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Record W2318586941 · doi:10.15278/isms.2015.ti03

ULTRAFAST SPECTROSCOPIC AND AB INITIO COMPUTATIONAL INVESTIGATIONS ON SOLVATIONDYNAMICS OF NEUTRAL AND DEPROTONATED TYROSINE.

2015· article· en· W2318586941 on OpenAlexaff
Takashige Fujiwara, Marek Z. Zgierski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsNational Research Council CanadaSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsProtonationSolvationChemistryDeprotonationExcited stateComputational chemistryPhotoexcitationTime-dependent density functional theoryAb initioPhotochemistryAb initio quantum chemistry methodsChemical physicsPhysical chemistrySolventDensity functional theoryMoleculeAtomic physicsOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

We have studied one of the aromatic amino acids, tyrosine, regarding its photophysical properties in various solvent conditions by using a femtosecond fluorescence up-conversion technique and high-level TDDFT and CC2 computations.In this talk, profound details not only on ultrafast solvation dynamics on a neutral tyrosine in various solvents, but also on the excited-state dynamics for a single-(or doubly-) deprotonated tyrosine under various pH solutions will be presented.In high basicity, a tyrosine shows different absorption/emission spectra, and a total spectrum consists of a combination of these individual spectra that depend on the pH of the solution.The time scale of acid-base equilibrium is essential in solvation dynamics; whereas the protonation is simply controlled by diffusion, the de-protonation is considered to be slow process such that acid-base equilibrium may not be reached in the short-lived excited state after photo-excitation.Experimental and computational approaches taken and insights obtained in this concerted work will be described.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.412

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 head0.026
GPT teacher head0.252
Teacher spread0.226 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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