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Record W2792494129 · doi:10.1002/cptc.201800022

The Light‐Driven Isomerization of Aqueous Nitrate: A Theoretical Perspective

2018· article· en· W2792494129 on OpenAlexaff
Jan‐Michael Mewes, Paul Jerabek, D. Scott Bohle, Peter Schwerdtfeger

Bibliographic record

VenueChemPhotoChem · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsMcGill University
FundersAlexander von Humboldt-Stiftung
KeywordsConical intersectionChemistryPhotochemistryIsomerizationChemical physicsExcited stateAqueous solutionSolvationExergonic reactionSinglet stateAtomic physicsExcitationComputational chemistryIonMolecular physicsPhysical chemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract The reaction mechanism for the rearrangement of the nitrate anion to its cis and trans peroxonitrite isomers is investigated in detail by quantum theoretical methods. The electronic ground state potential energy hypersurface (PES) features a bifurcation point along the minimum energy path at high energy, while the intrinsic reaction path moves the bifurcation point towards the transition state (TS) between the two peroxynitrite isomers. Coupled‐cluster calculations reveal a high‐lying transition state (4.6 eV) for the major photochemical isomerization pathway via an S 1 /S 0 conical intersection, explaining why electronic excitation of the bright singlet states with λ =200–270 nm is required to trigger formation of peroxinitrite, while excitation of the weak band around 300 nm (wavelengths >270 nm) does instead lead to non‐radiative regeneration of NO 3 − . The influence of the aqueous solution is considered using polarizable continuum solvation in combination with explicitly solvated model systems. Despite the charged and polar nature of nitrate, we find that solvent effects exert a suprisingly small influence, neither changing the shape of the PES, nor affecting the nature of the excited states.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.379

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 studies0.0000.001
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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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.

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

Citations3
Published2018
Admission routes1
Has abstractyes

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