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Record W1977992803 · doi:10.1021/jp036007v

Calculation of Free Energy Profiles for Elementary Bimolecular Reactions by ab Initio Molecular Dynamics:  Sampling Methods and Thermostat Considerations

2004· article· en· W1977992803 on OpenAlexaff
Evan Kelly, Michael Seth, Tom Ziegler

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistryThermostatAb initioComputational chemistryDensity functional theoryElementary reactionAb initio quantum chemistry methodsPhysical chemistryThermodynamicsMoleculeOrganic chemistryPhysicsKineticsQuantum mechanics

Abstract

fetched live from OpenAlex

A study designed to refine the procedure for performing ab initio molecular dynamics calculations (AIMD) on chemical reactions is presented. Of key interest is the calculation of changes in free energy along the entire reaction path. Several simple elementary reactions are studied with the Car−Parrinello projector augmented-wave (CP−PAW) density-functional theory (DFT) methodology. The illustrative gas-phase bimolecular addition reactions are (i) a σ complexation of BH 3 + H 2 O → H 2 O·BH 3, (ii) the Diels−Alder reactions of butadiene with ethene, C 4 H 6 + C 2 H 4 → cyclohexene, 1,3-cyclopentadiene (CP) and ethene, CP + C 2 H 4 → norbornene, and the stereoselective reaction of 5-amino-CP with ethene, amino-CP + C 2 H 4 → amino-norbornene, (iii) the carbene cyclopropanation Cl 2 C + C 2 H 4 → Cl 2 C 3 H 4, and (iv) the dimerization of ketene. These reactions were used to test both the slow-growth and point-wise thermodynamic integration (STI and PTI) methods of phase-space sampling as well as the Nosé−Hoover and Andersen thermostats. It is found that the PTI technique is potentially superior to the slow-growth method in terms of computational expense and is at least as accurate. The Nosé−Hoover thermostat appears to be inadequate for most of the reactions modeled here, whereas the stochastic Andersen thermostat affords more accurate results.

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: none
Teacher disagreement score0.656
Threshold uncertainty score0.414

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 head0.013
GPT teacher head0.317
Teacher spread0.304 · 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

Citations51
Published2004
Admission routes1
Has abstractyes

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