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Record W2077896935 · doi:10.1021/ic0608391

An ab Initio Molecular Dynamics and Density Functional Theory Study of the Formation of Phosphate Chains from Metathiophosphates

2006· article· en· W2077896935 on OpenAlexaff
Nicholas J. Mosey, Tom K. Woo

Bibliographic record

VenueInorganic Chemistry · 2006
Typearticle
Languageen
FieldChemistry
TopicChemical Reaction Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsChemistryAb initioMoleculeDensity functional theoryPhosphateComputational chemistryMolecular dynamicsYield (engineering)Chemical physicsPolymerizationAtom (system on chip)ThermodynamicsOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

The reactions that occur between metathiophosphate (MTP) molecules are identified and examined through ab initio molecular dynamics simulations and static quantum chemical calculations at the density functional level of theory. The simulations show that certain types of MTPs can react to yield phosphate chains, while others only dimerize. These differences are rationalized in terms of reaction energies and the electronic structures of these molecules. In the reaction leading to the formation of phosphate chains, the reactive center, a tri-coordinate phosphorus atom, is continually regenerated. A polymerization mechanism linking MTPs to phosphate chains is developed on the basis of these results. This information sheds light on the underlying processes that may be responsible for the formation of phosphates under high-temperature conditions and may prove useful in the development of protocols for the rational synthesis of complex phosphate structures.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations15
Published2006
Admission routes1
Has abstractyes

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