatures (near-edge X-ray absorption fine structures, or NEXAFS) at the C K-edge (280-290 eV) and Ca L 2,3 -edge (344-356 eV) in STXM were used to determine the chemical identity of carbonate minerals and surrounding organic matter of the microbial mats. The results of the study show that dolomite nucleates in close association with the organic matter of the mats, where degradation is highest (defined in our adjacent study as the increase in C:N ratio). In TEM, polycrystalline dolomite is seen mineralizing in the matrix of the microbial mat organic material (Fig. 1). In STXM, the identity of the carbonate mineral changes from calcite on the outside to dolomite on the inside of the microbial mat particle (Fig. 2). In addition, our microsensor observations of elevated H 2 S concentrations, surface oxygenation from oxygenic phototrophy, high reduction potential, high organic carbon, high Mg:Ca ratio and high organic matter degradation (by C:N ratio) in each of the studied microbial mats confirms that the ideal dolomite mineralization conditions according to models of the dolomite problem are present in each case.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.277
Teacher spread0.236 · 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.

Study designObservational
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
Published2023
Admission routes2
Has abstractyes

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