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Record W2328864223 · doi:10.1021/ie301241h

Combined Application of in Situ FBRM, ATR-FTIR, and Raman on Polymorphism Transformation Monitoring During the Cooling Crystallization

2012· article· en· W2328864223 on OpenAlexaff
Yingying Zhao, Junsheng Yuan, Zhiyong Ji, Jingkang Wang, Sohrab Rohani

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2012
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsWestern University
FundersProgram for Changjiang Scholars and Innovative Research Team in UniversityNational Natural Science Foundation of China
KeywordsCrystallizationRaman spectroscopyIn situPolymorphism (computer science)Fourier transform infrared spectroscopyMetastabilityChemistryAttenuated total reflectionKineticsTransformation (genetics)Analytical Chemistry (journal)Materials scienceChromatographyChemical engineeringOrganic chemistryOpticsBiochemistry

Abstract

fetched live from OpenAlex

This study evaluates the potential use of the FBRM, ATR-FTIR, and Raman for on line detection of polymorphic transformation of carbamazepine (CBZ) during the cooling crystallization. Changes in solution concentration as a function of time were quantified from the ATR-FTIR data. A new quantitative method of polymorphs ratio was developed using Raman spectroscopy for in situ monitoring during a solution-mediated transformation of carbamazepine from form II to form III in 1-propanol. The polymorphic forms initially crystallized from solution, in the absence of seeds, could be clearly identified by FBRM and showed good agreement with results of microscopic images. Furthermore, the kinetics of the conversion of carbamazepine from metastable form to the stable form at different cooling rates could be readily followed.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.316
Teacher spread0.258 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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