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Record W2140330662 · doi:10.1039/c1cp20188c

Iron oxyhydroxide nanoparticles formed by forced hydrolysis: dependence of phase composition on solution concentration

2011· article· en· W2140330662 on OpenAlexafffund
Dong Fu, Peter Keech, Xueliang Sun, J. Clara Wren

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2011
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGoethiteLepidocrociteFerricPhase (matter)NanoparticleHydrolysisEnthalpyChemistryParticle (ecology)Chemical engineeringInorganic chemistryParticle sizeNanometreIron oxideHydrous ferric oxidesThermodynamicsPhysical chemistryOrganic chemistrySorptionAdsorption

Abstract

fetched live from OpenAlex

Nanoparticles of single-phase lepidocrocite (γ-FeOOH) and goethite (α-FeOOH) have been synthesized by forced hydrolysis of ferric nitrate with no other additives, and the particles have been characterized by XRD, FT-IR and TEM. At low Fe(NO(3))(3) concentrations the hydrolysis product is predominantly γ-FeOOH, while at high concentrations it is α-FeOOH. These particles are nanometers in size and fall within narrow particle size distributions. The dependence of the oxyhydoxide phase on ferric nitrate concentration is attributed to two thermodynamic factors, the enthalpy of formation and the surface enthalpy of hydration at the oxide-water interface (which is a function of surface area). Two potential mechanisms for the phase-specific growth are proposed that explain the solution concentration dependence of the phase formed. Three other common nanoscale particles (α-Fe(2)O(3), Fe(3)O(4) and γ-Fe(2)O(3)) have also been prepared by relatively simple thermal/chemical treatment of the γ-FeOOH nanoparticles.

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 categoriesMeta-epidemiology (narrow)
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 score0.015
Threshold uncertainty score1.000

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)0.0000.000

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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 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

Citations66
Published2011
Admission routes2
Has abstractyes

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