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Record W4389426713 · doi:10.36939/ir.202312071601

Estimated Detection Limits of Carboxylates in Palagonite by X-ray Diffraction and Reflectance Spectroscopy

2023· dissertation· en· W4389426713 on OpenAlexafffund
D. M. Applin

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Winnipeg
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyMinistère des relations internationales et de la FrancophonieResearch Manitoba
KeywordsMars Exploration ProgramSpectroscopyAnalytical Chemistry (journal)RegolithInfrared spectroscopyDetection limitMineralogyVNIRDiffuse reflectionChemistryMaterials scienceOpticsReflectivityPhysicsAstrobiologyChromatography

Abstract

fetched live from OpenAlex

Low molecular weight carboxylates (carbonates, oxalates, formates, and acetates) are either known or are expected to be present on the surface of Mars. Previous work has suggested these phases to be present in Gale Crater materials at nearly the expected detection limit (LOD) for crystalline materials with the Mars Science Laboratory (MSL)Curiosity rover CheMin X-ray diffraction (XRD) instrument. Detection limits of these materials by CheMin-like XRD and reflectance spectroscopy are poorly constrained, thus leading to uncertainties in detectability with these types of instruments. I have filled this knowledge gap by making intimate mixtures of a variety of carboxylates with the JSC Mars-1a regolith analogue material and measured their XRD patterns with a CheMin-like breadboard and reflectance spectra with instruments analogous to the SuperCam instrument on the Mars Perseverance rover. I used simple linear regression to create calibration curves to estimate LODs and compared and contrasted ten different LOD calculations previously used for XRD. I found that the carboxylates measured have LODs near 1.0 wt.% by XRD. Oxalate minerals are likely undetectable by reflectance spectroscopy in bulk materials at expected concentrations, while acetate and formate minerals have relatively low LODs at near-infrared wavelengths due to their sharp and strong absorption bands. Carbonate minerals may show decreasing LODs with increasing grain size in reflectance spectra and have relatively high LODs at near-infrared wavelengths for fine grained powders and relatively low LODs when using the 3950 nm absorption band at all grain sizes. Application of these data to CheMin observations show that my data could accurately detect low concentrations of siderite at nearly the same values determined from previous CheMin data processing within error and within an average of 0.5-1.0 wt.% where siderite was detected. After applying the calibration curves from the other carboxylates, I did not find strong evidence for their detection in any of the CheMin data. Some samples, primarily the Gale crater Rocknest aeolian material may contain some concentration of whewellite which may be consistent with the analysis of the Sample Analysis at Mars (SAM) data, but detection may be complicated by overlapping plagioclase Bragg peaks. I applied the measured reflectance spectra from 350 to 4000 nm to some data collected by the SuperCam instrument at Jezero crater that were implied to contain organic compounds through analysis of Perseverance Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) data. I did not find evidence for carboxylates in the reflectance spectra except for Mg-rich anhydrous carbonates, and I determined the concentration to be between roughly 5.0 and 20.0 wt.%, which is broadly consistent with the previous analyses of these samples by radiative transfer modelling.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.282
Teacher spread0.266 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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