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<i>Ab initio</i>Calculations of the Linear and Nonlinear Optical Properties of Amino Acids

2010· article· en· W2127825477 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Physics Conference Series · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHyperpolarizabilityPolarizabilityAb initioAmino acidSecond-harmonic generationNonlinear opticalNonlinear systemComputational chemistryHarmonicChemistryNonlinear opticsAb initio quantum chemistry methodsMolecular physicsChemical physicsMaterials sciencePhysicsMoleculeQuantum mechanicsOrganic chemistryBiochemistryLaser

Abstract

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A number of proteins can assemble into chiral structures that display strong nonlinear optical activity. For instance, proteins such as myosin and collagen exhibit intense second harmonic generation (SHG). A large number of experimental studies on the SHG of proteins have been conducted; however few predictive models have been proposed that reliably relate the macroscopic SHG properties to the amino acids present in the peptidic chain. In this study, the linear polarizability (α), first (β) and second hyperpolarizability (γ) of all twenty amino acids was investigated by time-dependent Hartree-Fock calculations under physiological conditions. Ab initio calculations were performed using the GAMESSUS computational chemistry package. We have found that the aromatic amino acids give rise to the largest mean α, β and γ values. With this finding, we hope to apply this method to protein structures in order to understand how second harmonic signal is generated from individual amino acids, as well as, recognize how manipulation of the secondary structure of proteins might enhance SHG and third harmonic generation (THG).

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.

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 score0.026
Threshold uncertainty score0.466

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 head0.039
GPT teacher head0.281
Teacher spread0.242 · 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