MétaCan
Menu
Back to cohort
Record W4287451071 · doi:10.2475/05.2022.02

Partial molar volumes of metal oxides in silicate melts: Effects of Coulombic interactions

2022· article· en· W4287451071 on OpenAlexaff
H.W. Nesbitt, Pascal Richet, G. Michael Bancroft, Grant S. Henderson

Bibliographic record

VenueAmerican Journal of Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsPartial molar propertyAlkali metalIonic radiusSilicateChemistryPartial chargeMolar volumeIonic potentialIonic bondingPartial oxidationInorganic chemistryOxideIonCrystallographyPhysical chemistryThermodynamicsAqueous solutionCatalysisOrganic chemistryMolecule

Abstract

fetched live from OpenAlex

Alkaline, alkaline earth, many 3d and most 4f modifier oxides dissolved in siliceous melts mix *non-ideally* with SiO~2~ to produce *linear*, density-compositional mixing trends from which partial molar volumes of modifier oxides (*V*\*) are determined. An analysis of these experimental data reveals that the partial molar volumes of alkali, alkaline earths, most 4f and many 3d modifier oxides partial molar volumes are accurately reproduced by: where F~C~ = (z^+^•z^−^)/d^2^ (Coulomb9s Law) and z indicates charge. The bond length 'd' is the sum of the radii of the cation (M^+^, M^2+^, M^3+^ or M^4+^) and oxide ion (O^2−^) observed in ionic crystals. The coefficients 'm' and 'b' are 0.325 and 1.38 Å/atom respectively. Partial molar volumes of network-forming oxides also conform to the above equation where 'm' = ∼3.25 and 'b' is 1.68 Å/atom. Coulomb9s force of attraction (F~C~) is the product of the cationic field strength (z^+^/d^2^) and the charge on an anion, where 'd' is the distance separating the centers of the two charges. In silicate melts containing modifier cations, apical O atoms of Si tetrahedra are negatively charged and are displaced toward the cations due to Coulombic attraction. The resulting collapse around the cations is referred to as 'electrostriction'. Partial molar volumes (*V*\*) of modifier oxides are thus composed of two terms, the volume of the polyhedron of the modifier cation (V~Poly~) and a volume associated with collapse of tetrahedra around the cation (V~Col~): V~Col~ is negative for all modifier oxides and becomes increasingly negative with increased charge on the cation and with increased coordination number (CN). V~Poly~ is itself composed of two terms, an intrinsic volume (V~Int~) and an excluded volume (V~Ex~). The intrinsic volume can be calculated using cationic and O^2−^ radii evaluated from ionic crystals. V~Ex~ reflects the state of packing around cationic polyhedra. It is equal to 6.83 Å^3^/atom for all modifier oxides so that the expression for V~Poly~ is: A linear relationship exists between V~Poly~ and V~Col~ which results in the observed linear density-composition trends from which partial molar volumes are determined. In spite of their linearity, these trends are the result of non-ideal mixing of modifier oxide and SiO~2~ components in siliceous melts. Our finding that tetrahedra collapse around modifier cations differs from the traditional perspective where modifier cations were considered to occupy voids within the silicate network but otherwise had limited effect on melt structure. These results demonstrate that modifier cations affect the network substantially by causing surrounding tetrahedra to rotate, twist, tilt and flex during their collapse toward modifier cations.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of ScienceSame topicGlass properties and applicationsFrench-language works237,207