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Record W2342354478 · doi:10.3390/met6040090

Characterization of Precipitates in a Microalloyed Steel Using Quantitative X-ray Diffraction

2016· article· en· W2342354478 on OpenAlexaff
J. B. Wiskel, Junfang Lu, Oladipo Omotoso, Douglas G. Ivey, H. Henein

Bibliographic record

VenueMetals · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsSuncor Energy (Canada)University of Alberta
Fundersnot available
KeywordsMaterials scienceCharacterization (materials science)DiffractionMetallurgyX-ray crystallographyCrystallographyChemistryNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

Quantitative X-ray diffraction (QXRD) (also known as the Rietveld method) was used to analyze the precipitates present in Grade 100 microalloyed steel. The precipitates were extracted from the steel using electrolytic dissolution and the residue from the dissolution was analyzed using XRD. The XRD pattern exhibited three (3) distinct diffraction peaks, and significant broadening of a fourth peak corresponding to the <10 nm size precipitates. QXRD analysis was applied to the XRD pattern to obtain precipitate size, composition, and weight fraction data for each of the four diffraction peaks observed. The predicted mean precipitate diameter and average atomic composition of the nano-size (<10 nm) precipitates was 4.7 nm and (Nb0.50Ti0.32Mo0.18)(C0.59N0.41), respectively. The predicted precipitate size correlates well with the average size of precipitates measured in previous work by the authors using both transmission electron microscopy (TEM) and small angle neutron scattering (SANS). The average atomic composition correlates well with the composition measured in this work using energy dispersive X-ray (EDX) analysis of individual nano-sized precipitates. The calculated weight fraction of the nano-size precipitates in the extracted residue was 42.2 wt. %. The calculated atomic compositions of the other three diffraction peaks were TiN, (Ti0.87Nb0.13)N, and (Nb0.82Ti0.18)(C0.87N0.13) with weight fraction values of 12.9 wt. %, 31.7 wt. %, and 13.1 wt. %, respectively. The sizes of both the (Ti0.87Nb0.13)N and the (Nb0.82Ti0.18)(C0.87N0.13) groups of precipitates were directly measured and were observed to range from 150 nm to 570 nm and from 90 nm to 475 nm, respectively. QXRD was unable to determine a reasonable mean precipitate size for either of these two groups of precipitates. The wide compositional range (i.e., varying levels of Nb and Ti) of these precipitates (as measured by EDX) resulted in XRD peak broadening that was erroneously interpreted as a size broadening effect.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.024
GPT teacher head0.236
Teacher spread0.212 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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