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Record W6959130241 · doi:10.1021/jp800777e.s001

Fragmentation-Based QM/MM Simulations: Length Dependence of Chain Dynamics and Hydrogen Bonding of Polyethylene Oxide and Polyethylene in Aqueous Solutions

2016· article· en· W6959130241 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

VenueFigshare · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsMolecular dynamicsAqueous solutionIntermolecular forceFragmentation (computing)Hydrogen bondPolyethylene oxidePolyethylene

Abstract

fetched live from OpenAlex

Molecular fragmentation quantum mechanics (QM) calculations have been combined with molecular mechanics (MM) to construct the fragmentation QM/MM method for simulations of dilute solutions of macromolecules. We adopt the electrostatics embedding QM/MM model, where the low-cost generalized energy-based fragmentation calculations are employed for the QM part. Conformation energy calculations, geometry optimizations, and Born−Oppenheimer molecular dynamics simulations of poly(ethylene oxide), PEO<sub><i>n</i></sub> (<i>n</i> = 6−20), and polyethylene, PE<i><sub>n</sub></i> (<i>n</i> = 9−30), in aqueous solution have been performed within the framework of both fragmentation and conventional QM/MM methods. The intermolecular hydrogen bonding and chain configurations obtained from the fragmentation QM/MM simulations are consistent with the conventional QM/MM method. The length dependence of chain conformations and dynamics of PEO and PE oligomers in aqueous solutions is also investigated through the fragmentation QM/MM molecular dynamics simulations.

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 score0.386

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 head0.017
GPT teacher head0.259
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