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Record W7064422008

Assessing different types of disorder in carbonate
\nminerals with vibrational spectroscopy

2015· dissertation· en· W7064422008 on OpenAlexafffundabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Light Source
KeywordsCalciteRaman spectroscopyFourier transform infrared spectroscopyMolecular vibrationX-ray absorption fine structureInfrared spectroscopyInfraredAnalytical Chemistry (journal)SpectroscopyCalcium carbonate
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, calcite was used as a test case to study the effects of structural disorder \non vibrational modes. Vibrational modes were examined using Fourier transform \ninfrared (FTIR) and Raman spectroscopy. Structural disorder was assessed by using \nX-ray diffraction (XRD) and X-ray absorption fine structure (XAFS) measurements. \nData for temperature dependent FTIR, FTIR-photoacoustic (FTIR-PAS), and XAFS \nmeasurements were collected at the Canadian Light Source Inc. (Saskatoon, SK). \nFour normal vibrational modes of calcite were thoroughly investigated: the symmetric \nin-plane stretch (v₁, Raman active), out-of plane bend (v₂, IR active), asymmetric \nin-plane stretch (v₃, IR active), and in-plane bend (v₄, Raman and IR active). \nShapes of the v₁ and v₄ peaks are affected by long-range disorder and temperature, \nwhile the v₂ and v₃ peaks remain unchanged. By comparing the FTIR absorption \nspectra of different calcium carbonate polymorphs, we suggest that planar carbonate \narrangements are the key to cause v₄ broadening at higher temperatures and with \nstructural defects. \nTo explore the effects of structural defects in more detail, crystalline domain \nsize, lattice strain, and microstrain fluctuation values were calculated from XRD data. \nLong-range disorder strongly affects the vibrations in calcite. Bonding distances and \ncoordination environments in calcite based minerals (plasters) were assessed from \ntheir XAFS spectra. Results indicate that the local environments are dependent on the secondary phases (mainly Ca(OH)₂) in them. My thesis work demonstrates that \nparing FTIR with other techniques is more effective for researchers. \nWeak peaks related to the combination and isotopic modes in a calcite FTIR \nabsorption spectrum were also well studied. My thesis work demonstrates that weak \npeaks at 848 cm⁻¹ and 1398 cm⁻¹ in a FTIR absorption spectrum of calcite are due \nto the v₂ and v₃ vibrations of ¹³CO₃²⁻ rather than combination modes. These two \npeaks become stronger in spectra of calcite with a higher ¹³C concentration. Also, \nthe ratio between areas of the 848 cm⁻¹ peak and the ¹³CO₃²⁻ v₂ peak in a FTIR \ntransmittance spectrum match the natural abundance ratio of ¹³C:¹²C (near 1%). An \ninteresting phenomenon is that positions of these two peaks do not maintain with ¹³C \nconcentration changes. Theoretical calculations performed by our colleagues (Anna \nHirsch and Dr. Leeor Kronik, Weizmann Institute of Science, Israel) confirm my \nthesis results. \nMy thesis work shows that FTIR-photoacoustic (FTIR-PAS) spectroscopy is \nan appropriate technique to study weak isotopic and combination-mode peaks since \nthey are relatively enhanced under an acoustic detector. Origins of combination-mode \npeaks were discussed, and quantitative analyses of the ¹³C v₂ peak were carried out \nbased on FTIR-PAS spectra. A surprising finding is that the ¹³C v₂ mode presents \ncrystallinity dependency, while the ¹²C v₂ mode is not.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2015
Admission routes3
Has abstractyes

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